Annals of Warsaw University of Life Sciences

Transkrypt

ISSN 1898-8830
Annals of Warsaw University of Life Sciences – SGGW
Animal Science No 54 (1) 2015
ISSN 1898-8830
1898 8830
Annals
of Warsaw
University
of Life
Sciences
– SGGW
Animal Science
No 54 (1)
2015
Agriculture
(Agricultural and Forest Engineering)
Animal Science
Forestry and Wood Technology
Horticulture and Landscape Architecture
Land Reclamation
Editorial Board
Bogdan Brzeziecki
Ewa Dobrowolska
Włodzimierz Kluciński
Anna Kołłajtis-Dołowy
Andrzej Lenart
Małgorzata Łobocka
Józef Mosiej
Jan Niemiec
Arkadiusz Orłowski
Maria Parlińska
Aurelia Radzik-Rant
Stanisław Stępka
Marek Szyndel
Czesław Waszkiewicz
Distribution
Annals are distributed by the Bookshop
of Warsaw University of Life Sciences
Press, 166 Nowoursynowska St., Warsaw,
Poland.
WARSAW UNIVERSITY
OF LIFE SCIENCES PRESS
166 Nowoursynowska St., 02-787 Warsaw
Poland, tel. (48 22) 593 55 20
e-mail: [email protected]
www.wydawnictwosggw.pl
Agriculture
Animal Science
Land Reclamation
Annals of Warsaw University of Life
Sciences were originally published in 1957
as Zeszyty Naukowe SGGW (Scientific Fascicles of SGGW). In 1980 the name was changed to Annals of Warsaw
University of Life Sciences.
The Annals (5 subject series) are published once or twice a year and will carry previously unpublished papers that are mainly
in English, but also in French, German or
Russian, followed by a short summary in
Polish. Manuscripts for publication should
be typewritten and submitted to the Warsaw
University of Life Sciences Press in two
copies. Papers submitted for consideration
by the Editorial board should not exceed 0.5
of a printed sheet (about 11 pages including illustrations, and should consist of the
following elements: 1) name and surname
of the author, 2) title of the paper, 3) abstract
(about 20 lines), 4) text of the paper, 5) date
when the paper was sent to the Warsaw University of Life Sciences Press and mailing
address of the author, 6) summary (one page),
7) tables and figures with captions. Authors
receive twenty five offprints free of change.
Annals
of Warsaw
University
of Life
Sciences
– SGGW
Animal Science No 54 (1)
Warsaw 2015
Contents
BALCERAK M., KUNOWSKA-SLÓSARZ
M., SLÓSARZ J., GOŁĘBIEWSKI M.,
BENET M., KUCZYŃSKA B., PRZYSUCHA T., NAŁĘCZ-TARWACKA T.
Influence of the breed and country of origin on milk performance of primiparous
cows
5
DYMNICKI E., GOŁĘBIEWSKI M., WÓJCIK A., PUPPEL K., KUCZYŃSKA B.,
SOSIN-BZDUCHA E., SZULC T. Changes in cow’s milk composition and physical
properties during the uninterrupted milking
process
15
GOŁĘBIEWSKI M., PIOTROWSKI T.,
BRZOZOWSKI P., GRODZKI H., PRZYSUCHA T., SLÓSARZ J., KUNOWSKA-SLÓSARZ M., NAŁĘCZ-TARWACKA T.,
WÓJCIK A. Relation between the shape
and course of lactation curve and production traits of Polish Holstein-Friesian and
Montbeliarde cows
27
KUCZYŃSKA B., PUPPEL K., NAŁĘCZ-TARWACKA T., CZUB M. Variation in the
activity of stearoyl-CoA desaturase enzyme
and endogenous precursors of unsaturated
fatty acids in cow’s milk during grazing
season
37
KUCZYŃSKA B., KAPUSTA A., PUPPEL K., NAŁĘCZ-TARWACKA T.,
BUDZIŃSKI A., GOŁĘBIEWSKI M.,
CZUB M., GRODZKI H. Relationships
between milk β-carotene concentrations
and the cytological quality of cow’s milk
45
KUCZYŃSKA B., BUDZIŃSKI A., KAPUSTA A., PUPPEL K., NAŁĘCZ-TARWACKA T., GOŁĘBIEWSKI M., WÓJCIK A.,
GRODZKI H. Relationships between
production traits and the parity of Polish
Holstein-Friesian cows
51
NAŁĘCZ-TARWACKA T., GOŁĘBIEWSKI M., KUCZYŃSKA B., PUPPEL K.,
WÓJCIK A., BRZEZIŃSKA M., CZUB M.,
BENET M. Changes in the concentration
of selected minerals in milk and blood of
high-milking cows during lactation
59
PRZYSUCHA T., GOŁĘBIEWSKI M.,
GRODZKI H., WNĘK K., SLÓSARZ J.,
KUNOWSKA-SLÓSARZ M., TOKARSKI
P. Analysis of results assessment of growth
of Charolais beef cattle in Poland
71
PRZYSUCHA T., GOŁĘBIEWSKI M.,
GRODZKI H., WNĘK K., SLÓSARZ J.,
KUNOWSKA-SLÓSARZ M., TOKARSKI P. Analysis of Limousine beef cattle
recording results in Poland
83
SAKOWSKI T., PUPPEL K., GOŁĘBIEWSKI M., KUCZYŃSKA B., METERA E.,
GRODKOWSKI G. Influence of lactation
stage on selected blood parameters and biological value of cow milk during pasture season in organic system of production
95
WNĘK K., GOŁĘBIEWSKI M., PRZYSUCHA T., WOŹNIAK A., WIERZBICKI J.
Differences in the assessment of beef carcasses in EUROP system
105
SERIES EDITORIAL BOARD
Editor-in-Chief
prof. dr hab. Anna Rekiel
Animal Science series Secretary
dr Katarzyna Góral-Radziszewska
Address of Editorial Office
Wydział Nauk o Zwierzętach SGGW,
ul. Ciszewskiego 8, 02-786 Warszawa, Poland
EDITORS
dr Wojciech Hyb – statistics editor
Natalia Filipczak – English language consultant
Agata Kropiwiec – Polish language consultant
THEME EDITOR
dr hab. Elżbieta Michalska – Genetics and animal breeding
dr hab. Elżbieta Pezowicz – Biology and ecology
dr hab. Iwona Kosieradzka – Animal nutrition and feedstuffs
dr hab. Tadeusz Kaleta – Behaviour and welfare of animal
dr hab. Justyna Więcek – Animal husbandry and production technology
SERIES EDITOR
Anna Rekiel
SERIES EDITORIAL ADVISORY COUNCIL
Prof. DSc. Andrzej Chwalibóg (Denmark)
Prof. DSc. Konrad Dąbrowski (USA)
Prof. DSc. Ondrey Debréceni (Slovakia)
Prof. Ewgienij Dobruk (Belarus)
Prof. dr hab. Robert J. Eckert (Poland)
Prof. Dr Sophie Ermidou-Pollet (Greece)
Prof. dr hab. Grażyna Garbaczewska (Poland)
Prof. DSc. Luis L. Gosálvez (Spain)
Prof. DSc. Adrian Harrison (Denmark)
Prof. dr hab. Jarosław O. Horbańczuk (Poland)
Prof. dr hab. Marta Kamionek (Poland)
Prof. Dr Drago Kompan (Slovenia)
Prof. Dr Sándor Kukovics (Hungary)
Prof. Dr Stoycho Metodiev (Bulgarian)
Prof. DSc Francois K. Siebrits (RSA)
Prof. dr hab. Jacek Skomiał (Poland)
Prof. dr hab. Romuald Zabielski (Poland)
The Editorial Board (Office) of “Annals of Warsaw University of Life Sciences – SGGW. Animal Science”
informs that the printed version of the journal is the original version.
Redakcja „Annals of Warsaw University of Life Sciences – SGGW. Animal Science” informuje, że wersja
drukowana czasopisma jest wersją pierwotną (referencyjną).
Covered in: AGRO, Index Copernicus (5.85), CAB Direct, CEON, ARIANTA, ePNP.
Bazy: AGRO, Index Copernicus (5.85), CAB Direct, CEON – Biblioteka Nauki, ARIANTA, e-Publikacje
Nauki Polskiej.
WARSAW UNIVERSITY
ISSN 1898-8830
EDITORIAL STAFF
Anna Dołomisiewicz
Elżbieta Wojnarowska
Edition: 150 prints
PRINT: POLIMAX s.c., 161 L Nowoursynowska St.,
02-787 Warsaw
Animal Science No 54 (1), 2015: 5–14
(Ann. Warsaw Univ. of Life Sci. – SGGW, Anim. Sci. 54 (1), 2015)
Influence of the breed and country of origin on milk performance
of primiparous cows
MAREK BALCERAK1, MAŁGORZATA KUNOWSKA-SLÓSARZ1,
JAN SLÓSARZ1, MARCIN GOŁĘBIEWSKI1, MICHAŁ BENET2,
BEATA KUCZYŃSKA1, TOMASZ PRZYSUCHA1,
TERESA NAŁĘCZ-TARWACKA1
1
2
Department of Animal Breeding and Production, Warsaw University of Life Sciences – SGGW
Dairy Cooperative “Spomlek”
Abstract: Influence of the breed and country of
origin on milk performance of primiparous cows.
The aim of the study was comparison of the milk
performance of primiparous cows from six European countries with Polish Holstein-Friesians, as well
as to demonstrate the differences within the different genetic groups. Material consisted of data contained in the dairy reports gathered from 26 farm
“Healthy Cow” project. The analysis involved data
including milk yield and its chemical composition,
i.e.: fat, protein, lactose, solids, and urea somatic
cells count in milk. On the basis of these results, it
was found that the country of origin had significant
impact on daily milk yield, percentage of fat, percentage of protein, percentage of lactose and also
affected dry matter content, urea and somatic cells
in the milk of lactating cows. Research reviled that
there were not differences in milk performance
between imported and native cows. However, the
breed of cows had an strong impact on daily milk
production, percentage of protein, percentage of
lactose, percentage of dry weight, as well as urea
content and somatic cells count.
Key words: primiparous cow, breed, milk components, country of origin
INTRODUCTION
Import of breeding material from western
countries had a significant impact on the
genetic improvement on population of
Polish Holstein-Friesian cows (Barański
et al. 2008, Czubska et al. 2009). The
main advantages of the import of breeding material to Poland were improvement
of the milk production and chemical composition as well as correction of cow body
conformation (e.g. udder and feet). However, analysis conducted by other authors
haven’t clearly confirmed if imported
animals characterized by better milk
performance than native ones (Barański
et al. 2008, Czubska et al. 2009). This is
due to genetic-environment interaction, as
well as multi-environmental factors that
have stronger than genetic effect on cow
productivity (Sender et al. 1987, Dorynek
and Kliks 1998, Litwińczuk et al. 2000,
Matras et al. 2000, Sawa et al. 2000,
Nałęcz-Tarwacka et al. 2002). As the
main factor affecting the dairy performance of cows is the environment, to take
full advantage of breeding value of cow
in terms of production and health, genotype on the animal should be match with
specific environmental conditions. On the
other hand, the breed of cattle is known to
have a huge impact on the composition of
6
M. Balcerak et al.
milk. The most valuable breeds for chees
producing plants are: Polish Red, Simmental, Montbeliarde and Brown Swiss
(Barłowska et al. 2014, Malchiodi et al.
2014). Those breeds do not impress with
quantity of produced milk, but in terms
of the milk composition outperformed
other popular breeds in Poland. The raw
material obtained from these breeds had
significant higher protein content in milk,
particularly kappa casein fractions, which
is very valuable for cheese production.
Despite the obvious advantages of such
milk its production is marginal in Poland
due to the relatively small population of
these breeds (Choroszy 1997).
Many authors (Sablik et al. 2001,
Czaplicka et al. 2002, Czaplicka et al.
2003, Puchajda et al. 2003, Bogucki et
al. 2009, Cichołowicz et al. 2010) dealt
with the comparison of milk performance of native and imported cows. However, those researches hasn’t clearly confirmed that imported heifers performed
better than Polish ones. So it seems
advisable to compare the milk performance of imported cows, with native ones
in similar environmental conditions.
The aim of the study was therefore
confrontation milk recording data of
cows originated from six European countries and Poland and demonstrate the differences within the different breeds.
MATERIAL AND METHODS
The study was conducted on 26 farms,
involved in “Healthy Cow”. This project
was initiated by the Dairy Cooperative
“Spomlek” located in Radzyn Podlaski
in 2011. The main objective of the program is to improve the health of animals,
upgrade breeders skill, introduce the
latest research results in the field of dairy
farming and the economics into milk
production. The “Healthy Cow” program
cooperatives were: Veterinary Institute
in Pulawy Polish Research Institute;
Warsaw University of Life Sciences −
SGGW, Department of Animal Sciences
and the Polish Federation of Dairy Cattle
Breeders and Producers.
Research material consisted of data
contained in dairy reports (RW-2) prepared by the Polish Federation of Dairy
Cattle Breeders and Producers. The
reports were gathered from 26 farms and
totally involved 12,357 observations. In
the statistical analysis fallowing variables were studied: milk yield and the
content of the milk: fat, protein, lactose,
solids, urea and somatic cells.
The analyzed factors were:
• the effect of the country of origin of
animals on the results of milk performance as well the differences between
particular countries;
• the effect of the country of origin
of animals on the level of urea and
somatic cell count in milk;
• the effect of the breed on the milk performance results;
• the effect of breed on the level of urea,
and the number of somatic cells.
Statistical analysis was performed with
IBM SPSS 21 (2013) software by the following GLM model (differences between
means were estimated with the F test):
Y = μ + KPi + KP1j + Rk + eijk
where:
μ
– average general;
KPi – country of origine (Austria,
the Czech Republic, Denmark,
Germany, France, the Netherlands, Poland);
Influence of the breed and country of origin on milk performance of primiparous cows
KP1j – imported, native;
Rk
– breed: Brown Swiss (BS), Back
and White variety of Holstein-Friesian (HO), Red and White
variety of Holstein-Friesian
(RW), Norwegian Red (NR),
Simental (SM);
eijk – random error.
RESULTS AND DISSCUSION
Table 1 presents the effect of country
of origin of the heifers on the milk performance. Heifers originated from six
European countries including: Austria,
the Czech Republic, Denmark, Germany,
France, the Netherlands and Poland. As
a result of analysis highly significant (p
≤ 0.01) the influence of heifers origin
on their milk yield, and the percentage
content of fat, protein and lactose was
observed. The highest performance
characterized by animals from France,
which produced an average of 27.03 kg
of milk a day. The lowest yield was
reported in hefiers originating from the
Netherlands, which produced 18.29 kg
milk daily. Moreover, results reviled that
imported animals generally produced
more milk than native, except for heifers
brought from the Netherlands (Table 1).
Different results were obtained by Gnyp
et al. (2006), who in his study found the
highest dairy performance in animals
imported from the Netherlands, and the
lowest in French ones. Other results
reported by Skrzypek and Szukalski
(2006), confirmed the superiority of
cows imported from Germany in terms of
milk yield (21.25 kg/day) compared with
Polish ones (21 kg/day) at the same age.
In the study of Czaplicka et al. (2013)
yield of cows imported from France was
7
at 14.43 kg of milk a day, in contrast to
Polish Holstein-Friesian which produced
only 12.92 kg of milk a day. On the
other hand, according to Czarniawska-Piątkowska (2009), imported cows
had lower milk yields than Polish cows
domestic (native – 27.75 kg/day, imported – 27.54 kg/day). Similarly, in the
study of Kuczaj (2004) heifers imported
from the Netherlands, characterized by
a lower productivity of milk (9.10 kg/
/day) than Polish HO and RW (12.02 and
11.7 kg/day, respectively). Also Gnyp et
al. (2001) found higher milk yield (18.77
kg/day) of native cows compared with
cows imported from Germany (14.54 kg
milk yield). Similar results were reported
by Antkowiak and Kliks (1998) and
Zdziarski et al. (2002).
Milk with the highest fat content derived
from animals imported from the Netherlands (average 4.36%). Similar to Gnyp
(2012), the obtained results confirmed the
highest content of fat in heifer originated
from the Netherlands. However, the highest protein content was found in milk of
German cows (an average of 3.66%),
and the highest content of lactose in milk
of animals from France (an average of
4.95%). There was a significant influence
on the country of origin of heifers on dry
matter content in milk (Table 1). The dry
matter content was the highest in milk
of cows imported from France, and was
12.94% on average.
The average fat content of milk from
imported cows in the study was 4.09%.
Comparing it with the average fat content of Polish population of HO reported
by Polish Federation of Dairy Cattle
Breeder and Producer in 2013, it was
found that native cows have a higher fat
content in milk (4.16%) compared to the
Significance
of the effect
Average
value
9099
72
Netherlands
Poland
71
2112
Denmark
231
224
Czech
Republic
France
128
Austria
Germany
N
Specification
0.16
0.22
0.87
0.47
0.75
0.34
0.47
0.84
SE
P ≤ 0.01
21.72
19.88
18.29
27.03
25.49
24.06
24.09
23.61
LSM
Milk
(kg)
0.02
0.02
0.11
0.06
0.09
0.04
0.06
0.10
SE
P ≤ 0.01
4.09
4.15
4.36
3.92
4.18
3.96
3.95
4.13
LSM
Fat
(%)
0.01
0.01
0.06
0.03
0.05
0.02
0.03
0.05
SE
P ≤ 0.01
3.44
3.44
3.49
3.43
3.67
3.40
3.29
3.52
LSM
Protein
(%)
0.005
0.007
0.028
0.015
0.024
0.011
0.015
0.027
P ≤ 0.01
4.86
4.84
4.79
4.95
4.77
4.89
4.83
4.94
SE
Lactose
(%)
LSM
TABLE 1. The influence of country origin of primiparous cows on milk components
0.028
0.037
0.143
0.078
0.123
0.056
0.077
0.139
SE
P ≤ 0.05
13.09
13.12
13.30
12.94
13.40
12.94
12.77
13.31
LSM
Dry matter
(%)
71.36
112.54
51.09
70.24
74.18
SE
172.58
206.04
211.26
200.43
214.33
LSM
25.10
34.11
P ≤ 0.01
283.13
310.14
1.85
2.52
P ≤ 0.01
191.01
177.91
9.66
5.28
8.33
3.78
5.20
9.37
SE
Somatic cells
count (103/l)
654.37 130.522 195.92
116.79
373.08
237.57
315.83
126.58
LSM
Urea content
(mg/l)
imported ones. Similar observations was
made by Gnyp et al. (2001). Mentioned
above authors also confirmed higher
fat content (4.16%) in Polish HO cows
compared with cows imported from Germany (4.02%). Nevertheless, the papers
published by Dymnicki and Reklewski
(1999) and Czerniawska-Piątkowska
(2009) reviled different results. These
authors of these publications stated that
imported cows were characterized by
higher content of fat than cow native
ones (4 vs. 3.82%, respectively). Our
study reviled that, cows imported from
Austria, Germany, Denmark and the
Netherlands had an average fat content
of the milk in the range of 4.0–4.9% of
fat and cows from the Czech Republic
and France range of 3.0–3.9% of fat. It
is worth mentioning, that German cows
characterized by the highest maximum
level of fat in milk at range of 5.0–5.9%
all analyzed cows. The studies presented
by Dymnicki and Reklewski (1999) and
Czerniakowska-Piątkowska (2009) indicated a similar to our study percentage of
fat in milk of German cows. The results
of Czaplicka et al. (2013) observed comparable to those obtained in the study
percentage fat content in milk of cows
imported from France (4.28%).
The average concentration of protein
in milk in our study was 3.44%. Other
authors (Dymnicki and Reklewski 1999,
Czaplicka et al. 2013) observed a similar
protein content in milk of cows imported
from France and Germany, the Polish
HO cows and the same age in (3.38,
3.19%, respectively). However, different results were obtained by Czerniawska-Piątkowska (2009) in her research
on comparison of production traits of
Holstein-Friesian cows imported from
9
Germany and their Polish contemporaries. Mentioned author observed a higher
protein content in milk of Polish cows
(3.34%) compared to imported ones
(3.37%). Dymnicki and Reklewski
(1999) and Czaplicka et al. (2013) found
that cows imported from France and Germany, produced similar to observed in
the study, concentration of milk protein.
In studies of Cichołowicz et al. (2010)
Holstein-Friesian cows imported from
Germany were superior for protein content (3.37%) if compared to cows originated from Sweden (3.28% protein).
Our study also reviled that the country of cow origin, had significant effect
(p ≤ 0.01) on the content of urea and
somatic cells in milk (Table 1). The
highest average content of urea in milk
characterized by animals from the Netherlands (654.37 mg/l) and the lowest, the
heifers imported from France (116.79
mg/l). Animals carrived from Austria
were characterized by the highest average
milk somatic cell count, which amounted
to 214.33 103/l, while the lowest average somatic cell count was observed in
animal from France – 172.58 103/l. In
studies of Czaplicka et al. (2013) found
that the heifers imported from France had
higher levels of SCC in milk (248 103/l)
than their contemporaries from Poland.
Table 2 presents the comparison of
the milk performance of imported and
native cows. There was no statistically
significant differences between those
two groups. However, it is worth noting,
that the imported animals clearly characterized by higher daily milk production
(23.89 kg) if compared to the Polish
contemporaries (19.88 kg). The chemical composition of milk in both groups is
similar. Nevertheless, imported animals
517
130
Norwegian
Red
Simmental
NS – non-significant.
Significance
of the effect
Average value
431
Red and
White
Holstein-Friesian
10786
73
Brown
Swiss
Black and
White
Holstein-Friesian
N
Specification
0.16
0.60
0.48
0.44
0.18
1.09
SE
P ≤ 0.01
21.72
18.02
20.41
21.25
23.77
24.48
LSM
Milk
(kg)
4.09
4.31
4.11
4.15
4.05
4.04
LSM
NS
Fat
(%)
0.02
0.07
0.06
0.05
0.02
0.13
SE
0.01
0.04
0.03
0.03
0.01
0.07
SE
P ≤ 0.01
3.44
3.51
3.50
3.38
3.43
3.57
LSM
Protein
(%)
TABLE 2. The influence of primiparous cows breed on milk components
Bread
0.01
0.02
0.01
0.01
0.01
0.03
SE
P ≤ 0.01
4.86
4.99
4.79
4.91
4.84
4.97
LSM
Lactose
(%)
0.02
0.10
0.07
0.07
0.03
0.17
SE
P ≤ 0.05
13.09
13.45
13.12
13.12
13.02
13.30
LSM
Dry matter
(%)
25.10
90.78
72.35
66.45
26.98
66.15
SE
P ≤ 0.01
283.13
112.91
233.34
188.63
338.44
163.39
LSM
Urea content
(mg/l)
1.85
6.72
5.35
4.92
1.99
12.10
SE
P ≤ 0.05
191.01
202.78
185.23
196.21
192.42
226.04
LSM
Somatic cells
count
(103/l)
NS
NS
13.09
4.86
3.44
0.02
3.44
0.02
0.03
3.44
NS
0.01
4.84
0.01
0.01
4.88
NS
0.01
13.12
0.01
13.04
0.01
LSM
SE
LSM
SE
LSM
SE
NS
4.09
NS – non-significant.
LSM
NS
0.16
21.72
4.15
0.22
19.88
4.03
0.24
LSM
SE
23.89
Imported
primiparous
2838
cows
Native
primiparous
9099
cows
Average value
Significance
of the effect
N
Specification
NS
1.85
191.01
25.10
283.13
0.02
2.52
177.91
34.11
310.14
0.03
2.74
206.53
37.08
251.13
0.04
SE
LSM
SE
Somatic cells
count
(103/l)
LSM
SE
Urea content
(mg/l)
Dry matter
(%)
Lactose
(%)
Protein
(%)
Fat
(%)
Milk
(kg)
TABLE 3. Milk performance of imported and native primiparous cows
11
were characterized by a slightly higher
level of somatic cells count. The average content of somatic cells in milk of
imported animals was 206.53 103/l and
native 177.91 103/l (Table 3).
Analyzing the results in Table 3 it
can be seen that the breed of cattle has
a highly significant effect (p ≤ 0.01)
on average daily milk yield. Among
the breeds studied, the highest daily
performance elements characterized by
Brown Swiss race that produced 24.48
kg of milk per day, whereas marked by
Simmental cows from which the daily
obtained averaged just over 18 kg.
Table 3 presents the effect of breed
on the of milk performance results. The
largest group of animals was represented
by Black and White variety of HolsteinFriesian (10,786 cows), while the smallest was the Brown Swiss breed (presented
by only 73 cows). The study also showed
a highly significant (p ≤ 0.01) the impact
of the breed of cattle on the protein and
lactose concentration in milk (Table 3).
The highest average protein content was
reported in Brown Swiss milk. The milk
obtained from Simmental and Norwegian
Red and Polish cows contained 3.57, 3.51
and 3.50% protein respectively. Simmentals’ milk, as indicated by Neja et al.
(2013), was characterized by the most
preferred ratio of protein to fat content.
According to Litwińczuk et al. (2006),
milk obtained from Simmentals had the
high content of the casein fraction, and had
the most preferable technological value.
The highest average lactose content was observed in Simmental milk
(4.99%). Slightly lower, but also a high
content of lactose was noticed in milk of
Brown Swiss and Holstein-Friesian of
Black and White variety.
12
M. Balcerak et al.
In our study, there was no significant
differences between the breeds in the
milk fat content.
Analyzing Table 3, can also be
observed that the breed of animals had
a significant influence on the dry matter
content in the milk. The highest content
of dry matter was observed in milk of
Simmentals with the average of 13.45%.
Study also reviled significant impact of
cattle breed on the amount of urea in milk
(p ≤ 0.01). The highest content of urea in
milk was stated in milk of Black and White
variety of Holstein-Friesian cows. Animals
of this breed characterized by an average content of milk urea at 338.44 mg/l.
There was significant effect of cow
breed on the somatic cell count in milk.
The lowest recorded number of somatic
cells was observed in Norwegian Red
milk, which contained on average only
185.23 103/l. However, the least favorable in terms of SCC were Brown Swiss
cows (Table 3).
CONCLUSIONS
Obtained results reviled that, the country
of cow origin had significant impact on
daily milk yield, percentage of fat, percentage of protein, percentage of lactose
and also on the dry matter content, urea
and somatic cells in the milk of lactating
cows.
Compeering the results of milk performance between native and imported
cows there were no statistically significant
differences between the two groups.
The breed of cows had strong influence
on daily milk production, percentage of
protein, lactose, dry matter, and also the
content of urea and somatic cell count in
milk.
REFERENCES
ANTKOWIAK I., KLIKS R., 1998: Długość
użytkowania i wydajność życiowa kilku genotypów krów w Wielkopolsce. Rocz. Akad. Rol.
w Poznaniu CCCII: 3–7.
BARAŃSKI W., JANOWSKI T., RAŚ M.,
ZDUŃCZYK S., OPSPMER G., DEWULF J.,
De KRUIF A., 2008: Zaburzenia rozrodu
i wybrane wskaźniki płodności w stadach
krów mlecznych objętych programem opieki
lekarsko-weterynaryjnej. Med. Wet. 64 (6):
807–811.
BARŁOWSKA J., LITWIŃCZUK Z., WOLANCIUK A., PASTUSZKA R., 2014: Skład
chemiczny, jakość cytologiczna i przydatność technologiczna mleka krów trzech ras
o umaszczeniu czerwono-białym żywionych
systemem TMR. Rocz. Nauk. PTZ 10 (4):
115–124.
BOGUCKI M., SAWA A., NEJA W., BEMBNISTA M., 2009: Użytkowość mleczna krów rasy
holsztyńsko-fryzyjskiej pochodzenia krajowego i zagranicznego. Rocz. Nauk. PTZ 5 (4):
21–31.
CHOROSZY B., 1997: Produkcja mleka i mięsa
wysokiej jakości. In: Chów bydła – cechy użytkowe, żywienie i ekonomika produkcji. Fundacja programów Pomocy dla Rolnictwa, Instytut
Zootechniki, Kraków: 106–107.
CICHOŁOWICZ E., CZERNIAWSKA-PIĄTKOWSKA E., SZEWCZUK M., 2010: Ocena
produkcyjności krów rasy holsztyńsko-fryzyjskiej importowanych ze Szwecji i Niemiec.
Acta Sci. Pol., Zootechnica 9 (3): 9–18.
CZAPLICKA M., CZERNIEWICZ M., PUCHAJDA Z., KRUK A., SZALUNAS T., 2002:
Ocena ilości i jakości mleka krów holsztyńsko-fryzyjskich i czarno-białych. Zesz. Nauk. Prz.
Hod. 55: 183–192.
CZAPLICKA M., SZALUNAS T., PUCHAJDA
Z., 2013: Porównanie użytkowości mlecznej
krów holsztyńsko-fryzyjskich importowanych
z Francji i ich krajowych rówieśnic. Rocz.
Nauk. PTZ 9 (1): 9–15.
CZAPLICKA M., CZERNIEWICZ M., PUCHAJDA Z., KIEŁCZEWSKA K., KRUK A., SZALUNAS T., 2003: Comparison of physical and
chemical properties and technological value of
milk local population of BW cows. Pol. J. Food
Nutr. Sci. 12/53, 3: 63–66.
CZERNIAWSKA-PIĄTKOWSKA E., SZEWCZUK M., SOWA A., ZYCHLINSKA-BUCZEK J., 2009: Porównanie poziomu cech
produkcyjnych krów rasy hf importowanych
z Niemiec z rówieśnicami krajowymi. Acta
Sci. Pol., Zootechnica 8 (3): 3–10.
CZUBSKA A., WÓJCIK P., KRUK M., 2009: Selekcja krów pod kątem długowieczności jako
czynnik poprawy rentowności gospodarstwa
rodzinnego. Prace i Mat. Zoot. 67: 45–55.
DORYNEK Z., KLIKS R., 1998: Wpływ wybranych czynników na kształtowanie się liczby
komórek somatycznych w mleku krów. Rocz.
AR w Poznaniu, CCCII, Zootech. 50: 91–95.
DYMNICKI E., REKLEWSKI Z., 1999: Użytkowość mleczna córek buhajów z niektórych
krajów europejskich i krów importowanych
z Niemiec i Holandii. Zesz. Nauk. Prz. Hod.
44: 101–108.
GNYP J., 2012: Wpływ kraju pochodzenia na
produkcyjność krów i relacje pomiędzy zawartością tłuszczu i białka w mleku. Rocz. Nauk.
PTZ 8 (4): 19–26.
GNYP J., KAMIENIECKI K., KOWALSKI P.,
MAŁYSKA T., 2001: Wydajność i skład mleka krów holszyńsko-fryzyjskich krajowych
i importowanych, utrzymywanych w gospodarstwach indywidualnych województwa lubelskiego. Zesz. Nauk. Prz. Hod. 59: 129–138.
GNYP J., KOWALSKI P., TIETZE M., 2006:
Wpływ genotypu oraz kraju pochodzenia krów
na ich wydajność dobową mleka, jego skład
i jakość cytologiczną. Ann. Univ. Mariae Curie-Skłodowska 24: 1–8.
KUCZAJ M., 2004: Analiza wartości użytkowej krów rasy czarno-białej importowanych
z Holandii i ich rówieśnic ras czarno- i czerwono-białej odchowanych w kraju. Med. Wet. 60
(12): 1317–1319.
LITWIŃCZUK A., PIERÓG M., KRÓL J., 2000:
Wpływ sezonu na jakość mleka towarowego
produkowanego w regionie lubelskim. Rocz.
Nauk. Zoot., Supl. 6: 77–81.
LITWIŃCZUK Z., TETER U., TETER W., STANEK P., CHABUZ W., 2006: Ocena wpływu
niektórych czynników na wydajność i jakość
mleka krów utrzymywanych w gospodarstwach
farmerskich. Rocz. Nauk. PTZ 2 (1): 133–140.
MALCHIODI F., CECCHINATO A., PENASA
M., CIPOLAT-GOTET C., BITTANTE G.,
2014: Milk quality, coagulation properties, and
13
curd firmness modeling of purebred Holsteins
and first- and second-generation crossbred cows
from Swedish Red, Montbéliarde, and Brown
Swiss bulls. J. Dairy Sci. 97: 4530–4541
MATRAS J., KLEBANIUK R., BUJANOWICZ B., WOJTASIK J., 2000: Zawartość
białka i tłuszczu oraz jakość mleka krów
w zależności od modelu żywienia w gospodarstwach specjalistycznych środkowo-wschodniej Polski. Rocz. Nauk Zoot., Supl. 6: 82–87.
NAŁĘCZ-TARWACKA T., GRODZKI H., PRZYSUCHA T., ZDZIARSKI K., 2002: Wpływ rui
na wydajność, skład chemiczny i przydatność
technologiczną mleka krów. Zesz. Nauk. Prz.
Hod. 62: 161–167.
NEJA W., JANKOWSKA M., SAWA A., BOGUCKI M., 2013: Analiza użytkowości mlecznej
i rozpłodowej krów krajowej populacji aktywnej. J. Cent. Euro. Agri. 14 (1): 91–101.
PUCHAJDA Z., CZAPLICKA M., SZALUNAS
T., 2003: Wydajność i skład mleka krów holsztyńsko-fryzyjskich importowanych z Francji
i ich rówieśnic krajowej rasy czarno-białej.
Rocz. Nauk. Zoot. 17 (2): 885–888.
SABLIK P., KAMIENIECKI H., GRZESIAK
W., 2001: Porównanie poziomu cech produkcyjnych i niektórych wskaźników rozrodczych
krów holsztyńsko-fryzyjskich importowanych
jako jałowice cielne z Francji z wynikami uzyskanymi od krów miejscowych. Zesz. Nauk.
PTZ 59: 239–246.
SAWA A., BOGUCKI M., CIEŚLAK M., 2000:
Wpływ wybranych czynników pozagenetycznych na związek między liczbą komórek somatycznych a cechami mleczności krów. Rocz.
Nauk Zoot., Supl. 6: 112–117.
SENDER G., GŁABÓWNA M., BASSALIK-CHABIELSKA I., 1987: Środowiskowe uwarunkowania liczby komórek somatycznych
w mleku krów. Zesz. Probl. Post. Nauk. Rol.
332: 67–74.
SKRZYPEK R., SZUKALSKI L., 2006: Użytkowość krów rasy czarno-bialej importowanych
z Holandii i Niemiec oraz krów wyhodowanych w Polsce. Med. Wet. 62 (02): 197–200,
ZDZIARSKI K., GRODZKI H, NAŁĘCZ-TARWACKA T., BRZOZOWSKI P., PRZYSUCHA
T., 2002: Wpływ systemu utrzymania i genotypu krów na długość ich użytkowania i życiową
użytkowość mleczną. Zesz. Nauk. Przeg. Hod.
62: 29–35.
14
M. Balcerak et al.
Streszczenie: Wpływ rasy i pochodzenia pierwiastek na wyniki ich użytkowości mlecznej. Celem
badań było porównanie parametrów użytkowości
mlecznej i składu mleka pierwiastek pochodzących z sześciu krajów europejskich z rówieśnicami utrzymywanymi w Polsce oraz wykazanie
różnic między rasami. Materiał do badań stanowiły dane zawarte w raportach wynikowych
z 26 gospodarstw. Analizowano takie dane, jak:
wydajność mleka oraz zawartości tłuszczu, białka, laktozy, suchej masy, komórek somatycznych
i mocznika w mleku. Na podstawie uzyskanych
wyników stwierdzono, że kraj pochodzenia pierwiastek okazał się istotnym czynnikiem wpływającym na dobową wydajność mleka, procentową
zawartość tłuszczu, procentową zawartość białka,
procentową zawartość laktozy. Wpływ ten wykazano również na zawartość: suchej masy, mocznika i komórek somatycznych w mleku. Analizując
wyniki użytkowości mlecznej pierwiastek importowanych z krajowymi, nie wykazano statystycznie istotnych różnic między obiema grupami. Rasa
krów miała wpływ na dobową produkcję mleka,
procentowe zawartości białka, laktozy i suchej
masy, a także na zawartości mocznika oraz komórek somatycznych w uzyskiwanym surowcu.
MS. received May 2015
Authors’ address:
Marek Balcerak
Katedra Szczegółowej Hodowli Zwierząt
Wydział Nauk o Zwierzętach SGGW
02-786 Warszawa, ul. Ciszewskiego 8
Poland
Changes in cow’s milk composition and physical properties during
the uninterrupted milking process
EDWARD DYMNICKI1, MARCIN GOŁĘBIEWSKI2, AGATA WÓJCIK2,
KAMILA PUPPEL2, BEATA KUCZYŃSKA2, EWA SOSIN-BZDUCHA4,
TADEUSZ SZULC3
Department of Animal Science, Institute of Genetics and Animal Breeding, Polish Academy of Science
Department of Cattle Breeding, Warsaw University of Life Sciences – SGGW
3
Department of Cattle Breeding and Milk Production, Wroclaw University of Environmental and Life
Sciences
4
Departament of Animal Genetic Resources Conservation, National Research Institute of Animal
Production
1
2
Abstract: Changes in cow’s milk composition
and physical properties during the uninterrupted milking process. The chemical composition of milk determines the nutritional value
and technological properties of milk and dairy
products. Many studies have been performed
on the chemical composition of milk, including
fatty acid and protein profile, however a limited
number of investigations have determined the
changes in chemical composition of the milk
during the milking process. Experiment were
designed to study changes in milk chemical
composition (i.e. fat, protein, casein, lactose,
urea, citric acid, total solids – TS, solids-non-fat
– SNF, free fatty acids – FFA, as well as acidity,
density, freezing point and somatic cell score)
during the uninterrupted milking. Fifty two
cows (455 samples) of three different breeds;
with daily production 5–12 kg; were sampled
during interrupted milking process. Representative sample were collected from each kg of
milked liquid. There were significant (P ≤ 0.01)
changes in fat, FFA, lactose, TS and density of
milk during milking. The concentration of fat,
FFA, and TS shown increasing tendency with
the course of milking, however, lactose and
density presented opposite trends. Therefore,
obtaining the whole quantity of milk from udder during the milking process, beside shaping
the health status, is an indispensable step to produce milk of the highest quality in terms of its
nutritional and technological value.
Key words: milking process, milk composition,
cow’s milk, fat
INTRODUCTION
Raw milk and dairy products are very
important components of human diet in
many part of the world. The chemical
composition of raw milk determines
the nutritional value and technological
properties of milk and dairy products.
Therefore, the chemical milk composition is of great importance for dairy
industry and there is a great need for
changing the composition of raw milk.
Numerous studies have been carried out
to investigate the influence of different
factors on cow’s milk chemical composition (Glantz et al. 2009, Kuczyńska,
2011, Sakowski et al. 2012). The milk
chemical composition strongly depends
upon the season (Lindmark-Månsson et
16
E. Dymnicki et al.
al. 2003, Lock and Garnsworthy 2003,
Nałęcz-Tarwacka and Grodzki 2005),
stage of lactation (Kuchtík et al. 2008,
Puppel et al. 2012), feeding (Friggens et
al. 2007, Kuczyńska et al. 2012), health
status (Wielgosz-Groth and Groth 2003,
Batavani et al. 2007) of the cow as well
as and genetic factors (Fox and McSweeney 1998, Stoop et al. 2008a, Stoop
et al. 2008b). Each milk compound can
be affected by the same factors. When
determining raw milk composition it is
also important to realize the interaction
between the feeding systems, management practices and breed (Heck et al.
2009).
Over the last years, many studies
have been performed on the chemical
composition of milk, including fatty
acid and protein profile (Wedholm et al.
2006, Soyeurt and Gengler 2008) as well
as its influence on human health (Roche
et al. 2001). However a limited number
of investigations have determined the
changes in chemical composition of the
milk during the milking. Mostly, the fat
fraction of milk have been investigated
(Whittlestone 1953, Kernohan et al.
1971, Ontsouka et al. 2003), and other
milk compounds have been rarely analyzed (Dobicki et al. 1993, Lollivier et
al. 2002, Vangroenweghe et al. 2002).
Typically, changes in cow’s milk constituents during the milking have been
examined by analyzing certain fraction
(e.g. beginning, middle and end of the
milking) and not sampled during the
whole milking process (Nielsen et al.
2005). Probably, the reason for that
was the equipment limitation which not
allowed to sample milk (e.g. representative sample of each liter of milk) during
uninterrupted milking.
Therefore, the aim of the study was to
investigate changes in milk chemical composition during the uninterrupted milking.
Animals and treatment
Fifty two cows were used in the experiment of which 18 represented Polish Holstein-Friesian (PHF) breed; 17 to Polish
Red (PR) and 17 to Polish Black and
White (PBW) breed. The animals originated from two different farms: all PHF
cows belonged to Institute of Technology and Life Sciences located in Falenty
near Warsaw, PR and PBW belonged to
Research Station of Organic Farming and
Animal Breeding in Popielno. For the
experiment purposed the chosen cows
varied in terms of their productivity (5–12
kg of milk per milking). In both farms
cows were housed in a tie stall system
in accordance with standards of animal
welfare developed by Polish Ministry of
Agriculture and Rural Development. The
lactation number as well as lactation stage
differ within the group of studied cows;
2–4 lactation and 90–200 day in milk
(DIM), respectively. Cows were milked
twice a day. All cows were healthy and
had continuous access to water. The cows
were fed individually in accordance with
their requirements, stage of lactation and
physiological status. Feeding rations were
balanced according to the INRA system
(INRA 2009). The diet composition is
presented in Table 1.
The procedures involving animals
were approved by the Local Commission
for Animals Ethics concerning animal
experimentation and care of experimental animals.
Changes in cow’s milk composition and physical properties during the uninterrupted...
17
TABLE 1. Diet and chemical composition of the cow’ diet
Treatmenta
Item
PHF cows
24.0
3.50
–
–
0.7
0.1
0.14
Maize corn silage
Corn silage
Grass silage
Hay
Soybean meal (46% C.P.)
Pasture ground chalk
Premixa
Salt
Rapeseed meal
Ground triticale
Magnesium oxide
Dry matter (% of DM)
Ash (% of DM)
Crude protein (% of DM)
Acid detergent fiber (% of DM)
Neutral detergent fiber (% of DM)
Calcium (% of DM)
Phosphorus (% of DM)
Crude fiber (% of DM)
UFL (% of DM · kg of DM–1)
0.05
2.0
–
0.05
Chemical composition
57.5
4.2
7.5
27.9
33.7
0.9
0.5
4.36
1.10
PR and PBW cows
–
–
30
6
–
0.1
0.05
0.02
–
1.5
–
67.2
6.45
5.75
33.7
41.6
0.7
0.6
4.56
1.16
a
Contained (on 1000 g): Ca – 150 g, P – 100 g, Na – 50 g, Mg – 40 g, Zn – 9000 mg, Mn – 7000 mg, Cu – 1000 mg,
J – 100 mg, Se – 50 mg, vitamin A – 1,200,000 IU, vitamin D3 – 120,000 IU, vitamin E – 5 000 mg, vitamin K
– 93 mg, vitamin B1 – 80 mg, vitamin B6 – 160 mg, vitamin B2 – 110 mg, vitamin B12 – 1000 μg.
C.P. – crude protein.
Sampling
Milk samples were collected between
April and June of 2012 once from each of
studied cow. All samples were collected
from evening milking. Before collecting
standard procedures of cow and udder
preparing were maintained. The teats were
cleaned with the cloth and the first squirt
of milk was discarded. Before attaching
milking tubes to udder milking cluster was
connected to De Laval (Milkocsope MK
II-KG-Scale) milk sampler. During the
interrupted milking representative sample
(50 ml) of milk from each kg of milked
liquid was pooled out. As the milk yield of
studied cows varied from 5 to 22 kg five to
twenty samples were collected from each
cow. The milk samples were placed in the
sterile bottles containing milk preserver
– Microtabs II (Bentley). Immediately
after milking, samples were delivered to
the laboratory of Institute of Genetics and
Animal Breeding for chemical examination. Totally, 455 samples were collected.
18
E. Dymnicki et al.
Chemical analysis
The concentration of standard chemical
compounds of the milk, i.e. fat, protein,
casein, lactose, urea, citric acid, total
solids (TS), solids-non-fat (SNF), free
fatty acids (FFA), as well as acidity, density, freezing point and somatic cell score
were determined by automated infrared
analysis with a Milkoscan 6000 instrument (FossElectric). MilkoScan employs
the FTIR measuring principle, in compliance with IDF and AOAC standards.
Evaluation of somatic cell count
(SCC) of the milk was proceeded on
Fossomatic 5000 (Bentley). Than SCC
was transformed to somatic cell score
(SCS) by natural logarithm.
Statistic analysis
The data were performed to multi-factor
analysis of variance (least square means)
by IBM SPSS Statistics 19.0 software.
The level of significance was set at
P ≤ 0.05 or P ≤ 0.01. The model used to
analyze influence of collecting number
and milk yield on milk compounds was
as follows:
Yijk = μ + Ai + Bj + (Ai × Bj) + eijk
where:
Yijk
μ
Ai
– dependent variable;
– general mean;
– effect of collecting (i = 1
– collected from 1st kg of
milk, …, 12th and beyond
12th kg of milk);
Bj
– effect of yield (1–5 kg milking yield, …, 10 and beyond
14 kg milking yield);
(Ai × Bj) – fixed interaction effect between collecting and yield;
eijk
– random error.
To present the tendency in changes of
milk components the exponential tendency line has been drown.
Only chemical compounds of milk
which were significantly affected by collecting and milking yield were the subject of further investigation. No effect
of consequent sampling and milking
yield on protein, casein, urea, citric acid,
freezing point, acidity and somatic cell
score was observed.
RESULTS AND DISCUSSION
The average production and milk composition of the cows is presented in Table 2.
The fat concentration in raw milk of
cows tend to change during the milking
process (Fig. 1). The lowest level of fat
was observed in milk at the beginning of
milking, however the lowest value was
noted in second collecting (from the 2nd
kg of milk). The difference between the
lowest and the highest level of milk fat
was over 30 g·kg–1. The average increasing rate of raw milk fat fluctuated at
23 g·kg–1 per collecting. Whittlestone
(1953), noted that fat content in fore
milk was much lower than obtain in our
study and was established at 16 g·kg–1
and in stripping milk was 89 g·kg–1. The
author suggested that the trends towards
increasing fat content during milking
may be explained by the clustering of the
fat globules as the consequence of the
partial filtration of the globule clusters
as the milk flows from the glands.
There was significant (P ≤ 0.01)
influence of the milk production on fat
concentration in raw milk (Fig. 2), however the tendency was unclear. It is well
known that there is the negative correlation between the fat concentration and
19
TABLE 2. The mean values for analyzed traits
Trait
Milk (kg)
Fat (g·kg–1)
Protein (g·kg–1)
Casein (g·kg–1)
Lactose (g·kg–1)
Total solids, TS (g·kg–1)
Solids-non-fat, SNF (g·kg–1)
Urea (mg·1–1)
Citric acid (g·kg–1)
Freezing point (m°C)
Fry fatty acids (mmol·100 g–1)
Density (g·cm–3)
Acidity (°SH)
Somatic cell score (ln SCC·10–3)
N
455
438
438
284
438
438
284
438
284
284
284
284
284
154
Mean
10.19
41.2
32.0
23.5
47.9
128.7
89.3
217.97
1.91
584.35
0.93
1.026
19.95
4.97
SD
4.21
15.9
4.7
2.9
2.8
16.2
4.0
73.12
0.49
20.70
0.79
0.002
5.02
1.15
Min
5.00
5.0
22.5
13.1
3.5
91.7
76.3
63.00
0.01
545.00
0.01
1.017
12.00
2.40
Max
22.00
113.9
43.6
31.3
53.9
189.6
98.9
478.00
2.90
702.00
4.91
1.034
38.00
8.65
60
55
50
fat [g⋅kg−1]
45
40
fat
trend line
35
30
25
20
1
2
3
4
5
6
7
8
9
10
11
12
collecng
FIGURE 1. Changes in fat concentration during milking
milk production (Gaydarska et al. 2001),
however some authors have found
opposite relation (Chaunan and Hayes
1991). The highest level of milk fat was
observed in milk of cows producing
7 kg of milk a milking and the lowest in
milk of high yielding cows (above 14 kg
of milk per milking). The difference
between the highest and the lowest level
was over 10 g·kg–1.
20
E. Dymnicki et al.
48
46
44
fat [g⋅kg−1]
42
40
fat
trend line
38
36
34
32
5
6
7
8
9
10
11
12
13
>14
milk [kg]
FIGURE 2. Influence of the milking yield on fat concentration in cow’s milk
Whittlestone (1953), confirmed that
the rise in fat percentage is the greatest in
cows producing a large amount of milk,
or milking with long intervals. Moreover,
he stated that the increase in fat content
results mainly from the increased number
of milk fat globules. Results obtained
by Dobicki et al. (1993), shown that fat
content was 2.88 and 5.79% at the milk
yield of 6 kg and 1.92 and 6.71% at the
milk yield 12 kg (in the single milking – the first and the last liter of milk,
respectively). According to Lollivier
et al. (2002), the concentration of milk
fat increases with the course of milking;
milk removed at the beginning of a milking, corresponding to the cisternal milk,
is less rich in milk fat than milk removed
at the end of milking, corresponding to
the alveolar milk. The explanation of the
phenomenon revealed Guinard-Flament
et al. (2001), who stated, that milk fat
globules are transferred from the alveoli
to the cistern during machine milking as
a result of oxytocin-mediated milk ejection.
An interesting results reported Froberg
et al. (2007) who observed low fat content in milk of suckler cows after isolation or weaning of their calves. Dymnicki
and Sosin-Bzducha (2012), reported that
milk of PR cows milked mechanically
after 12 hours of their calves isolation
characterized by a very low fat content
(0.55–0.87%) depending on the lactation
stage. Similar results obtained Combellas and Tesorero (2003), and Marin et al.
(2007).
Similar to fat concentration tendencies
of free fatty acids changes in milk during
milking were stated (Fig. 3). The increasing rate was equal to 0.04 mmol·100 g–1
of fat. However, the higher than in fat
content variation in the concentration of
FFA was observed. The pick of the FFA
concentration was reported at the 11th
collection and its lowest level at 2nd collecting (79% between extremes).
21
2.50
−1
free faƩy acids [mmol⋅100 g ]
2.00
1.50
free faƩy acids
1.00
trend line
0.50
0.00
1
2
3
4
5
6
7
8
9
10
11
12
collecƟng
FIGURE 3. Changes in free fatty acids concentration during milking
The level of lactose in milk of studied cows was strongly affected by collecting number (Fig. 4). The changes in
lactose concentration during milking can
be compared to shape of the standard
lactation curve and the tendency line
was opposite to that observed in fat. The
highest level of lactose was observed
in 2nd kg of milk (2nd collection) and
the lowest at 12th collection. Difference
50
49
−1
lactose [g⋅kg ]
49
48
48
lactose
trend line
47
47
46
46
1
2
3
4
5
6
7
8
9
collecƟng
FIGURE 4. Changes in lactose concentration during milking
10
11
12
22
E. Dymnicki et al.
Total solids concentration in milk
during milking was changed (P ≤ 0.01)
with following collection (Fig. 5). The
highest level was observed at 11th sample
and the lowest at the 2nd with the difference between ambivalent values equal to
29.8 g·kg–1. Clear increasing tendency
for TS content during milking was noted
(increasing rate – 0.2 g·kg–1).
The highest density was observed
at the beginning of milking and the its
lowest value at the end of the process
(Fig. 6). However, the difference between
the highest and the lowest values were
small and equal to 1.06 g·cm–3. The tendency of raw milk density changes were
similar to those observed in lactose concentration. Decreasing rate was equal to
0.21 g·cm–3 per collecting.
The results of the research shown
linear relationship between consequent
sample of milk and concentration of milk
components. Fat, free fatty acids, total
between extremes was fluctuated at 3.0
g·kg–1. With the course of milking lactose level in raw milk dropt with the rate
of 0.2 g·kg–1 per collecting.
The results of other authors differed
significantly. According to Dobicki et
al. (1993) and Bruckmaier et al. (2004)
there were no differences in percentage
of protein and lactose between the first
and the last squirts of milk during the
milking. However Vangroenweghe et
al. (2002) observed that the lactose and
protein content in raw milk was lower
in post-striping compared to fore milk.
Moreover, lactose concentration also
strongly depends upon the health status
of mammary gland and is synthesized
exclusively by udder epithelial cells. In
case of mastitis lactose partially leaks
into blood circulation through the damaged blood vessels and its concentration
in milk decreases (Bruckmaier et al.
2004).
150
145
−1
Total solids [g⋅kg ]
140
135
130
total solids
trend line
125
120
115
110
1
2
3
4
5
6
7
8
9
10
11
12
collecƟng
FIGURE 5. Changes in dry matter total solids concentration during milking
23
0.001
0.001
−3
density [g⋅cm ]
0.001
0.001
density
0.001
trend line
0.001
0.001
0.001
1
2
3
4
5
6
7
8
9
10
11
12
collecƟng
FIGURE 6. Changes in milk density during milking
solids contents were increasing, lactose
decreasing and protein content shown
no changes. From physical properties of
milk only density was changing during
milking process. Therefore, obtaining
the whole quantity of milk from udder
during the milking process, beside shaping the health status, is an indispensable
step to produce milk of the highest quality in terms of its nutritional and technological value.
REFERENCES
BATAVANI R.A., ASRI S., NAEBZADEH H.,
2007: The effect of subclinical mastitis on milk
composition in dairy cows. Iranian J. Vet. Res.
8: 205–2011.
BRUCKMAIER R.M., ONTSOUKA C.E.,
BLUM J.W., 2004: Fractionized milk composition in dairy cows with subclinical mastitis.
Vet. Medicine – Czech 49: 283–290.
CHAUNAN V.P.S., HAYES J.F., 1991: Genetic
Parameters for First Lactation Production and
Composition Traits for Holsteins Using Mul-
tivariate Restricted Maximum Likelihood.
J. Dairy Sci. 74 (2): 603–610.
COMBELLAS J., TESORERO M., 2003: Cow
– calf relationship during milking and its effect
on milk yield and calf live weight gain. Livestock Res. Rural Development 15 (3): 1–10.
DOBICKI A., ASUQUO I.B., ADAMSKI M.,
1993: Zmienność składu mleka krów w kolejnych porcjach udojonego mleka. Przegląd Hodowlany 4: 11–14.
DYMNICKI E., SOSIN-BZDUCHA E., 2012:
Effects of calves separation and injection of
oxytocin on milk composition of the Polish
Red cows. Proceedings of the LXXVII Zjazd
Naukowy Polskiego Towarzystwa Zootechnicznego, September 10–12, Wroclaw. Book of
Abstracts: 32.
FOX P.F., McSWEENEY P.L.H., 1998: Dairy
Chemistry and Biochemistry. Blackie Academic and Professional, London.
FRIGGENS N.C., RIDDER C., LØVENDAHL
P., 2007: On the Use of Milk Composition
Measures to Predict the Energy Balance of
Dairy Cows. J. Dairy Sci. 90: 5453–5467.
GAYDARSKA V., KRUSTEV K., SIMEONOVA
S., IVANOV M., 2001: Influence of environmental and genetic factors on the milk yield
and phenotypic and genotypic parameters of
24
E. Dymnicki et al.
milk production in Black-and-White dairy
cows in Bulgaria. Biotechnology in Animal
Husbandry 17: 11–15.
GLANTZ M., LINDMARK M., STÅLHAMMAR
H., BÅRSTRÖM L., FRÖJELIN M., KNUTSSON A., TELUK C., PAULSSON M., 2009:
Effects of animal selection on milk composition
and processability. J. Dairy Sci. 92: 4589–4603.
GUINARD-FLAMENT J., MICHALSKI M.C.,
RULQUIN H., 2001: Evolution of milk fat
content and fat globule diameter according to
milking time in dairy cows. Renc. Res. Rum
Paris, France.
HECK J.M.L., Van VALENBERG H.J.F., DIJKSTRA J., Van HOOIJDONK A.C.M., 2009:
Seasonal variation in the Dutch bovine raw milk
composition. J. Dairy Sci. 92: 4745–4755.
KERNOHAN E.A., WADSWORTH J.C., LASCELLESA A.K., 1971: Changes in the composition of bovine milk fat during milking. J.
Dairy Res. 38: 65–68.
KUCHTÍK J., ŠUSTOVÁ K., URBAN T., ZAPLETAL D., 2008: Effect of the stage of lactation on milk composition, its properties and
the quality of rennet curdling in East Friesian
ewes. Czech J. Animal Sci. 53: 55–63.
KUCZYŃSKA B., 2011: Bioactive components
and technological parameters of milk produced
at ecological and conventional farms. Warsaw
University of Life Sciences Press, Warsaw.
KUCZYŃSKA B., PUPPEL K., GOŁĘBIEWSKI
M., KORDYASZ M., GRODZKI H., BRZOZOWSKI P., 2012: Comparison of fat and
protein fractions of milk constituents in Montbeliarde and Polish Holstein-Friesian cows
from one farm in Poland. Acta Vet. Brno 81:
139–144.
LINDMARK-MÅNSSON H., FONDÉN R., PETTERSSON H.E., 2003: Composition of Swedish dairy milk. Inter. Dairy J. 13: 409–425.
LOCK A.L., GARNSWORTHY P.C., 2003: Seasonal variation in milk conjugated linoleic acid
and delta(9)-desaturase activity in dairy cows.
Liv. Production Sci. 79: 47–59.
LOLLIVIER V., GUINARD-FLAMENT J., OLLIVIER-BOUSQUET M., MARNET P., 2002:
Oxytocin and milk removal: Two important
sources of variation in milk production and milk
quality during and between milkings. Reproduction Nutrition Development 42: 173–186.
MARIN B., BERG C., HERNÁNDEZ C., GALINA C.S., LIDFORS L., SVENNERSTENSJAUNJA K., 2007: Effect of restricted suckling on milk yield, milk composition and udder
health in cows and behavior and weight gain
in calves, in dual-purpose cattle in the tropics.
Tropical Animal Health and Production 39:
71–81.
NAŁĘCZ-TARWACKA T., GRODZKI H., 2005:
Influence of early spring feeding on fatty acid
levels of cow’s milk. Polish J. Food Nutrition
Sci. 1: 67–70.
NIELSEN N.I., LARSEN T., BJERRING M., INGVARTSEN K.L., 2005: Quarter health, milking interval, and sampling time during milking
affect the concentration of milk constituents. J.
Dairy Sci. 88: 3186–3200.
ONTSOUKA C.E., BRUCKMAIER R.M.,
BLUM J.W., 2003: Fractionized milk composition during removal of colostrum and mature
milk. J. Dairy Sci. 86: 2005–2011.
PUPPEL K., NAŁĘCZ-TARWACKA T.,
KUCZYŃSKA B., GOŁĘBIEWSKI M.,
GRODZKI H., 2012: Influence of combined
supplementation of cow’s diet with linseed
and fish oil on thrombogenic and atherogenic
indicators of milk fat. Animal Sci. Papers and
Reports 30 (4): 317–328.
ROCHE H.M., NOONE E., NUGENT A., GIBNEY M.J., 2001: Conjugated linoleic acid:
A novel therapeutic nutrient? Nutrition Research Reviews 14: 173–187.
SAKOWSKI T., KUCZYŃSKA B., PUPPEL K.,
METERA E., SŁONIEWSKI K., BARSZCZEWSKI J., 2012: Relationships between physiological indicators in blood, and their yield, as
well as chemical composition of milk obtained
from organic dairy cows. J. Sci. Food Agric. 92
(14): 2905–2912.
SOYEURT H., GENGLER N., 2008: Genetic
variability of fatty acids in bovine milk. Biotechnology, Agronomy, Society and Environment 12: 203–210.
STOOP W.M., BOVENHUIS H., Van ARENDONK J.A.M., 2008a: Genetic parameters for
milk urea nitrogen in relation to milk production traits. J. Dairy Sci. 90: 1981–1986.
STOOP W.M., Van ARENDONK J.A.M., HECK
J.M.L., Van VALENBERG H.J.F., BOVENHUIS H., 2008b: Genetic parameters for ma-
jor milk fatty acids and milk production traits
of Dutch Holstein friesians. J. Dairy Sci. 91:
385–394.
VANGROENWEGHE F., DOSOGNE H., BURVENICH C., 2002: Composition and milk
cell characteristics in quarter milk fractions of
dairy cows with low cell count. Vet. Journal
164: 254–260.
WEDHOLM A., HALLÉN E., LARSEN L.B.,
LINDMARK MÅNSSON H., KARLSSON
A.H., ALLMERE T., 2006: Comparison of
milk protein composition in a Swedish and a
Danish dairy herd using reversed phase HPLC.
Acta Agric. Scandinavica, Sect A 56: 8–15.
WHITTLESTONE W.G., 1953: Variation in the
fat content of milk throught the milking process. J. Dairy Sci. 20: 146–153.
WIELGOSZ-GROTH Z., GROTH I., 2003: Effect of the udder health on the composition and
quality of quarter milk from black and white
cows. Electronic J. Polish Agric. University 6
(2): 2–5.
nym mleka (czyli tłuszcz, białko, kazeina, laktoza, mocznik, kwas cytrynowy, sucha masa – s.m.,
sucha masa beztłuszczowa – s.m.b., wolnych
kwasów tłuszczowych – FFA oraz kwasowość,
gęstość, punkt krzepnięcia i liczba komórek somatycznych) podczas nieprzerwanego doju. Badania przeprowadzono na 52 krowach (3 różnych
ras) o średniej dziennej produkcji mleka wynoszącej 5–12 kg. Ogółem pobrano 455 próbek mleka.
Reprezentatywne próbki pobierano z każdego kolejnego udojonego kilograma mleka. Stwierdzono
istotne (P ≤ 0,01) zmiany w zawartości tłuszczu,
FFA, laktozy, TS i gęstości mleka podczas dojenia. Koncentracja tłuszczu, FFA i TS wykazały
tendencję wzrostową w trakcie dojenia, jednak
laktoza i gęstość wykazały trend odwrotny. Pozyskanie całej ilości mleka z wymion podczas procesu dojenia, obok kształtowania stanu zdrowia,
jest więc niezbędnym krokiem w kierunku produkcji mleka najwyższej jakości pod względem
jego wartości odżywczej i technologicznej.
MS received May 2015
Streszczenie: Zmiany w składzie mleka krowiego
podczas nieprzerwanego doju. Skład chemiczny
mleka określa wartość odżywczą i właściwości
technologiczne mleka i produktów mlecznych.
Przeprowadzono wiele badań dotyczących składu
chemicznego mleka, profilu kwasów tłuszczowych i zawartości białek. Jednak istnieje mało
badań, które dotyczyłyby zmian w składzie chemicznym mleka w trakcie procesu dojenia. Celem
badań było określenie zmian w składzie chemicz-
25
Authors’ address:
Marcin Gołębiewski
Zakład Hodowli Bydła
02-786 Warszawa, ul. Ciszewskiego 8, Poland
Relation between the shape and course of lactation curve and
production traits of Polish Holstein-Friesian and Montbeliarde cows
MARCIN GOŁĘBIEWSKI, TOMASZ PIOTROWSKI, PIOTR BRZOZOWSKI,
HENRYK GRODZKI, TOMASZ PRZYSUCHA, JAN SLÓSARZ,
MAŁGORZATA KUNOWSKA-SLÓSARZ, TERESA NAŁĘCZ-TARWACKA,
AGATA WÓJCIK
Abstract: Relation between the shape and course
of lactation curve and production traits of Polish
Holstein-Friesian and Montbeliarde cows. The
aim of the study was to examine the relation between shape and course of lactation curve and
production traits of Polish Holstein-Friesian
(PHF) and Montbeliarde (MO) cows kept under
various production systems. The production parameters were based on cows records developed
by Polish Federation of Cattle Breeders and Producers and involved 1374 lactations. For estimation of lactation curve parameters Wood’s model
was applied. The influence of breed, lactation
number and type of the farm on Wood’s parameters were analyzed. The relations between shape
and curse of the lactation curve on daily production and milk chemical composition were investigated. Analysis revealed that standard shape of
the lactation curve was the most often observed,
the significantly higher frequency was observed
in MO than PHF cows. Cows with standard lactation curve characterized by the highest production and the best milk quality. The significant
influence of breed, lactation number and farm
type on Wood’s parameters were stated. Cow
with less dynamic changes in milk production
during lactation characterized by significantly
better production parameters.
Key words: lactation persistency, lactation curve
shape, production traits, dairy cow, Montbeliarde
breed, Polish Holstein-Friesian breed
INTRODUCTION
The lactation persistence of dairy cows,
measured by the level and rate of daily
milk production decreasing after the
peak of lactation, plays a important
role in economics of milk production
(Togashi and Lin 2009). The slower milk
decline during the lactation the beneficial economic effect. The difficulties of
comparing the lactation persistence of
cows in various studies are mainly due
to different ways of defining this parameter (Gengler 1996, Swalve and Gengler
1999). The lactation persistence can be
presented in three ways: as a uniform rate
of lactation (Gengler and Misztal 1996),
on the basis of milk records (Gengler and
Misztal 1996, Grossman et al. 1999) and
by setting the parameters of mathematical models of lactation curves (Rowlands
et al. 1982, Goodal and Sprevak 1984,
Leon-Velarde et al. 1995). According
to Grossman et al. (1999), the first two
ways of defining the lactation persistence are vague, hence the great interest
of researchers in finding mathematical
model describing lactation curve that
precisely describe the distribution of
28
M. Gołębiewski et al.
the daily milk records of lactating cows.
Mostly, for these purposes, in scientific
literature gamma function of lactation
curves developed by Wood was applied
(1967, 1976).
Cows with flat lactation curve characterized by higher feed efficiency, better
withstand high milk production at the
peak of lactation (Muir et al. 2004, Weller
et al. 2006), are more resistant to diseases
(Jakobsen et al. 2002, Harder et al. 2006),
characterized by better fertility (Bar-Anan
and Ron 1985, De Vries 2006), thus tend
to generate higher revenue (Dekkers et
al. 1998). Despite the great importance
of lactation perseverance, this feature is
often not taken into account in the merit
indexes. The reason for this may be the
lack of adequate data to estimate its economic weight and the difficulty in assessing the influence of the effect of lactation
persistence on other functional traits.
Recently, with the growing interest in
methods that use data on test day records,
the more popular have become the procedures for lactation persistence (lactation
curve) assessment in animal breeding
programs (Schaeffer and Dekkers 1994,
Jamrozik et al. 1997).
The aim of this study was to determine
the relationship between the shape and
course of the lactation curve and the and
production traits of Polish Holstein-Friesian and Montbeliarde cows kept under
various production systems.
The material consisted cows of Polish
Holstein-Friesian of Black and White
variety (PHF) and Montbeliarde (MO)
from six dairy farms located different regions of Poland. All farms were divided
into two groups with regard to herd size,
production system and the intensity of
production. Data were recorded by the
Polish Association of Cattle Breeders and
Milk Producers (PFHBiPM), and each
of the stocks covered by the milk performance was controlled by AT4. Herds
differed size and intensity of production,
and all of them were two races held at
the same time (the exception was only
one herd of cows term montbeliarde). In
total, the study analyzed 1374 lactations
(967 PHF and 407 MO).
For statistical analysis, the data from
the daily performance reports, consisted:
1. Basic identification data of each studied cow, i.e.: tag number, breed, herd
number, birth data and culling data;
2. Performance information of studied cows, i.e.: milk production, fat,
protein, lactose, urea and dry matter
concentration, somatic cell count. In
addition to standard production traits,
the FCM (fat corrected milk) and
ECM (energy corrected milk) were
calculated according to the formulas:
FCM = 0.4 M × 15 F
ECM = 0.25 × M + 12.2 × F + 7.7 × P
where:
M – milk (kg);
F – fat (kg);
P – protein (kg).
3. Analysis of lactation curve shape was
based on Wood’s model parameters:
Yn = anbe–cn
where:
Yn – average daily yield in the n-th
week;
Relation between the shape and course of lactation curve and production traits...
a
b
c
n
– parameter describing general
production ability related to peak
lactation;
– parameter related to the ascending
part of the curve between calving
and peak of lactation;
– parameter related to the descending part of the curve following
lactation peak;
– week of the lactation (Wood 1967).
Wood function parameters were
calculated according to Gauss-Newton method (Hartley 1961).
Since a non-linear form of regression
does not guarantee convergence, Wood’s
function was transformed to its logarithm
form: ln Yn = ln (a) + b ln (n) – cn.
Wood’s model can fit analyzed traits
curves in four different shapes (Wood
1976, Macciotta et al. 2005), mainly
depending on the value of parameters
b and c, as a is always positive and
influences average level of production
(Table 1). Type C1 represents the shape
of the typical curve of daily milk yield
while C2 and C3 correspond to continuously increasing and decreasing curves,
respectively. The type C4 refers to the
TABLE 1. Possible curve shapes of Wood’s model
(Gołębiewski 2010)
Curve
shape
Parameters of
Wood’s model
b
c
C1
b>0
c<0
C2
b>0
c>0
C3
b<0
c<0
C4
b<0
c>0
Curve description
standard lactation
curve
continuously
ascending curve
continuously
descending curve
inverted to standard
curve
29
shape of reversed standard curve, with
a descending initial phase and ascending phase after reaching the minimum
(Gołębiewski 2010).
Goodness of fit was estimated by
the adjusted determination coefficient
(R2) (Olori et al. 1999, Macciotta et al.
2005).
Scripts were written in Visual Basic
using Solver in MS Excel and run in
order to calculate parameters of Wood’s
model.
For the statistical analysis PAWS Statistics 19 (2010), software package was
applied. To compare the distribution of
lactation curves types of the of cows of
both breeds Chi2 test was used.
The analysis of variation (ANOVA)
of SPSS software package was used
to evaluate breed (MO and PHF), production intensity (1 – intensive and 2
– less intensive), lactation number (first,
second, third, fourth and more) on coefficients of Wood’s model according to
model 1, which is:
Y = μ + Ai + Bj + Ck + (Ai × Bj) +
+ (Ai × Ck) + eijkl
where:
μ – mean;
Ai – breed (1 – MO; 2 – PHF);
Bj – lactation number (1 – first,
2 – second, 3 – third, 4 – fourth
and more);
Ck – production intensity (1 – larger
herds,
intensive
production
system; 2 – smaller herds, moderate production intensity);
Ai × Bj – interaction between breed and
lactation;
Ai × Ck – interaction between breed and
production intensity;
eijkl – random error.
30
During the statistical analysis of the
production parameters of studied cows
also influence of the shape of the lactation curve on the analyzed traits was performed according to model 2, which is:
Y = μ + Eh + eh
where:
μ – mean;
Eh – lactation curve shape (1-C1;
2-C3; 3-C4);
Due to the incidental occurrence C2
curve was omitted in further analysis.
To evaluate impact of the production
parameters on dynamics of parameters
b and c of Wood function model 3 were
applied in a form:
Y = μ + Fg + Gt + eijkl
where:
μ – mean;
Fg – parameter b (1) ≤ 0; (2) 0–0.5;
(3) > 0.51);
Gt – parameter c (1) ≤ –0.25; (2)
–0.249–0.3; (3) > 0;
In order to determine the direction
and strength of the relationship between
parameters b and c of the Wood model
and the production traits Pearson correlations were calculated.
Distributions of the different types of
lactation curves of the MO and PHF
breeds are shown in Table 2. There was
a significant (P ≤ 0.05) differences
between both breeds in report to lactation curves distributions. The most
frequently observed type of lactation
curve was standard lactation curve (1),
which occurred in 73.9% cows. Similar
results obtained Olori et al. (1999).
Marcciotta et al. (2005), reported 80
and 17% frequencies of types C1 and
C4, respectively. The standard shape of
the lactation curve, illustrating the daily
changes in milk yield, was observed
more frequently in MO than PHF cows
(of more than 7 percentage points).
Other types of curves occurred less
frequently: type 3 (16.8%) and type 4
(9.2%). Significant differences between
breeds were reported only during statistical analysis of type 3 of lactation curve.
The PHF cows were characterized by a
6.4 percentage point higher frequency of
the type 3 of lactation curve.
The effect of breed on the development of Wood’s model parameters was
studied (Table 3). Statistically significant differences between the breeds were
observed for the all analyzed parameters.
PHF cows were characterized by a 3.269
kg higher (P ≤ 0.01) daily milk production (the parameter a). Similar results
observed Gołębiewski (2010). However,
MO cows had faster dynamic of production to the lactation peak and more rapid
decline after reaching maximum capacity (respectively parameters b and c of
Wood’s model). The differences between
the breeds were 0.105, 0.025 respectively
for parameters b and c with comparable
level of the determination coefficient
(R2). Olori et al. (1999) observed great
proportion of lactation curves with
R2 ≥ 0.75.
Table 4 presents the effect of the intensity of production on the parameters of
Wood’s model. It was noted (P ≤ 0.01)
higher values of the parameter a (3.614)
31
TABLE 2. Distribution of the lactation curve types in Polish Holstein-Friesian and Montbeliarde cows
Curve shape
PHF
694
1
181
91
967
1
2
3
4
Total
Breed
%
68.4
100.0
78.4
71.7
–
MO
321
0
50
36
407
%
31.6
0.0
21.6
28.3
–
Total
PHF and MO
1015
1
231
127
1374
%
73.9
0.1
16.8
9.2
100.0
Chi2 ≤ 0.05; 1 – standard; 2 – ascending; 3 – descending; 4 – inverted.
TABLE 3. Influence of the breed of cow on Wood’s model parameters
Breed
Parameter
a
b
c
R2
N
967
967
967
967
PHF
Mean
31.943**
0.228**
–0.121**
0.718*
SE
0.326
0.014
0.004
0.007
N
407
407
407
407
MO
Mean
28.674**
0.333**
–0.146**
0.693*
Total
SE
0.522
0.023
0.007
0.012
N
1374
1374
1374
1374
Mean
30.975
0.259
–0.129
0.711
SE
0.280
0.012
0.003
0.006
a – parameter describing general production ability related to peak lactation; b – parameter related to the ascending
part of the curve between calving and peak of lactation; c – parameter related to the descending part of the curve
following lactation peak; R2 – determination coefficient;
* significance at P ≤ 0.05; ** significance at P ≤ 0.01.
TABLE 4. Influence of the production intensity on Wood’s model parameters
Production intensity
Parameter
a
b
c
R2
N
233
233
233
233
1
Mean
33.976**
0.317*
–0.159**
0.726
SE
0.728
0.036
0.010
0.013
N
1141
1141
1141
1141
2
Mean
30.362**
0.247*
–0.122**
0.708
Total
SE
0.299
0.012
0.003
0.007
N
1374
1374
1374
1374
Mean
30.975
0.259
–0.129
0.711
SE
0.280
0.012
0.003
0.006
1 – intensive production; 2 – less intensive production; a – parameter describing general production ability related
to peak lactation; b – parameter related to the ascending part of the curve between calving and peak of lactation; c
– parameter related to the descending part of the curve following lactation peak; R2 – determination coefficient;
defining the overall productivity for
type 1 of farm, which is characterized by
a higher intensity of production, nutrition and free-stall production system.
Cows kept in this system were also
characterized by a faster growth of curve
(P ≤ 0.05) in the initial phase of lactation
and the (P ≤ 0.01) more rapid decrease
(0.037) in its final stage, than cows kept
in farms with lower production intensity,
a – parameter describing general production ability related to peak lactation; b – parameter related to the ascending part of the curve between calving and peak of lactation; c – parameter related to the descending part of the curve following lactation peak;
R2 – determination coefficient; 1, 2, 3, 4 and more – lactation numbers;
* significance at P ≤ 0.01.
0.003
0.006
0.711
–0.129
1374
1374
0.034
0.028
–0.133
0.707
33
33
0.009
0.011
0.768*
–0.155*
281
281
0.01
0.007
–0.142*
0.774*
356
356
704
0.009
–0.111*
704
c
R2
0.656*
0.275
704
b
0.004
0.012
0.259
30.975
1374
1374
0.1
1.811
38.472*
0.15
33
33
0.611
0.029
0.287
36.378*
281
281
0.023
0.527
36.106*
0.217
356
356
25.872*
704
a
0.29
Se
Mean
N
Se
Mean
N
0.015
Mean
N
Mean
Se
N
Mean
Se
N
Total (n = 1374)
4 and more n = 33
3 (n = 281)
Lactation
2 (n = 356)
1 (n = 704)
Parameter
TABLE 5. Influence of the lactation number on Wood’s model parameters
0.295
Se
32
traditional feeding and tie-stall system.
The determination coefficient (R2) did
not differ significantly in both types of
farms. Also Gołębiewski (2010), confirmed that cows kept under intensive
production system characterized by
higher milk production.
When analyzing the effect of the lactation number on Wood’s model parameters (Table 5) study revealed that the
value of the parameter a for the cows
in first lactation were lower (P ≤ 0.01)
from lactating cows at second, third,
fourth and further lactations (by 10.234,
10.506, 12.600 respectively). It was also
found lower value of the parameter c of
primiparous versus cows at second and
third lactation (0.031 and 0.44 at P ≤
≤ 0.01 respectively), what was probably
caused by better lactation persistency of
younger cows. Similarly, the R2 value
was lower at first than at second and third
lactation (0.118 and 0.112 respectively).
There were no significant differences in
the values of the parameter b between
different lactations numbers.
There was no relation between lactation curve and performance parameters
in standard lactation. The best production parameters, such as: milk, FCM,
ECM, fat, protein, lactose and dry matter,
were characterized by a cow with lactation curve opposite to the standard curve
(type 4) however the values were very
similar to those obtained by the cows
standard (type 1) lactation curve. Cows
with a standard lactation curve characterized by the highest concentration of
chemical components of milk, excluding
protein content which reached the highest value at cows with a decreasing lactation curve (type 3).
Different results were observed during
the analysis of the relationship between
the shape of the lactation curve, and the
performance parameters based on the
daily records (Table 6). Significant differences in daily milk yield were reported
between cows characterized by curves of
types 1 and 4 (1.691), and types 3 and
4 (1.548). Cows with a standard curve
(type 1) had the highest daily production.
The number of somatic cells (P ≤ 0.01)
differ between cows characterized by
a different course of lactation curve, and
was the lowest for type 1 (611.070), and
the difference between types 1 and 3 and
types 1 and 4 were 127.56 and 139.39
respectively. Lactation curve type had an
influence (P ≤ 0.05) on the percentage
of protein in milk. The highest protein
content were reported in milk produced
by cow characterized by standard lactation curve (3.484) and the lowest in milk
of cows with type 4 of lactation curve
(3.378). There was no relation between
of lactation curve shape and concentration of fat, lactose, dry matter and urea
in milk.
33
Table 7 presents the relationship
between the dynamics of lactation curve
changes, and the performance parameters
based on test day records. There was a significantly higher daily yield of cows with
a moderate increase in the initial phase of
lactation (parameter b) compared with the
cows characterized by rapid increase of the
milk production before the lactation peak.
Cows with moderate value of parameter b
(2) also characterized by a higher content
of fat, protein, lactose and dry matter in
milk than cows from the first group (P ≤
0.01), as well as lower somatic cells count
in milk (P ≤ 0.01), and the highest urea
levels compared with cows of fast (1)
and slow (3) growth rate of the lactation
curve. Cows characterized by the smallest
value of parameter b characterized by the
(P ≤ 0.01) the highest percentage of protein content (3.558) and the lowest level
of urea in milk (230.62) compared to the
cows of the other groups (1.2).
Analyzing the lactation curve declining rate at the final phase of lactation
(parameter c) the dominance of cows
with moderate decrease rate (2) on other
TABLE 6. Relation between lactation curve shape and production traits of cows based on test day
records
Curve shape
Trait
Milk (kg)
Fat (%)
Protein (%)
Lactose (%)
Dry matter (%)
Somatic cell
count (K/ml)
Urea (mg/l)
N
1015
989
1015
1015
1015
1
Mean
23.069*
3.904
3.484**
4.938
13.322
SE
0.169
0.042
0.016
0.008
0.023
N
231
229
231
231
231
3
Mean
22.926*
3.922
3.433**
4.952
13.307
SE
0.350
0.088
0.033
0.014
0.045
N
127
126
127
127
127
1015
611.070* 25.964
231
738.630* 58.593
127
1015
232.360
231
246.210
127
2.067
4.409
4
Mean
21.378*
3.727
3.378**
4.976
13.268
SE
0.493
0.132
0.043
0.014
0.066
750.460** 74.114
240.730
6.495
34
TABLE 7. Influence of the dynamics of lactation curve changes on milk production
Parameter
Trait
N
1 Mean
SE
N
b 2 Mean
SE
N
3 Mean
SE
N
1 Mean
SE
N
c 2 Mean
SE
N
3 Mean
SE
Milk
(kg)
Fat
(%)
Protein
(%)
Lactose
(%)
Dry
matter
(%)
Somatic
cell count
(K/ml)
Urea
(mg/l)
360
357
360
360
360
360
360
22.367**
0.286
661
23.262**
0.209
353
22.72
0.286
509
22.554**
0.239
737
23.38*
0.196
128
21.383**
0.489
3.852
0.073
649
3.941
0.051
339
3.833
0.077
492
3.878
0.063
726
3.927
0.048
127
3.729
0.131
3.414*
0.026
661
3.443*
0.019
353
3.558*
0.026
509
3.558*
0.022
737
3.417*
0.018
128
3.375*
0.043
4.961
0.01
661
4.94
0.009
353
4.935
0.013
509
4.933
0.011
737
4.946
0.008
128
4.977
0.013
13.292
0.037
661
13.304
0.028
353
13.357
0.04
509
13.389*
0.033
737
13.271*
0.026
128
13.266
0.065
739.68*
45.788
661
583.79*
28.179
353
663.21
52.754
509
706.8**
44.446
737
584.94**
25.905
128
745.52**
73.699
244.34*
3.64
661
248.8*
2.614
353
230.62*
3.308
509
229.75*
2.829
737
252.27*
2.434
128
241.88
6.544
b, c – parameters of Wood’s model;
1, 2, 3 – dynamics of lactation curve changes;
groups (1 and 3) for the majority of production parameters was observed. These
cows produced more milk (P ≤ 0.01) from
cows with high (1) and small (3) values
of parameter c. Milk obtained from these
cows was characterized by a high content of fat, had significantly lower levels
of somatic cells count as well (P ≤ 0.01)
as the highest level of urea than animals
from other groups. Cows with the fast
declining rate (1) of lactation curve at
the end of lactation were characterized
higher milk production (P ≤ 0.05), the
highest concentration of protein in milk
(3.558) and dry matter (13.389) than
cows of group 3 (P ≤ 0.01).
There was no significant correlation
between the Wood’s model parameters
and production traits in standard lactation. However a significant (P ≤ 0.01)
correlations were reported between the
parameter b and the percentage of protein (0.105) in milk based on daily test
records (Table 8). Moreover, negative
correlation was observed between the
level of urea in the milk of the parameter
b (–0.067). The parameter c (P ≤ 0.01)
was negatively correlated with the percentage of protein content (–0.182) and
dry matter (–0.098) in milk. There was
also a negative correlation (P ≤ 0.05)
between the parameter c and the number
TABELA 8. Correlations between Wood’s model
parameters and milk production traits (mean values)
Parameter
b
c
Milk (kg)
–0.005
0.022
Fat (%)
–0.017
–0.001
Protein (%)
0.105** –0.182**
Lactose (%)
–0.014
0.043
Dry matter (%)
0.037 –0.098**
Somatic cell count (K/ml) 0.003
–0.058*
Urea (mg/l)
–0.067* 0.0143**
of somatic cells count (–0.058). Study
reveled that correlation between the urea
content and parameter c of Wood’s model
remained at 0.0143.
CONCLUSION
Irrespectively to cow’s breed, the most
frequently type of lactation curve was
standard lactation curve. However, the
abnormal shape of lactation curves
were more frequent in MO than PHF
cows. Moreover, study reviled that, only
standard lactation curved guaranteed the
highest daily milk production.
REFERENCES
BAR-ANAN R., RON M., 1985: Association
among milk yield, yield persistency, conception, and culling of Israeli Holstein dairy cattle.
J. Dairy Sci. 68: 382–386.
De VRIES A., 2006: Economic value of pregnancy in dairy cattle. J. Dairy Sci. 89: 3876–3885.
DEKKERS J.C.M., TEN HAAG J.H., WEERSINK A., 1998: Economic aspects of persistency of lactation in dairy cattle. Livest. Prod.
Sci. 53: 237–252.
GENGLER N., 1996: Persistency of lactation
yields: A review. Interbull Bulletin 12: 87–96.
GENGLER N., MISZTAL I., 1996: Approximation of reliability for multiple-trait animal
35
models with missing data by canonical transformation. J. Dairy Sci. 79: 317–328.
GOŁĘBIEWSKI M., 2010: Porównanie efektywności użytkowania bydła rasy montbeliarde
i odmiany czarno-białej rasy polskiej holsztyńsko-fryzyjskiej. Praca doktorska. SGGW, Warszawa.
GOODAL E.A., SPREVAK D. 1984: A note on
a stochastic model to describe the milk yield of
a dairy cow. Anim. Production 38: 133–136.
GROSSMAN M., HARTZ S.M., KOOPS W.J.,
1999: Persistency of Lactation Yield: A Novel
Approach. J. Dairy Sci. 82: 2192–2197.
HARDER B., BENNEWITZ J., HINRICHS D.,
KALM E., 2006: Genetic parameters for health
traits and their relationship to different persistency traits in German Holstein dairy cattle.
J. Dairy Sci. 89: 3202–3212.
HARTLEY H.O., 1961: The modified Gauss–
–Newton method for the fitting of nonlinear
regression functions by least squares. Technometrics 3: 269–280.
JAKOBSEN J.H., MADSEN P., JENSEN J.,
PEDERSEN J., CHRISTENSEN L.G., SORENSEN D.A., 2002: Genetic parameters
for milk production and persistency for Danish Holsteins estimated in random regression
models using REML. J. Dairy Sci. 85: 1607–
–1616.
JAMROZIK J., SCHAEFFER L.R., DEKKERS
J.C.M., 1997: Genetic evaluation of dairy cattle using test day yields and Random Regression Model. J. Dairy Sci. 80: 1217–1226.
LEON-VELARDE C.U., MCMILAN I., GENTRY R.D., WILTON W., 1995: Models for
estimating typical lactation curves in dairy
cattle. J. Animal Breeding and Genetics 112:
333–340.
MACCIOTTA N.P.P., VICARIO D., CAPPIOBORLINO A., 2005: Detection of Different
Shapes of Lactation Curve for Milk Yield in
Dairy Cattle by Empirical Mathematical Models. J. Dairy Sci. 88: 1178–1191.
MUIR B.L., FATEHI J., SCHAEFFER L.R.,
2004: Genetic relationships between persistency and reproductive performance in first
lactation Canadian Holsteins. J. Dairy Sci. 87:
3029–3037.
OLORI V.E., BROTHERSTONE S., HILL W.G.,
MCGURIC B.J., 1999: Fit of standard models
of the lactation curve to weekly records of milk
36
production of cows in single herd. Livest. Prod.
Sci. 58: 55–63.
ROWLANDS G.J., LUCEY S., RUSSELL A.M.,
1982: A comparison of different models of the
lactation curve in dairy cattle. Animal Production 35: 135–144.
SCHAEFFER L.R., DEKKERS J.C.M., 1994:
Random regression in animal models for test-day production in dairy cattle. Proc. 5th World
Congr. Genetics and Applied Livestock Production Guelph. ON. 28: 443–446.
SWALVE H.H., GENGLER N., 1999: Genetics
of lactation persistency. Occasional Publication Brochure Sociology in Animal Sciences.
24: 75–82.
TOGASHI K., LIN C.Y., 2009: Economic
weights for genetic improvement of lactation
persistency and milk yield. J. Dairy Sci. 92:
2915–2921.
WELLER J.I., EZRA E., LEITNER G., 2006:
Genetic analysis of persistency in the Israeli
Holstein population by the multi-trait animal
model. J. Dairy Sci. 89: 2738–2746.
WOOD P.D.P., 1967: Algebraic model of the lactation curve in cattle. Nature 216: 164–165.
WOOD P.D.P., 1976: Algebraic models of lactation curves for milk, fat and protein production,
with estimates of seasonal variation. Animal
Production 22: 35–40.
Streszczenie: Zależność między kształtem oraz
przebiegiem krzywej laktacji a cechami produkcyjnymi krów rasy polskiej holsztyńsko-fryzyjskiej
i montbeliarde. Celem pracy było określenie zależności między kształtem i przebiegiem krzy-
wych laktacji a kształtowaniem się parametrów
produkcyjnych w stadach krów rasy PHF i MO
w różnych systemach utrzymania. Wskaźniki
produkcyjne analizowanych stad opracowano na
podstawie wyników oceny użytkowości mlecznej, które obejmowały 1374 laktacje. Do obliczenia parametrów krzywej laktacji wykorzystano
model Wooda. Analizowano wpływ rasy, laktacji oraz typu gospodarstwa na kształtowanie się
parametrów modelu Wooda. Badano również
zależność między kształtem i przebiegiem krzywej a produkcją i składem chemicznym mleka
w próbnych udojach. W przeprowadzonych badaniach stwierdzono, że najczęściej występującym
typem krzywej była krzywa standardowa, która
wykazała większą częstotliwość krów rasy MO
niż PHF. Standardowy przebieg krzywej laktacji
gwarantował największą produkcję i jakość mleka
badanych krów. Stwierdzono istotny wpływ rasy,
laktacji oraz typu gospodarstwa na kształtowanie
się parametrów modelu Wooda. Krowy charakteryzujące się mniej dynamicznym przebiegiem
laktacji charakteryzowały się istotnie lepszą produkcyjnością laktacyjną.
Authors’ address:
Marcin Gołębiewski
02-786 Warszawa, Ciszewskiego 8, Poland
Variation in the activity of stearoyl-CoA desaturase enzyme
and endogenous precursors of unsaturated fatty acids
in cow’s milk during grazing season
BEATA KUCZYŃSKA, KAMILA PUPPEL, TERESA NAŁĘCZ-TARWACKA,
MARTA CZUB
Abstract: Variation in the activity of stearoyl-CoA desaturase enzyme and endogenous precursors of unsaturated fatty acids in cow’s milk
during grazing season. The aim of this study was
to determine variation in the activity of stearoyl-CoA desaturase enzyme and endogenous precursors of unsaturated fatty acids in cow’s milk during the grazing season. The study was carried out
in 10 certified organic farms The major criterions
of choosing organic farms to the experiment were
as follows: obtaining certificate for at least five
years and abidance of the organic farming standards, possessing a herd of Black and White Polish
Holstein-Friesian cows (numbering more than
30 cows). The highest concentrations of CLA
cis9, trans11 isomer, TVA and LA in milk fat has
been reported in June, slightly lower in July and
August. While the lowest level has been recorded
in May, at the beginning of grazing period. Significant correlations between MUFA and SCD (r2 =
= 0.828, P < 0.01) has been recorded. We concluded, that monitoring of SCD activity can be used
as a tool to achieve high unsaturation of milk fat,
during grazing period.
Key words: CLA, SCD, TVA, LA, grazing, bovine
milk
INTRODUCTION
In recent years, scientific and public
interest are relating with nutritional quality of milk, which play significant role in
maintaining of human health. Milk and
milk products are desirable and valuable
source of food. The nutritional quality
of dairy products is strongly correlated
with the quality of milk fat and relates
to a high concentration of unsaturated
fatty acids, as well as high content of
conjugated dienes of linoleic acid (C18:2
c9, t11; CLA). Oleic acid (C18:1 c9;
OA) is important representative of monounsaturated fatty acid (MUFA) found
in adipose tissue and in triacylglycerols
of cow’s milk fat. Dairy products are the
major dietary source of CLA, but CLA is
also found in the meat from ruminants.
CLA is a term used to describe positional
(carbon 6,8 to 12,14) and geometric (cis-cis (c), cis-trans (c,t), trans-cis (t, c) and
trans-trans (t, t)) isomers of linoleic acid
(C18:2 n6 c9, c12; LA). The content of
major CLA isomers in ruminants milk
fat could be precisely determining both
by standards method e.g.: gas chromatography with a flame – ionization detector
(GC-FID) and silver ion high performance liquid chromatography (Ag+HPLC)
or by more advanced techniques e.g.
gas chromatography – mass spectrometry (GC-MS) (Radzik-Rant et al.
2012). Stearoyl-CoA desaturase (SCD)
38
B. Kuczyńska et al.
catalyzes the introduction of the first
cis-double bond in the delta-9 position
(between carbons 9 and 10) in several
fatty acyl-CoA substrates. Activity of
SCD enzyme is regulated by many
different factors, e.g.: diet, hormones,
temperature, metals, peroxisomal proliferators, vitamin A and developmental
processes (Bernard et al. 2001 by Ntambi
1995, 1999). In cow’s milk, OA, palmitoleic acid (C16:1 c9) and substantial part
of CLA are synthesised endogenously, in
the mammary gland through the action
of mammary delta-desaturase on stearic
(C18:0), palmitic (C16:0) and vaccenic
(C18:1 t11; TVA) acids (Griinari and
Bauman 1999).
Nutrition and herd management practices appears to be the factors which
have the highest effect on the CLA concentration in milk and milk products,
and an organic diet based on fresh or
dried forage, that is rich in CLA precursory fatty acids, may improve the yield
of fatty acids with beneficial effects on
health (Prandini et al. 2009).
Analysis of the fatty acid composition of milk fat (derived from different
species of animals), showed that organic
system significantly shapes the antioxidant capacity of milk (Barłowska et
al. 2011, Kuczyńska 2011a, b, Markiewicz-Kęszycka et al. 2013). It should be
noted that organic milk reduced eczema
incidence in infants (Rist et al. 2007,
Kummeling et al. 2008). Differences
in the levels of SCD activity may be
explained by the significant variations
in the content of unsaturated fatty acids
(MUFA, TVA, CLA, LA etc.) in cow’s
milk fat in response to the dietary factors
(Griinari and Bauman 1999, Chilliard et
al. 2000).
High importance is attributed to feeding regime at organic farms, as well as
a higher biological value of pastures
(a higher proportion of herbs, clovers
or Fabaceae plants) compared to non-organic ones (Ellis et al. 2006, Collomb
et al. 2008, Butler et al. 2011, Kuczyńska
et al. 2011a, b, Baars et al. 2012). The
concentration of essential fatty acids
(EFAs) can be increased in cow’s milk
through the diet manipulation by supplementation of cow’s diet various types
of oils or seeds (Reklewska et al. 2002,
Puppel et al. 2013). An increasing interest in enhancing CLA content in milk,
particularly C18:2 cis9, trans11, has
been linked to beneficial health effects
of this isomer. CLA arises anti-carcinogenic, anti-diabetic, anti-atherogenic,
anti-lipogenic and immunomodulatory
functions observed in clinical and biological research (Pariza 1999, Parodi
1999). In addition CLA inhibit chemically induced tumors, prevent atherosclerosis and improve the protein-to-fat
ratio in experimental animals.
The aim of this study was to determine variation in the activity of stearoyl-CoA desaturase enzyme and endogenous
precursors of unsaturated fatty acids in
cow’s milk during the grazing season.
The study was carried out in 10 certified
organic farms The major criterions of
choosing organic farms to the experiment
were as follows: obtaining certificate for
at least five years, abidance of the organic
farming standards, and possessing a herd
of Black and White Polish Holstein-Friesian cows (numbering more than 30
cows). Selected farms were located in
Variation in the activity of stearoyl-CoA desaturase enzyme and endogenous precursors...
Mazovia region in close neighborhood,
to provide comparable climate and soil
conditions. Representative milk samples
(from 165 cows) were collected from
each cow during milking by means of
a milk meter in the milking parlor during
grazing seasons (from May to August).
At the initial grazing period (May) cows
were grazing on pasture (ad libitum)
and additionally received 10 kg of grass
silage and 2 kg of concentrate per cow
daily. Then, from June to August basis
diet of cows constituted a pasture. Cows
were strip-grazed on a multispecies
pasture (Dactylis glomerata L. 16%;
Phalaris arundinacea L. 6%; Agrostis
stolonifera L. 3.4%; Poa pratensis L.
14.5%; Lolium perenne L. 14%; Festuca
rubra L. 4.3%; Trifolium repens 15.5%;
Trifolium pratense L. 4.5%; Poa annua
and P. trivialis 8.3%. Five quadrants
(1 m2 each) of pasture (from each organic farms) were cut one day of each
week pre- and post-grazing to determine
chemical composition.
Combined milk from morning and
evening milking was placed in sterile
bottles, preserved with Mlekostat CC
(660 samples of milk; 165 samples of
milk per month). After milking, samples
were immediately submitted to the Cattle
Breeding Division (Milk and Meat Testing Laboratory of Warsaw University of
Life Sciences) for analysis.
Analyzed of health-promoting compounds of cow’s milk lipid fraction
included determination concentrations
of CLA, TVA and LA. Extraction of
crude fat was performed according to
Röse-Gottlieb procedure (AOAC 1995),
at a room temperature. Fatty acid methylation was performed according to the
transesterification method by EN ISO
39
5509:2000. Analysis of fatty acid methyl
esters (FAME) was carried out with
a gas chromatograph (GC instrument
type 7890A Agilent Technologies) with
Agilent ChemStation, using a Varian
CP-SIL 88 fused-silica capillary column
(100 m length, 0.25 mm internal diameter
and 0.20 μm film thickness). The separation of one micro liter of each sample
was performed at pre-programmed
temperature: column temperature was
kept at 130°C, for 1 min, then increased
from 130 to 175°C at rate of 5.5°C per
min (kept at 175°C for 8 min), and then
to 215°C at rate of 2.75°C per min, and
was kept at 215°C for 10 min. Subsequently temperature increased from 215
to 230°C at rate of 20°C per min and was
kept at 230°C for 10 min. Total run time
was 52.477 min. Purified helium was
used as a carrier gas, with a head pressure of 49.6 kPa and a constant column
flow of 1.5 ml per min. The flow rate of
the carrier gas was average velocity to
23.535 cm per sec. The injection system
(Agilent Technologies type G 4513A)
used a split ratio of 1 : 100 and an injector temperature 180°C. The detection by
a flame-ionization detector (FID) detector was temperature at 250°C. Peaks of
individual fatty acids were identified by
using pure fatty acids standards: PUFA
1 from marine, composed of 18 fatty
acid standards from C14:0 to C24:1 and
with individual C18:1 trans11 and CLA
standards (Sigma-Aldrich). Additionally,
selected saturated and monounsaturated
fatty acids were analyzed in order to
formulate index of activity of stearoyl-CoA desaturase (SCD) enzyme as an
indicators of endogenous precursors of
unsaturated fatty acids in cow’s milk.
Activity of SCD enzyme was assessed
40
and calculated as proposed by Smith et
al. (2002), using the following formula:
(C16:1 + C18:1) / (C14:0 + C16:0 +
+ C18:0 + C16:1 + C18:1).
The data obtained were analyzed statistically using analysis of variance (least
squares) by means of the SPSS 21 packet
software.
The model used for analyzed milk
samples was
Yijk = μ + Ai + eij
where:
Yijk – dependent variable;
μ – general mean;
Ai – month effect (May, June, July,
August);
eij – standard error.
The nutritional requirements of the animals and the nutritive value of their diet
were calculated in accordance with the
nutrition standards set out in the INRATION 4.0 software. Table 1 summarizes
the feeding characteristics during grazing
period from May to August.
In the current study, activity of
stearoyl-CoA enzyme and endogenous
precursors of unsaturated fatty acids of
cow’s milk was weakening with the passage of the grazing season (Fig. 1).
Generally, the highest concentrations
of CLA cis9, trans11 isomer, TVA and
LA in milk fat has been reported in June,
slightly lower in July and August. While
the lowest level has been recorded in
May, at the beginning of grazing period.
The first time in the 1930s already,
Both et al., noted that summer milk had
a greater absorbance at 233 nm than milk
produced in the winter. In 1963, Riel
noted that summer milk fat had more
conjugated dienoic acid than winter milk
fat. Ruminants that are exlusively pasture fed produce greater levels of TVA
and CLA compared to those fed indoors
(Nałęcz-Tarwacka 2006), although this
effect is depended on the specific diet
composition (Puppel et al. 2013). The
CLA content mirrored the TVA rather
than LA content with a drop TVA in TVA
TABLE 1. Chemical composition and nutritional value of pastures used in cow feeds (% of DM)
Traits
Ash
Crude protein
Ether extract
Crude fibre
UFL
PDIN
PDIE
NDF
ADF
LA
LNA
Pasture
May
8.21
14.2
2.4
27.82
0.85
88.96
84.92
42.30
30.4
11.82
33.3
June
8.33
18.52
3.89
26.62
0.84
115.23
96.53
48.56
31.26
43.75
60.6
July
8.81
18.82
4.13
28.62
0.91
115.75
95.62
52.84
40.3
42.5
52.16
August
8.89
19.23
3.56
29.01
0.89
102.56
93.24
45.63
28.96
28.95
45.15
41
4
3,5
**
3
2,5
SCD
2
TVA
LA
1,5
CLA
1
0,5
0
May
June
July
August
** May different from June, July and August for TVA, LA and CLA by contrast (P ≤ 0.01).
FIGURE 1. Variation in the activity of SCD enzyme and the concentrations of TVA, LA, and CLA
(g per 100 g of fat) in cow’s milk during the grazing period
beginning in June and occurring before
the drop in CLA in August. This result
is partially explained by the fact CLA
in milk is mainly from delta-9 desaturasion of TVA in the mammary gland
in ruminants. TVA of cow’s milk fat is
primarily from rumen biohydrogenation
in the pathway LA → CLA cis9, trans11
→ TVA → C18:0 → C16:0.
Soyeurt et al. (2008) reported positive
genetic correlations between the indices
of C14, C16 C18 (0.72, 0.62 and 0.97,
respectively) and monounsaturated fatty
acids (MUFA), and showed that proportion of MUFA is linked to the activity of
SCD.
In Table 2 significant correlations
between activity of SCD enzyme and
selected indexes of delta-9 desaturase,
such as: C14:1 index, C16:1 index and
C18:1 index, (0.144, 0.243 and 0.638,
respectively) has been presented. Increasing the concentration of C18:0 and C18:1
acids and lower level of C16:0 acid are
typical for cows which are grazed on
pasture. In the case of cows fed TMR
TABLE 2. Relationships between selected indexes of delta-9 desaturase and month of grazing, and correlations between activity of SCD enzyme and selected indexes of delta-9 desaturase
Traits
May
June
July
August
LSM
SE
LSM
SE
LSM
C14:1index
ABC
0.13
0.003
0.10
A
0.002
B
0.11
0.002
0.11
C16:1 index
0.06ABC
0.003
0.06A
0.002
0.05B
0.002
0.05C
C18:1index
1.99
0.057
1.78
0.034
b
1.85
0.035
1.84
0.035 0.63** 0.402**
0.005
0.32
0.003
0.32
0.003
0.32
0.003
27.33ABC 0.608 29.63A 0.364 29.77B 0.363
29.8C
0.375 0.82**
MUFA
Abc
0.31
A
C
c
SE
Correlations
SE
SCD
LSM
SCD
MUFA
0.002 0.14** 0.149**
0.002 0.24**
Values in the rows marked with the same letters differ significantly A,B,C P ≤ 0.01; a,b,c P ≤ 0.05.
**Significant correlaction has been reported.
1
–0.049
0.828**
1
42
diet an inverse relationship has been
demonstrated (Kelly et al. 1998, Nałęcz-Tarwacka 2006, Kuczyńska 2011).
CONCLUSION
In the current study significant correlations between MUFA and SCD
(r2 = 0.828, P < 0.01) has been recorded.
We concluded, that monitoring of SCD
activity can be used as a tool to achieve
high unsaturation of milk fat, during
grazing period.
Acknowledgements
Researches was supported by the National Science Center and realized within
the project N N 311 320135 entitled
“Bioactive components and technological parameters of milk produced
at ecological and conventional farms”.
Additionally, we would like to express
our very great appreciation and respects
to Professor Henryk Grodzki. We feel
deeply honored to have worked with such
remarkable Scientist and we are grateful
for his exceptional help, endless patience
and encouragement that accompanied us
through all those years.
REFERENCES
BAARS T., WOHLERS J., KUSCHE D., JAHREIS G., 2012: Experimental improvement
of cow milk fatty acid composition in organic winter diets. J. Sci. Food. Agric. 92 (14):
2883–2890.
BARŁOWSKA J., SZWAJKOWSKA M., LITWIŃCZUK Z., KRÓL J., 2011: Nutritional
value and technological suitability of milk
from various animal species used for dairy production. Compr. Rev. Food. Sci. F. 10:
291–302.
BERNARD L., LEROUX CH., HAYES H.,
GAUTIER M., CHILIARD Y., MARTIN P.,
2001: Characterization of the caprine stearoylCoA desaturase gene and its mRNA showing
an unusually long 3’-UTR sequence arising
from single exon. Gene 281: 53–61.
BUTLER G., STERGIADIS S., SEAL C., EYRE
M., LEIFERT C., 2011: Fat composition of organic and conventional retail milk in northeast
England. J. Dairy Sci. 94: 24–36.
CHILLIARD Y., FERLAY A., MANSBRIDGE
R.M., DOREAU M., 2000: Ruminant milk fat
plasticity: nutritional control of saturated, polyunsaturated, trans and conjugated fatty acids.
Ann. Zootech. 49: 181–205.
COLLOMB M., BISIG W., BÜTIKOFER U.,
SIEBER R., BREGY M., ETTER L., 2008:
Fatty acid composition of mountain milk from
Switzerland: comparison of organic and integrated farming systems. Intern. Dairy J. 18:
976–982.
ELLIS K.A., INNOCENT G., GROVE-WHITE
D., CRIPPS P., McLEAN W.G., HOWARD
C.V., MIHM M., 2006: Comparing The Fatty
Acid Composition Of Organic And Conventional Milk. J. Dairy Sci. 89 (6): 1938–1950.
GRIINARI J.M., Bauman D.E., 1999: Biosynthesis of conjugated linoleic acid and its incorporation into meat and milk in ruminants. Pages
180–200 in Advances in Conjugated Linoleic
Acid Research. Vol. 1. M.P. Yurawecz, M.M.
Mossoba. J.K.G. Kramer, M.W. Pariza, C.J.
Nelson, eds. Am. Oil Chem. Soc. Press, Champaign, IL.
KELLY M.L., KOLVER E.S., BAUMAN D.E.,
VAN AMBURH M.E., MULLER L.D., 1998:
Effect of intake of pasture on concentrations
of conjugated linoleic acid in milk of lactating
cows. J. Dairy Sci. 81: 1630–1636.
KUCZYŃSKA B., NAŁĘCZ-TARWACKA T.,
PUPPEL K., GOŁĘBIEWSKI M., GRODZKI
H., SLÓSARZ J., 2011a: The content of bioactive components in milk depending on cow
feeding model in certified ecological farms.
J. Res. Appl. Agri. Engng. 56 (4): 7–13.
KUCZYŃSKA B., PUPPEL K., METERA E.,
KLIŚ P., GRODZKA A., SAKOWSKI T.,
2011b: Fatty acid composition of milk from
Brown-Swiss and Holstein-Friesian black and
white cows kept in a certified organic farm.
Ann. Warsaw Univ. Life Sci. 49: 61–67.
KUMMELING I., THIJS C., HUBER M., Van
de VIJVER L., SNIJDERS B., PENDERS J.,
STELMA F., Van REE R., Van Den BRANDT
P., DAGNELIE P., 2008: Consumption of organic foods and risk of atopic disease during the
first 2 years of life in the Netherlands. Brit. J.
Nutr. 99: 598–605.
NAŁĘCZ-TARWACKA T., 2006: Effect of selected factors on the functional component content of milk fat in dairy cows. Treatises and
Monographs. Wyd. SGGW, Warszawa.
MARKIEWICZ-KĘSZYCKA M., CZYŻAK-RUNOWSKA G., LIPIŃSKA P., WÓJTOWSKI J., 2013: Fatty acid profile of milk – a review. Bull. Vet. Inst. Pulawy 57: 135–139.
PRANDINI A., SIGOLO S., PIVA G., 2009: Conjugated linoleic acid (CLA) and fatty acid
composition of milk. curd and Grana Padano
cheese in conventional and organic farming systems. J. Dairy Res.76 (3): 278–282.
PUPPEL K., KUCZYŃSKA B., NAŁĘCZ-TARWACKA T., GRODZKI H., 2013: Influence of
linseed variety on fatty acid profile in cow’s
milk. J. Sci. Food Agric. 93: 2276–2280.
RADZIK-RANT A., ROZBICKA-WIECZOREK
A., RANT W., CZAUDERNA M., KUCZYŃSKA B., 2012: The content of cis-9, trans-11
CLA isomer determined by two methods in
ewe’s milk fat. Ann. Warsaw Univ. Life Sci.
51: 119–126.
REKLEWSKA B., OPRZĄDEK A., REKLEWSKI Z., PANICKE L., KUCZYŃSKA B.,
OPRZĄDEK J., 2002: Alternative for modifying the fatty acid composition and decreasing
the cholesterol level in the milk of cows. Liv.
Prod. Sci. 76: 235–243.
RIST L., MUELLER A., BARTHEL C., SNIJDERS B., JANSEN M., SIMÕES-WÜST A.P.,
HUBER M., KUMMELING I., VON MANDACH U., STEINHART H., THIJS C., 2007:
Influence of organic diet on the amount of conjugated linoleic acids in breast milk of lactating
women in the Netherlands. British J. Nutr. 97:
735–743.
SOYEURT H., DEHARENG F., MAYERES P.,
BERTOZZI C., GENGLER N., 2008: Variation of Δ9-desaturase activity in dairy cattle.
J. Dairy Sci. 91: 3211–3224.
43
TURPEINEN A.M., MUTANEN M., ARO A.,
SALMINEN I., BASU S., PALMQUIST D.L.,
GRIINARI J.M., 2002: Bioconversion of vaccenic acid to conjugated linoleic acid in humans. Am. J. Clin. Nutr. 76: 504–510.
Streszczenie: Wpływ okresu wypasu pastwiskowego na poziom indeksu enzymu stearoilo-CoA
desaturazy i jego endogennych prekursorów nienasyconych kwasów tłuszczowych w mleku krowim. Celem pracy było określenie zmienności
w aktywności enzymu delta-9 desaturazy SCD
i koncentracji endogennych prekursorów nienasyconych kwasów tłuszczowych w mleku krów
w okresie wypasu pastwiskowego. Badania przeprowadzono w 10 certyfikowanych gospodarstwach ekologicznych. Główne kryteria wyboru
gospodarstw ekologicznych do eksperymentu to:
posiadanie certyfikatu od co najmniej pięciu lat
i przestrzeganie standardów z ekologicznej produkcji, utrzymywanie minimum 30 krów rasy
polskiej holsztyńsko-fryzyjskiej w stadach. Najwyższe koncentracje: izomeru CLA c9, t11, TVA
i LA w tłuszczu mlekowym wykazano w czerwcu, nieco niższe w lipcu i sierpniu. Najniższe
poziomy natomiast zaobserwowano w maju,
w początkowym okresie wypasu pastwiskowego.
Wykazano istotną korelację (p ≤ 0,01) między
MUFA i SCD (r2 = 0,828). Podsumowując, monitorowanie aktywności SCD może być użyteczne
jako narzędzie w celu zwiększania nienasycenia
tłuszczu mleka pozyskiwanego w trakcie wypasu
pastwiskowego.
Authors’ address:
Beata Kuczyńska
ul. Ciszewskiego 8, 02-786 Warszawa, Poland
e-mail: beata_kuczyń[email protected]
Relationships between milk β-carotene concentrations
and the cytological quality of cow’s milk
BEATA KUCZYŃSKA, ALEKSANDRA KAPUSTA, KAMILA PUPPEL,
TERESA NAŁĘCZ-TARWACKA, ARKADIUSZ BUDZIŃSKI,
MARCIN GOŁĘBIEWSKI, MARTA CZUB, HENRYK GRODZKI
Abstract: Relationships between milk β-carotene concentrations and the cytological quality
of cow’s milk. The objective of the study was to
describe the relationship between milk β-carotene concentration and the cytological quality
of milk of high yielding cows. The experiment
was carried out at the research dairy farm of the
Warsaw University of Life Sciences – SGGW
(WULS). From a herd of 320 Polish Holstein-Friesian cows maintained in a free-stall dairy
shed 58 cows were selected taking into consideration the stage of lactation (15 ±14 days).
Cows were fed a total mixed ration (TMR) diet
provided ad libitum. Four groups of cows taking
into consideration concentration of β-carotene
in milk has been created: (1) below 150 mg/l;
(2) 151–250 mg/l; (3) 251–450 mg/l; (4) beyond
450 mg/l. The content of β-carotene and SCC
amounted at the herd level: 192 103 ml and 0.312
mg/l respectively. The β-carotene content ranged
from 0.150 to 0.451 mg/l. The highest content
of β-carotene, 0.451 mg/l, was found in milk of
cows with the lowest level of somatic cells count
(SCC). The lowest level, 0.150 mg/l, was found
in milk of cows with the highest level of SCC.
Milk SCC varies significantly with the concentration of β-carotene in cow’s milk. Researchers
should consider monitoring for this variable as
potential cofounder when exploring the relationship between mastitis, intramammary infection
and nutritional management.
Key words: β-carotene, somatic cells count, immunity
INTRODUCTION
Mastitis is the most common infectious
disease of dairy cows and results in economic loss for both dairy farmers and for
dairy’s (Geary et al. 2012). The production of high quality milk is a requirement
to sustain a profitable dairy industry and
somatic cell count (SCC) values are routinely used to identify subclinical mastitis (Philpot and Nickerson 2000). Age,
number of quarters with intramammary
infection, season, nutrition are significant
factors that have been associated with
SCC (Schepers et al. 1997, Kuczyńska
2011, Puppel et al. 2012). Increased
SCC with parity may be attributed to
increased prevalence of intramammary
infection and greater cellular response to
certain pathogens.
β-carotene stabilizes the free radicals,
as meaning breaking the sequence of
radical reactions, and prevents radical
degradation processes of cell components
(Kankofer and Albera 2007). Carotenoids have diverse biological functions
and actins, the most important of which
are effective antioxidants in vitro, but the
situation in vivo is less clear. It stabilizes
the free radicals, as meaning breaking
46
the sequence of radical reactions, and
prevents radical degradation processes
of cell components. Preferably also
operates on the reproductive system. It
has been proved that the higher content
of β-carotene reduces the incidence of
retained placenta, and accelerates and
supports ovarian luteal activity (Kankofer
and Albera 2007, Kawashima et al. 2009,
Kumar et al. 2010). Carotenoids have
also been reported to have immunomodulatory effects, such as the reduction in
UV-induced immunosuppresion and the
increase in natural killer cell activity after
dietary supplementation with β-carotene
(Van den Berg et al. 2000).
Low plasma concentrations of β-carotene is associated with increased incidence of udder infection. Carotenoids
also increase the lymphocytes population
and their activity, stimulate phagocytosis
(Chew 1993, Michal et al. 1994). The
carotenoid content in roughage largely
depends on environmental conditions.
Important is the method of harvest, weather conditions, as well as a method of preserving feed (Bergamo 2003, Krzyżewski
2012). It has been proved that the drying
may result in loss of β-carotene of as
much as 83%. Ensiling process results
in less losses but they get deeper as time
goes on storage silage in a silo or prism
(Krzyżewski 2012).
The objective of the study was to
describe the relationship between milk β-carotene concentration and the cytological quality of milk of high yielding cows.
The experiment was carried out at the
research dairy farm of the Warsaw
University of Life Sciences – SGGW
(WULS). From a herd of 320 Polish
Holstein-Friesian cows maintained in
a free-stall dairy shed 58 cows were
selected taking into consideration the
stage of lactation (15 ±14 days). Cows
were fed a total mixed ration (TMR) diet
provided ad libitum, formulated using
the INRA system (Table 1).
TABLE 1. Ingredient composition of the TMR diet
Ingredients
TMR diet
Feeding ration (kg)
Maize silage
Alfaalfa silage
Maize corn silage
Concentrate
Straw
Total
Concentrate (kg)
Hydropalm – by pass oil
Fodder chalk
NaHCO3
BetaLac – premix
NaCl
Rapeseed meal
Soya meal
Grain meal
Rumex
Ca3(PO4)2
Total
23.33
10.83
3.70
5.12
1.00
43.98
0.60
0.15
0.12
0.13
0.05
2.23
2.30
1.30
0.005
0.05
6.94
Sampling
Representative milk samples were collected from each cow during milking
by means of a milk meter in the milking
parlor. Milk samples were taken individually from each cow 10 times during
the experiment at monthly intervals.
Milk analyses
Analysis of the somatic cell count (SCC)
was performed using a Somacount-150
Relationships between milk β-carotene concentrations and the cytological quality...
counter (Bentley Poland, Warsaw,
Poland).
Analysis of β-carotene was established
using an Agilent 1100 Series reverse
phase high-performance liquid chromatograph (Agilent Technologies, Waldbronn, Germany) and Zorbax Eclipse
XDB C8 column (4.6 × 150 mm, 5 μm
film thickness) according to the method
described by Puppel et al. (2012).
Four groups of cows taking into consideration concentration of β-carotene
in milk has been created: (1) below 150
mg/l; (2) 151–250 mg/l; (3) 251–450
mg/l; (4) beyond 450 mg/l.
Statistical analyses
The data obtained were analyzed statistically by multifactor analysis of variance
using SPSS 21.0 (SPSS Inc., Chicago,
IL, USA).
Yijkl = μ + Ai + Bj + (Ai × Bj) + eijk
where:
Yijkl – dependent variable;
Ai – β-carotene effect (i = 1–4, where:
(1) < 150 mg/l; (2) 151–250 mg/l;
(3) 251–450 mg/l; (4) > 450 mg/l);
Bj – SCC effect;
Ai × Bj – interaction between β-carotene
content and SCC;
eiij – standard error.
TABLE 2. β-carotene and somatic cells count of
bovine milk during experiment
Ingredient
N
LSM
SEM
Somatic cells count
(103/ml)
580
192A
26.674
β-carotene (mg/l)
580
0.312A
0.0083
LSM – least square of the mean, SEM – standard error
of the mean, values in the column marked with the same
letters differ significantly at P ≤ 0.01.
In contrast, Morris (2002) reported
lower concentration of β-carotene (0.1
mg/l). Milk composition can be altered
by the feeding regime. The content of
β-carotene was shown to be transferred
either directly from the feed to the milk
(Kuczyńska 2011) or from supplements
added to the cows’diet (Puppel et al.
2012). Puppel et al. (2012) reported, that
modification of the diet of cows with fish
oil and linseed significantly influenced
antioxidant properties of their milk;
however, the response of multiparous
and primaparous cows was noticeably
different to the supplement introduced.
The content of β-carotene ranged
at the herd level from 0.150 to 0.451
mg/l. The highest content of β-carotene,
0.451 mg/l, was found in milk of cows
with the lowest level of SCC (Table 3).
TABLE 3. Effect of β-carotene concentration in
milk on the somatic cells count
N
Somatic cells
count
(103/ml)
SEM
0.150
112
279 ABC
60.653
0.151–0.250
186
210 AD
47.066
0.251–0.450
164
160
BDE
50.124
> 0.451
118
125 CDE
59.091
β-carotene
(mg/l)
The content of β-carotene and somatic
cells count (SCC) amounted at the herd
level: 192 103/ml and 0.312 mg/l respectively (Table 2). The overall mean for
β-carotene content were similar to the
value obtained by Kuczyńska (2011).
47
SEM – standard error of the mean, values in the column marked with the same letters differ significantly at
P ≤ 0.01.
48
The lowest level, 0.150 mg/l, was found
in milk of cows with the highest level
of SCC. LeBlanc (2004) reported, that
concentration of β-carotene in milk
from cows with mastitis is almost half
lower (0.070 mg/l), than from cows
with healthy gland (0.160 mg/l). Cows
suffering from severe mastitis tend to
produce milk containing less β-carotene and more retinol than non-infected
cows (Chew et al. 1993). It has been
proved, that the higher content of β-carotene reduces the incidence of retained
placenta, and accelerates and supports
ovarian luteal activity (Kankofer 2007,
Kawashima et al. 2009, Kumar et al.
2010). It can therefore concluded that
carotenoids also affect the immunity
of the mammary gland, slow down
the inflammatory process (mastitis),
and thus contribute to a lower content
of SCC in milk (Chew 1993, Michal
1994).
CONCLUSION
Milk SCC varies significantly with the
concentration of β-carotene in cow’s
milk. Researchers should consider
monitoring for this variable as potential
cofounder when exploring the relationship between mastitis, intramammary
infection and nutritional management.
Acknowledgement
Researches was supported by National
Science Center and realized within
the project NN 311 55 8840 entitled
“Relationship between concentration
of bioactive substances in milk during
standard lactation and blood biochemical parameters of high yielding Polish
Holstein-Friesian cow’s”.
REFERENCES
BERGAMO P., 2003: Fat soluble vitamin contents and fatty acid composition in organic
and conventional Italian dairy products. Food
Chem. 82 (4): 625–631.
CHEW B.P., 1993: Role of carotenoids in the immune response. J. Dairy Sci. 76: 2804–2811.
GEARY U., LOPEZ-VILLALOBOS N., BEGLEY N., MCCOY F., O’BRIEN B., O’GRADY
L., SHALLOO L., 2012: Estimating the effect
of mastitis on the profitability of Irish dairy
farms. J. Dairy Sci. 95: 3662–3673.
KANKOFER M., ALBERA E., 2007: The concentration of vitamin a and its provitamin –
β-carotene in bovine retained and not retained
placenta. Acta Vet. (Beograd), 57 (2–3): 181–
–189.
KAWASHIMA C., NAGASHIMA S., SAWADA
K., SCHWEIGERT F.J, MIYAMOTO A., Kida
K., 2010: Effect of β-carotene supply during
close-up dry period on the onset of first postpartum luteal activity in dairy Cows. Reprod.
Dom. Anim. 45: 282–287.
KRZYŻEWSKI J., STRZAŁKOWSKA N., BAGNICKA E., JÓŹWIK A., HORBAŃCZUK
J., 2012: Wpływ antyoksydantów zawartych
w tłuszczu pasz objętościowych na jakość
mleka krów. Żywność – Nauka – Technologia
– Jakość 3 (82): 35–45.
at ecological and conventional farms. Dissertations and Monographs. Wydawnictwo SGGW,
Warsaw (In Polish, with an English abstract).
KUMAR S., PANDEY A.K., MUTHA M.R.,
RAZZAQUE W.A.A., 2010: Role of β-carotene / vitamin A in animal reproduction. Vet.
World 3 (5): 236–237.
LeBLANC S.J., HERDT T.H., SEYMOUR W.M.,
DUFFIELD T.F., LESLIE K.E., 2004: Peripartum serum vitamin E, retinol, and beta-carotene in dairy cattle and their associations with
disease. J. Dairy Sci. 87: 609–619.
MICHAL J.J., HEIRMAN L.R., WONG T.S.,
CHEW B.P., 1994: Modulatory, effects of dietary on blood and mammary leukocyte function in periparturient dairy cows. J. Dairy Sci.
77: 1408–1421.
MORRIS C.A., KNIGHT T.W., NEWMANS
S.A.N., HICKEY S.M., DEATH A.F., O’NEILL
Relationships between milk β-carotene concentrations and the cytological quality...
49
K.T., RIDLAND M., 2002: Genetic studies of
carotenoids concentration in the plasma and
milk of New Zeland dairy cattle. New Zeland
J. Agri. Res. 45: 27–33.
PHILPOT W.N., NICKERSON S.C., 2000: Winning the fight against mastitis. Westfalia-Surge,
Inc.: 13–15.
PUPPEL K., NAŁĘCZ-TARWACKA T., KUCZYŃSKA B., GOŁĘBIEWSKI M., KORDYASZ M., GRODZKI H., 2012: The age of
cows as a factor shaping the antioxidant level
during a nutritional experiment with fish oil
and linseed supplementation for increasing the
antioxidant value of milk. J. Sci. Food Agric.
92: 2494–2499.
SCHEPERS A.J., LAM T.J., SCHUKKEN Y.H.,
WILMINK J.B., HANEKAMP W.J., 1997: Estimation of variance components for somatic
cell counts to determine thresholds for uninfected quarters. J. Dairy Sci. 80: 1833–1840.
Van den BERG H., FAULKS R., FERNANDO
GRANADO H., HIRSCHBERG J., OLMEDILLA B., SANDMANN G., SOUTHON S.,
STAHL W., 2000: The potential for the improvement of carotenoid levels in foods and
the likely systemic effects. J. Sci. Food Agric.
80: 880–912.
(15 ±14 dni), jak również i wiek krów (wieloródki). Krowy objęte były całorocznym żywieniem
TMR, ad libitum. Po uzyskaniu wstępnych wyników, krowy zostały podzielone na cztery grupy,
biorąc pod uwagę średnią koncentrację β-karotenu w tłuszczu mlekowym: (1) poniżej 150 mg/l;
(2) 151–250 mg/l; (3) 251–450 mg/l; (4) powyżej
450 mg/l. Prezentowane wyniki stanowią średnią z 10 pobrań uzyskanych od krów w trakcie
trwania laktacji 305-dniowej. Średnia zawartość
β-karotenu i LKS w mleku krów dla całego stada
wyniosła odpowiednio 0.312 mg/l i 192 tys./ml.
Biorąc pod uwagę zawartość LKS w mleku, koncentracja β-karotenu znajdowała się w przedziale
od 0.150 do 0.451 mg/l. Największą zawartość
β-karotenu, 0.451 mg/l, wykazano w mleku krów
o najwyższej jakości cytologicznej. Najniższy
poziom natomiast w mleku o najwyższym poziomie LKS – 279 103/ml. Badania wykazały, że
poziom LKS w istotny sposób kształtowany jest
przez stężenie β-karotenu w mleku krów. Dlatego też, powinno się rozważyć monitorowanie tej
zmiennej jako potencjalnego czynnika w trakcie
określania zależności między zakażeniem wymienia, mastitis i bilansowaniem dawek pokarmowych w bioaktywne składniki dla wysokowydajnych krów.
Streszczenie: Zależność między zawartością
β-karotenu a jakością cytologiczną mleka. Celem
pracy było określenie zależności między koncentracją β-karotenu a jakością cytologiczną mleka
wysokowydajnych krów rasy PHF. Doświadczenie przeprowadzono w Rolniczym Zakładzie Doświadczalnym SGGW Obory – Wilanów. Ze stada
podstawowego liczącego 320 krów rasy polskiej
holsztyńsko-fryzyjskiej, utrzymywanych w systemie wolnostanowiskowym, wyselekcjonowano 58 krów, biorąc pod uwagę stadium laktacji
Authors’ address:
Beata Kuczyńska
ul. Ciszewskiego 8, 02-786 Warszawa
Poland
Relationships between production traits and the parity of Polish
Holstein-Friesian cows
BEATA KUCZYŃSKA, ARKADIUSZ BUDZIŃSKI,
ALEKSANDRA KAPUSTA, KAMILA PUPPEL, TERESA NAŁĘCZ-TARWACKA,
MARCIN GOŁĘBIEWSKI, AGATA WÓJCIK, HENRYK GRODZKI
Abstract: Relationships between production traits
and the parity of Polish Holstein-Friesian cows.
The objectives of the study was to describe the
relationships between milk urea, protein, fat concentrations and the age of Polish Holstein-Friesian cows. The experiment was carried out at the
research dairy farm of the Warsaw University of
Life Sciences – SGGW (WULS). From a herd of
320 Polish Holstein-Friesian cows maintained in
a free-stall dairy shed 50 cows were selected. Parity
had significant effect on the shaping the concentration of the production traits. The highest content of
protein, 3.87%, was found in milk of cows during
3rd and subsequent lactations in the 10th collecting
(above 271 day of lactation). The fat content ranged
at the herd level from 3.18 to 4.89 %, the highest
level has been recorded in milk of cows during
3rd and subsequent lactations, in the 10th collecting (above 271 day of lactation). The urea content
ranged at the herd level from 183 to 267 mg/l. Milk
production traits varies significantly with the age of
cows. Hence, researchers should consider monitoring for this variable as potential cofounder when
exploring the relationship between urea, protein,
fat content in milk and nutritional management for
meeting the production requirements of cows.
Key words: cow, parity, protein, fat, urea
INTRODUCTION
The gross composition of cow’s milk is
variable, because many factors influence
the end product. These variations can
be related to genetics and environment
parameters. The milk composition also
varies within the cows from milking to
milking and with the intensification of
production, stage of lactation, disease
and age of the cows (Nałęcz-Tarwacka
2006, Januś 2008, Kuczyńska 2011,
Puppel et al. 2012).
Concentration of urea in milk is also
variable from herd to herd and within
cows. The variation in milk urea concentrations indicates a wide variation in
protein, energy and water intake (Minakowski 2006). The proper formulation
of cows diet requires to appropriately
balance diets for rumen digestion and
absorption of needed nutrients for maintenance of body tissue and production
of milk. Hof et al. (1997) reported that
regular measurement of milk urea N in
bulk samples can be used to monitor N
losses from rumen fermentation.
The cow production depends not only
on its genetic and physiological characteristics but also on the quantity and
quality of nutrients to its intermediary
metabolism. Production traits are the
result of the voluntary intake and the
nutrient density of feed intake (Piłat
52
2006). The INRA system distinguishes TABLE 1. Ingredient and chemical composition
the various parts of proteins which are of the TMR diet
finally digested in the intestine, i.e. PDIA Composition
TMR diet
(Protein Digestible in the Intestine from
Ingredient (kg/day)
dietary origin), microbial protein allowed Maize silage
25.000
by available fermentable N (PDIMN) Alfaalfa silage
9.400
and microbial protein allowed by avail- Corn silage
3.700
able fermentable energy (PDIME). The Concentrate
5.200
sum of PDIA + PDIMN, and the sum Straw
1.000
of PDIA + PDIME gives PDIN and
Concentrate (kg)
PDIE values of a feed (Kowalski et al. Hydropalm – by pass oil
0.600
2008). Balancing a cows basal diet with
Pasture ground chalk
0.150
the appropriate supplementary feeds is
NaHCO3
0.125
achieved when PDIN and PDIE values
BetaLac – premix
0.130
are equal (+/–50 g) and meet the producNaCl
0.050
tion requirements (Kida 2003).
2.230
The objectives of this study was to Rapeseed meal
Soya
meal
2.300
describe the relationships between milk
1.300
urea, protein, fat concentrations and the Grain meal
Rumex
0.005
parity of Polish Holstein-Friesian cows
Ca3(PO4)2
0.050
during lactation.
Chemical composition
The experiment was carried out at the
research dairy farm of the Warsaw
University of Life Sciences – SGGW
(WULS). From a herd of 320 Polish
Holstein-Friesian cows maintained in
a free-stall dairy shed 50 cows were
selected taking into consideration: stage
of lactation (8 ±14 days) and parity (1st,
2nd, 3rd and subsequent lactations).
During the experimental period cows
feeding ration was based on the total
mixed ration (TMR) diet provided ad
libitum, formulated using the INRA
system. Representative TMR samples
were analyzed for dry matter, crude
protein, ash, ether extract, acid detergent
fiber, neutral detergent fiber. Chemical
composition of the treatment diets is presented in the Table 1.
DM (%)
Crude protein (% of DM)
Acid detergent fiber (% of DM)
Neutral detergent fiber (% of DM)
Ash (% of DM)
Ether extract (% of DM)
Ca (% of DM)
P (% of DM)
Total (ULF)
Total (PDIE) (g)
Total (PDIN) (g)
57.500
18.500
19.000
28.500
5.000
4.500
0.700
0.500
19.500
1860
1835
Sampling
Representative milk samples were collected from each cow during milking
by means of a milk meter in the milking
parlor. Milk samples were taken individually from each cow 10 times during
the experiment at monthly intervals (10
collecting from each cow). The samples
Relationships between production traits and the parity of Polish Holstein-Friesian cows
53
were collected at following stages of lactation: first: 8–30; second: 31–60; third:
61–90; fourth: 91–120; fifth: 121–150;
sixth: 151–180; seventh: 181–210;
eighth: 211–240; ninth: 241–270 and
tenth: above 271 day of lactation.
Ai – parity effect (1, 2, 3 ,4);
Bj – stage of lactation effect;
(Ai × Bj) – interaction between parity
and stage of lactation;
eij – standard error.
Milk analysis
Gross milk composition, i.e. fat, protein,
and urea content, were determined by
automated infrared analysis (FTIR) with
a Milkoscan FT-120 instrument (FOSS
Electric, Hillerød, Denmark).
Parity had significant effect on the shaping the concentration of the protein in
cow’s milk. The content of this constituents ranged during lactation at the herd
level from 2.95 to 3.87%. The highest
content of protein, 3.87%, was found
in milk of cows during 3rd lactation in
the 10th collecting (above 271st day of
lactation, Fig. 1). The overall mean for
protein (Table 2) content were similar
to the value obtained by Gnyp et al.
(2006). Chalupa (1984), reported, that
supplemental protein can increase milk
yield by providing more amino acids, by
increasing available energy, and by altering efficiency of utilization of absorbed
nutrients.
Statistical analyses
The data obtained were analyzed statistically using analysis of variance (least
squares) by means of the SPSS 21 packet
software.
The model used for analyzed milk
samples was
Yijk = μ + Ai + Bj + (Ai × Bj) + eij
where:
Yijk – dependent variable;
4.1
3.9
Protein [%]
3.7
3.5
1st lactaon
3.3
2nd lactaon
3.1
3rd lactaon
2.9
2.7
2.5
1
2
3
4
5
6
7
8
9
10
FIGURE 1. Relationships between concentration of protein and the parity of Polish Holstein-Friesian
cows
54
TABLE 2. Relationships between production traits and the parity of Polish Holstein-Friesian cows
Parameter
Parity
1st lactation
2nd lactation
3rd and subsequent lactations
average for the entire herd
1st lactation
2nd lactation
1st lactation
2nd lactation
1st lactation
2nd lactation
Protein (%)
Fat (%)
Fat: protein ratio (-)
Urea (mg/l)
LSM
3.39ab
3.44b
3.47a
3.44
3.88Ab
4.12bc
4.42Ac
4.14
1.14Ab
1.20bc
1.27Ac
1.20
183ABC
267A
264B
243
SEM
0.194
0.276
0.293
0.251
0.497
0.368
0.653
0.550
0.115
0.103
0.182
0.170
8.584
6.611
11.562
11.341
LSM – last square mean; SEM – standard error of the mean; values in the column marked with the same letters
differ significantly A,B,C at P ≤ 0.01, a,b,c at P ≤ 0.05.
The fat content ranged at the herd level
from 3.18 to 4.89%. The highest content
of fat, 4.89%, was found in milk of cows
during 3rd and subsequent lactations; in
the 10th collecting – above 271st day of
lactation (Fig. 2).
The overall mean for fat (Table 2) were
similar to the value obtained by Grodzki
and Brzozowski (2005) and Nogalski
(2006). The higher fat content in the
multiparous cow’s milk could be due
to more intense fat reserve mobilization
5.5
Fat [%]
5
4.5
1st lactaon
2nd lactaon
4
3rd lactaon
3.5
3
1
2
3
4
5
6
7
8
9
10
FIGURE 2. Relationships between concentration of fat and the parity of Polish Holstein-Friesian cows
in early lactation (Berry et al. 2007). In
contrast Borkowska (2005) showed that
the age of cows affect only milk yield.
While, Litwińczuk et al. (2006) reported,
that parity is associated with decrease in
fat content.
The fat: protein ratio ranged at the
herd level from 1.14 to 1.27. The highest ratio, 1.27 was found in milk of cows
during 3rd and subsequent lactations
(Table 2). The optimum fat: protein ratio
is 1.2–1.4. Lower values are likely to lead
to subclinical rumen acidosis which can
interfere with reproductive performance
of cows. The fat: protein ratio higher
than 1.4 signals energy deficit and subclinical ketosis (Pogorzelska et al. 2004).
Toni et al. (2011), reported that analyses
of milk components in early postpartum
(6–9 days in milk), particularly the ratio
of fat: protein is a valuable indicator of
lipomobilization and the negative energy
balance status in post partum cows.
The urea content ranged at the herd
level from 183 to 267 mg/l. The highest content of urea, 267 mg/l, was
found in milk of cows during 2nd lactation (Table 2). It significantly differed
from LSM in cows during 1st lactation.
Godden et al. (2001) reported significant
differences between lactations, also with
the lowest concentrations of urea in cows
in the 1st lactation. The overall mean for
urea were similar to the value obtained
by Sawa et al. (2010) and Slósarz (2011),
who reported a mean for urea of 260
mg/l (optimal range of 250 to 270 mg/l).
However, lower values were reported
by other researchers. In contrast OstenSacken (1999) found, that the lower concentration of urea in cow’s milk is associated with a lack of metabolic burden,
associated with a history of lactations,
55
and therefore the level below to 200 mg/l
is satisfactory for primiparous cows.
Milk urea concentration can be used as
a tool to monitor protein feeding efficiency and dietary protein-energy ratio
in dairy cows (Hof et al. 1997).
CONCLUSION
Milk production traits varies significantly with the age of cows. Hence,
researchers should consider monitoring
for this variable as potential cofounder
when exploring the relationship between
urea, protein, fat content in milk and
nutritional management for meet the
production requirements of cows.
Acknowledgement
Researches was supported by National
Science Center and realized within
the project NN 311 55 8840 entitled
“Relationship between concentration
of bioactive substances in milk during
standard lactation and blood biochemical parameters of high yielding Polish
Holstein-Friesian cow’s”.
REFERENCES
BERRY D.P., BUCKLEY F., DIPLOM P., 2007:
Body condition score and live weight effects
on milk production in Irish Holstein-Friesian
dairy cows. Anim. 1 (9): 1351–1359.
BORKOWSKA D., 2005: Użytkowanie mleczne.
In: Hodowla i użytkowanie bydła. Praca zbiorowa pod red. Litwińczuka i Szulca. Państwowe
Wyd. Rolnicze i Leśne, Warszawa: 97–106.
CHALUPA W., 1984: Discussion of protein symposium. J. Dairy Sci. 67: 1134–1146.
GNYP J., KOWALSKI P., TIETZE M., 2006:
Wydajność mleka krów, jego skład i jakość
cytologiczna w zależności od niektórych czynników środowiskowych. Ann. Universe. Maria
Curie-Skłodowska 24 (3): 17–26.
56
GODDEN S.M., LISSEMORE K.D., KELTON
D.F., LESLIE K.E., WALTON J.S., LUMSDEN
J.H. 2001: Relationships between milk urea
concentrations and nutritional management,
production, and economic variables in Ontario
dairy herds. J. Dairy Sci. 84: 1128–1139.
GRODZKI H., BRZOZOWSKI P., 2005:
Hodowla i użytkowanie bydła. (In:) Hodowla
i użytkowanie zwierząt gospodarskich. Ed.
H. Grodzki. Wydawnictwo SGGW, Warszawa:
11–17, 23, 37–42.
HOF G., VERVOORN M.D., LENAERS P.J.,
TAMMING S., 1997: Milk urea nitrogen as
a tool to monitor the protein nutrition of dairy
cows. J. Dairy Sci. 80: 3333–3340.
JANUŚ E., 2008: Podstawowe wskaźniki płodności krów i ich związek z wydajnością. Hodowca Bydła 11: 28–37.
KIDA K., 2003: Relationships of metabolic profiles to milk production and feeding in dairy
cows. J. Vet. Med. Sci. 65 (6): 671–677.
KOWALSKI Z.M., STRZETELSKI J.A., NIWIŃSKA B. NOWAK W., PAJĄK J., SZYSZKOWSKA A., 2008: Standardowe metody
oznaczania rozkładu białka pasz w przewodzie
pokarmowym zwierząt przeżuwających. Wiad.
Zoot. 44 (4): 53–58.
at ecological and conventional farms. Treaties
and Monographs. Warsaw University of Life
Sciences – SGGW, Warsaw.
LITWIŃCZUK A., BARŁOWSKA J., KRÓL J.,
SAWICKA W., 2006: Porównanie składu
chemicznego i zawartości mocznika w mleku
u krów czarno-białych i simentalskich z okresu
żywienia letniego i zimowego. Ann. Universe.
Maria Curie-Skłodowska 24 (10): 67–72.
MINAKOWSKI D., 2006: Żywienie krów
w aspekcie wymagań produkcji mleka wysokiej jakości. Hodowca Bydła 3: 8–11.
NAŁĘCZ-TARWACKA T., 2006: Effect of selected factors on the functional component
content of milk fat in dairy cows. Treaties
and Monographs, Treaties and Monographs.
Warsaw University of Life Sciences – SGGW,
Warsaw.
NOGALSKI Z., 2006: Zależność między płodnością i mlecznością a niektórymi cechami budowy krów. Rocz. Nauk. Polskiego Tow. Zoot.
2 (4): 57–66.
OSTEN-SACKEN A., 1999: Oznaczanie poziomu
mocznika w mleku – nowy parametr informacyjny dla hodowcy. Przeg. Hodowla. 6: 5–8.
PIŁAT J., 2006: Potrzeby pokarmowe bydła. (In:)
Żywienie bydła. Wydawnictwo Uczelniane
Akademii Techniczno-Rolniczej, Bydgoszcz:
54–69.
POGORZELSKA J., JASTRZEBSKI M., SZAREK J., 2004: Wpływ wybranych czynników
na kształtowanie sie stosunku białko–tłuszcz
w mleku krów pierwiastek o wysokim udziale
genów rasy HF. Zesz. Nauk. Przegl. Hodowla.
72 (1): 217–225.
PUPPEL K., NAŁĘCZ-TARWACKA T., KUCZYŃSKA B., GOŁĘBIEWSKI M., KORDYASZ M., GRODZKI H., 2012: The age of
cows as a factor shaping the antioxidant level
during a nutritional experiment with fish oil
and linseed supplementation for increasing the
antioxidant value of milk. J. Sci. Food Agric.
92: 2494–2499.
SAWA A., BOGUCKI M., JANKOWSKA M.,
KRĘŻEK-CZOPEK S., 2010: Wpływ wybranych czynników na udział prób mleka
o określonej zawartości białka i mocznika.
Acta Scient. Polon. 9 (3): 57–64.
SLÓSARZ J., 2011: Analiza żywienia. (In:) Metody chowu i hodowli bydła. Wydawnictwo
SGGW, Warszawa: 327–329.
TONI F., VINCENTI L., GRIGOLETTO L., RICCI A., SCHUKKEN Y.H., 2011: Early lactation
ratio of fat and protein percentage in milk is
associated with health, milk production, and
survival. J. Dairy Sci. 94 (4): 1772–1783.
Streszczenie: Kolejność laktacji krów rasy PHF
jako czynnik kształtujący poziom cech użytkowych
mleka w intensywnym systemie produkcji. Celem
badania było oszacowanie zależności między
zawartościami białka, tłuszczu, oraz mocznika
w zależności w od kolejności laktacji. Badaniami
objęto 50 krów rasy polskiej holsztyńsko-fryzyjskiej. Za pomocą spektrofotometrii w podczerwieni FTIR oznaczono koncentrację poszczególnych składników mleka. W pracy wykazano
zróżnicowane poziomy składników użytkowych
mleka w kolejnych laktacjach. Największą zawartość białka, 3,87%, stwierdzono w mleku
krów w okresie 3. laktacji, w 10. pobraniu (powyżej 271. dnia laktacji). Zawartość tłuszczu wahała
się na poziomie od 3,18 do 4,89%, najwyższy poziom wykazano w mleku krów będących w 3. laktacji, w 10. pobraniu (powyżej 271. dnia laktacji).
Zawartość mocznika wahała się przedziale od
183 do 267 mg/l na poziomie stada. Cechy produkcyjne mleka różniły się znacznie w zależności
od wieku krów. Sugeruje się, aby w trakcie zarządzania stadami wielkotowarowymi uwzględniać
obserwację zmiennej, jaką jest wiek krów (numer
laktacji), przy bilansowaniu dawek pokarmowych
w poszczególnych grupach produkcyjnych.
Authors’ address:
Beata Kuczyńska
Poland
57
Changes in the concentration of selected minerals in milk and
blood of high-milking cows during lactation
TERESA NAŁĘCZ-TARWACKA1, MARCIN GOŁĘBIEWSKI1,
BEATA KUCZYŃSKA1, KAMILA PUPPEL1, AGATA WÓJCIK1,
MAŁGORZATA BRZEZIŃSKA1, MARTA CZUB1, MICHAŁ BENET2
1
2
Dairy Cooperative “Spomlek”
Abstract: Changes in the concentration of selected
minerals in milk and blood of high-milking cows
during lactation. The aim of this research was the
analysis of the content of calcium, phosphorus and
magnesium in milk and blood of Polish Holstein-Friesian (PHF) milking cows during full lactation.
The research was conducted on 100 PHF cows during two years (50 cows in each year). Samples of
milk and blood were taken in each month of lactation (10 samples) in order to determine minerals
concentration. Additionally, samples of forage were
pooled out. Study revealed that the level of calcium
in the feed is too low, the level of phosphorus – optimal, whereas the content of magnesium exceeds
animal demand. There were significant differences
in the content of calcium, phosphorus and magnesium in the consecutive months of cows’ lactation.
The content of minerals in blood was normal; similar situation was observed in the case of the calcium and phosphorus in milk, with the exception of
milk magnesium concentration, which was too low
and most diversified during the lactation.
Key words: minerals, blood, milk
INTRODUCTION
The concentration of minerals in the
blood can diagnose many diseases, such
as pasture tetany, kidney disease or
postnatal paralysis (Kowalski 2012). In
turn, their content in milk is important in
processing, it is also a direct indicator of
the quality of the raw material and milk
products, and indirect indicator of environmental pollution (Brodziak 2011).
Minerals affect the physical properties of
the milk and the stability of the proteins.
Increasing concentration of magnesium
ions reduces the thermal stability of milk
protein (Jaworski and Kuncewicz 2008).
The amount of calcium determines the
suitability of milk for cheese production
and the magnesium participates in the
construction and activation of enzymes
(Król et al. 2006, Kuczyńska 2011).
According to Soszka (2012), there are
numerous papers on the mineral nutrition
of dairy cows. Few, however, is a work
depicting the interrelationships between
minerals. Most balanced minerals are
calcium and phosphorus, less magnesium. Appropriate calcium to phosphorus
ratio is very important in the prevention
of metabolic diseases, which often occurs
in dairy herds. Mineral content in milk
is variable and depends on many factors (genetic and environmental) (Dymnicka 1998). According to Jaworski and
Kuncewicz (2008), skimmed milk has
a mineral content as follows (in mg per
60
T. Nałęcz-Tarwacka et al.
100 cm3): Ca – 100–140, P – 75–110 and
Mg – 75–110.
The aim of this research was to analyze the mineral content in the milk and
blood of high-yielding cows during full
lactation and to determine the relationship between them.
The experiment was conducted at the
Agricultural Experimental Farm at
Wilanów-Obory.
Cows were kept in free-stall system
and were fed Total Mixed Ration (TMR)
adapted to milk performance. TMR
included: corn silage, hay silage, alfalfa
hay silage, corn silage, straw and ration
appropriate for the technology group.
The organoleptic evaluation confirmed
good feed quality. Feeds have a pleasant smell, the right color, hay and silage
well preserved. The composition of the
rations is presented in Table 1.
TABLE 1. Daily ration for experimental cows (kg)
Feeds
Corn silage
Grass silage
Alfalfa haylage
Corn grain silage
Concentrate
Straw
TMR-1
28
–
8.5
5.8
7.76
–
TMR-2
23
–
10
4.4
5.1
0.7
TMR-3
20
–
15
1
2.2
1
TMR-1 was prepared for cows with
daily milk yield of 39 kg, TMR-2 for cows
with a capacity of 28 kg, while TRM-3
for cows with a yield of 18 kg of milk.
Total mixed rations were supplemented
with tray elements and vitamins according to cows requirements. The research
was conducted on 100 PHF cows during
two years (50 cows in each year). Samples of milk and blood were taken (at the
same day) in each month of lactation (10
samples) in order to determine minerals
concentration. Additionally, samples of
forage were pooled out.
Milk samples were collected in
accordance with the requirements of
PN-EN ISO 707:208 from the evening
milking (250 ml) into sterile plastic
containers containing Mlekostat CC preservative. The samples were transported
to the Laboratory Milk Evaluation at the
Department of Animal Breeding.
Blood was collected from the tail vein.
The sample containing 1 ml of blood
and the preservative was transported to
the Laboratory of the Veterinary Medicine Faculty. Blood minerals (calcium,
phosphorus and magnesium) were determined by biochemistry analyzer BT-200
(Cormay).
The milk samples minerals were determined test strips by REFLEKTOQUANT
Merck.
Statistical analysis were performed
using IBM SPSS 21.0 statistical package.
To estimate the impact of the analyzed
factors on minerals blood and milk concentration two-way analysis of variance
was used (GLM procedure) by following
model:
Yijk = μ + Ri + Pj + (R × P)ij + eijk
where:
Yijk – variable;
μ – average general;
Ri – influence of year, i = 1, 2;
Pj – the effect of the j lactation month,
j = 1 , 2, 3, ..., 10;
(R × P)ij – the effect of the lactation
month and year interaction;
eijk – random error.
Changes in the concentration of selected minerals in milk and blood of high-milking cows...
To determine the relationship between
the minerals in the blood and milk, and
between minerals and other constituents
of milk Pearson correlation was calculated.
61
around 74.64–86.13%. This indicates
inadequate cover of the animals needs.
The coverage ratio for phosphorus
was lowest in cows with the lowest productivity. Cows fed TMR-1, producing
40 kg of milk per day, had covered 114%
of their requirements. Analyzing the
values shown in Table 5 it can be seen
that the animals magnesium supply was
above the norm and ranges between 128
and 132%.
Table 2 presents a comparison of the
demand and minerals intake of cows
depending on their daily performance. It
contains information on the coverage of
the daily requirement of the animals.
Comparing calcium intake and animals requirements, it was observed,
that the requirement coverage fluctuates
Mineral content in the blood
Figure 1 presents the amount of calcium
in the blood of cows during the 10 consecutive months of lactation. The results
TABLE 2. Minerals requirement and consumption
Milk
performance
(kg)
Ca
111
138
163
Mg
23.5
29.5
37
Ca
95.6
103
136
Consumption
(g)
P
55
77.6
101
concentraƟon (mg·dl–1)
17.5
27.5
40
Requirement
(g)
P
60.5
75.5
88.5
lactaƟon months
FIGURE 1. The blood calcium content of the cows
Mg
31.1
38.2
47.4
Coverage of requirement
(%)
Ca
P
Mg
86.13
90.91 132.17
74.64 102.78 129.42
83.44 114.12 128.05
62
pancreas dysfunction. However, clinical hypocalcemia, due to a decrease in
blood Ca levels below 5 mg·dl–1, is the
main cause of post partum retention –
a frequent problem of many breeders.
The obtained results indicate that the
animals were not at risk due to the Ca
content in the blood.
Figure 2 presents the content of phosphorus in the blood of cows during 10
consecutive months of lactation. The
results obtained in the first and second
year of experience fluctuated between
5.309 and 7.005 mg·dl–1. There were
a statistically significant differences in
the content of P in the blood between
successive months of the first (P ≤ 0.01)
and second (P ≤ 0.05) year of the study.
Statistically significant differences in the
contents of the P in the blood between
the years stated in the following months
of lactation: fourth, seventh and tenth
(P ≤ 0.01), as well as the fifth and eighth
(P ≤ 0.05). Winnicka (2011) stated that
values are correct for cattle at a level of
5.6–6.5 mg·dl–1.
in both the first and second year of the
experiment were in the range of 7.777
to 10.783 mg·dl–1. A statistically significant difference in the blood Ca content
between lactation months (P ≤ 0.01) and
the years, was observed. The reference
values given by Winnicka (2011) range
from 9.00 to 12.10 mg·dl–1.
In both the first and second year of
experience in the seventh month of
lactation, the lowest content of Ca was
found in the blood, 9.547 mg·dl–1 in the
first year and 7.777 mg·dl–1 in the second
year, respectively. However, in the eighth
month of lactation blood contained
the highest content of Ca. In the first
year of the experiment observed value
10.783 mg·dl–1, and the second 10.684
mg·dl–1, respectively. Study reviled that
the Ca content in the blood of cows was
normal, except for the its concentration
in the seventh month (7.777 mg·dl–1) in
the second year of the study. According to Winnicka (2011), analysis of the
Ca content in the blood helps diagnose
kidney malfunction, parathyroid and
lactaƟon months
FIGURE 2. The content of phosphorus in the blood of cows
tion. The results obtained within two
years of research range from 1.769 to
2.555 mg·dl–1. There was a statistically
significant differences in the content of
magnesium in the blood between following months of lactation: first, second,
fourth, fifth, eighth, ninth and tenth
(P ≤ 0.01) and sixth (p ≤ 0.05) and the
years. The reference values given by
Winnicka (2011) ranged from 1.90 to
3.00 mg·dl–1.
The lowest concentration of the Mg
was observed in the first year of the
study reported in the eighth month of
lactation (1.769 mg·dl–1), while in the
second year of the study the lowest value
was reported in the seventh month of lactation (2.023 mg·dl–1). The highest concentration of Mg in the first year of the
experiment was 2.538 mg·dl–1 and was
recorded in the third month of lactation,
and in eight months (2.555 mg·dl–1) in
the second year of the study. The results
reviled that the Mg content in the blood
of analyzed cows was physiologically
normal. Symptoms of tetany may occur
The lowest phosphorous content in the
first year of the study was found in the first
month of lactation, it was 5.309 mg·dl–1,
while in the second year – the lowest
value of 5.575 mg·dl–1 was observed
in the ninth month. Study revealed that
the highest content of P was observed in
fourth month of the first year of the study
and the seventh month the second year
(7.005 and 6.556 mg·dl–1, respectively).
Researches confirmed that P content in
the blood was physiologically normal,
with the exception of the level of 5.309
mg·dl–1 observed in the first year of the
study. Winnicka (2011) reported the
content of phosphorus in the blood can
be helpful in the diagnosis of hyperparathyroidism and thyroid dysfunction.
Jamroz (2001) indicates that P level it is
not accurate source of information, since
the element concentration in the blood is
dependent on the concentration of Mn,
Mg and Cu in the feed.
Figure 3 presents the concentration
of magnesium in the blood of cows
during 10 consecutive months of lacta-
63
lactaƟon months
FIGURE 3. The content of magnesium in the blood of the cows
64
when magnesium concentrations fall
below 1.7 mg·dl–1.
To conclude that the studied mineral
content in the blood of the test animals
were ranged within normal limits (with
just a few exeptions). Low feed coverage
for Ca was not reflected in its concentration in the blood.
Mineral content in the milk of cows
Figure 4 presents the calcium content
in milk of cows during 10 consecutive
month of lactation.
The results of milk Ca concentration
obtained in the experiment of both the
first and second year of the experiment
are in the range of 598 to 1096.6 mg·l–1.
There were a statistically significant
differences in Ca concentration in
the milk between successive months
(P ≤ 0.01) and between successive years.
According to Gabryszczuk et al. (2010),
the calcium content in milk varies from
600 to 1200 mg·l–1. Research conducted
by Kuczyńska (2011) indicated that
contents of the Ca in milk was aver-
aging 1020 mg·l–1. According to the
researchers conducted by Krzyżewski
et al. (2009), the content of calcium
in 100 g of milk was 119 mg. Similar
results were presented by Kuczyńska
et al. (2009). Lower Ca concentration
of PHF breed cows reported Brodziak
et al. (2011) averaging 919.0 mg·dm–3.
Black and White breed variety cows
milk was characterized by the lowest Ca
content (108.6 mg%), and the highest
was reported in the Simmental (138.2
mg%), according to Litwińczuk (2004).
According to the research of Mountain
(2002), the calcium content of milk
in winter and was higher than in the
summer (1.12 vs 1.05 g·kg–1, respectively). Milk from different regions of
the Poland characterized by the difference in calcium and magnesium, which
is reported in the Górska (2002) study.
In the first year of the experiment the
lowest content of the element in the milk
was recorded in the seventh month of
lactation and it was 614.5 mg·l–1, while
the highest in the eighth –989.7 mg·l–1.
lactaƟon months
FIGURE 4. The content of calcium in milk of trial cows
exception of the first month. Kuczyńska
(2011), reported that reference value
of phosphorus in milk ranges between
750 and 1100 mg·l–1, and the results of
her study reviled that P content in milk
originated from intensive and organic
farms fluctuated at 807 and 824 mg·l–1
respectively. According to the research
Krzyżewski et al. (2009), the phosphorus content in milk was 93 mg·100 g–1.
Research of Litwińczuk (2004) confirmed that milk of Black and White
breed variety cows contained the lowest
phosphorus concentration (80.8 mg%),
and Simmentals’ milk was the richest in
P (108.3 mg%).
The lowest content of the P in the first
year of the experiment was 348.8 mg·l–1
and was recorded in the eighth month
of lactation. In the second year of the
experiment the lowest content was 542.1
mg·l–1, and was observed in tenth month
In the second year of the experiment the
lowest calcium content in milk was characterized by milk from the fourth month
of lactation and was 598.0 mg·l–1, while
the highest in the second month of lactation – 1096.6 mg·l–1.
Drop in the content of Ca in milk in
the seventh lactation month was probably the result of its lowest concentration
in the blood of experimental animals.
Figure 5 shows the phosphorus content
in the milk of cows during lactation.
The results in both the first and second
year of the study are in the range of from
348.8 to 1024.6 mg·l–1. There was a statistically significant differences in the
content of P in the milk between successive months (P ≤ 0.01) and between
studied years. Statistically significant
differences in the content of the P in the
milk between the years stated in each
month of lactation (P ≤ 0.01) with the
65
lactaƟon months
FIGURE 5. Phosphorus content in the milk of trial cows
66
lactaƟon months
FIGURE 6. Magnesium content in the milk of trial cows
of lactation. In both the first and second
year of study in the first month of lactation the maximum P content in milk was
observed (863.3 and 1024.6 mg·l–1 in the
first and year respectively). Study reviled
that phosphorus content was decreasing with consecutive lactation months.
Figure 6 presents the magnesium content
in the milk of cows during 10 consecutive months of lactation.
year of the experiment were in the range
of 45.69 to 111.33 mg·l–1. There was
a statistically significant differences in
Ca concentration in the blood between
successive months (P ≤ 0.01) and studied years. Statistically significant differences in the content of the Mg in the
milk was stated between first, second,
third, fourth, seventh and eighth month,
however, however, the biggest differences were observed between the fifth
and ninth month. The reference values
given by Kuczyńska (2011) range from
120 to 134 mg∙l–1. In a study conducted
by Kuczyńska (2011) the magnesium
content in milk from conventional farms
averaged 112 mg·l–1 and organic at 107
mg·l–1. Studies of Brodziak et al. (2011)
reviled that the Mg content in milk averaged 127.9 mg·dm–3, while Krzyżewski
(2009) reported the average Mg content
of 13 mg per 100 g of milk. Mountain
research (2002) confirmed higher magnesium content in milk harvested in
winter (91.38 mg·kg–1) than in summer
(85.13 mg·kg–1). In the experiment,
the maximum magnesium content of
the milk was observed in eight months
and ninth month of lactation, 111.33
mg·l–1 in the first and 107.07 mg·l–1 in
the first and second year of lactation,
respectively. The lowest values milk
magnesium content were reported in
67
raƟo
lactaƟon months
FIGURE 7. The calcium to phosphorus ratio in milk cows during 10 consecutive months of lactation
the third and fourth month of lactation
(61.71 and 45.69 mg·l–1, for the first and
second year respectively). Our study
reviled that the magnesium content in
the milk of cows are normal in the early
and late lactation, and from the second
to the seventh month of lactation were
obtained lower values than in the studies Górska (2002) and Kuczyńska
(2011). Figure 7 presents the calcium
to phosphorus ratio in milk consecutive
months.
year of the experiment ranged between
0.974 to 2.896. A statistically significant
difference in ratio of calcium to phosphorus in milk between successive months
(P ≤ 0.01) and years were reported. Significant differences in the Ca : P in milk
were stated in the third, fourth, fifth,
sixth, seventh, eighth and ninth month.
In the experiment, the high values of
Ca : P was reported in the eighth and
second month of lactation, in the first
and second year respectively (2.896 (at
first) and 1.488 (in the second year of the
experiment).The lowest ratio of Ca and
P in the first year of experience characterized by the milk from the first month
of lactation (1.191), while in the second
year of milk from the fourth month of
a characterized by the lowest Ca : P
– 0.974. According to Kłobukowski and
Kozikowski (2008), the most advantageous relation between Ca and P should
be established at 1.2 : 1. Kuczyńska
(2011) studies reported that Ca : P in
milk ranged between 1.2 and 1.3. The
study results obtained in the second
experiment are similar to those reported
in the literature.
Table 3 presents the correlation coefficients between the minerals contained in
milk and its concentration in the blood.
Analysis of these values, reviled that
there is a negative, highly significant
relationship between the content of magnesium in the blood and the content of
calcium in milk (–0.116) and the Ca to P
ratio. Also negative correlation between
the content of phosphorus in the blood
and phosphorus in milk was reported.
However, the relationship between the
content of phosphorus in the blood and
68
TABLE 3. Correlation between the mineral components in the milk and blood
Chemical element
Ca
milk
Mg
milk
P
milk
r
Mg
blood
P
blood
Mg
milk
P
milk
Ca : P
milk
Ca
blood
Mg
blood
P
blood
1
0.334**
0.068*
0.515**
0.006
–0.116**
0.071
0.000
0.045
0.000
0.884
0.003
0.074
866
866
866
642
642
642
1
significance P ≤
n
866
r
0.334
significance P ≤
0.000
n
866
**
0.016
0.174
–0.019
–0.077
0.023
0.639
0.000
0.639
0.051
0.559
642
642
642
–0.066
0.078
0.096
0.049
**
866
866
866
r
*
0.068
0.016
1
–0.725
significance P ≤
0.045
0.639
**
0.000
*
–0.079*
0.045
n
866
866
866
866
642
642
642
r
0.515**
0.174**
–0.725**
1
0.067
–0.150**
0.142**
0.000
0.000
0.000
0.091
0.000
0.000
Ca : P
significance P ≤
milk
n
Ca
blood
Ca
milk
866
866
866
866
642
642
642
r
0.006
–0.019
–0.066
0.067
1
0.154**
0.229**
significance P ≤
0.884
0.639
0.096
0.091
0.000
0.000
n
642
642
642
642
642
642
642
r
–0.116**
–0.077
0.078*
–0.150**
0.154**
1
0.114**
significance P ≤
0.003
0.051
0.049
0.000
0.000
n
642
642
642
642
642
0.004
642
642
r
0.071
0.023
–0.079
0.142
0.229
0.114
significance P ≤
0.074
0.559
0.045
0.000
0.000
0.004
n
642
642
642
642
642
642
*
**
**
**
1
642
r – Pearson’s correlation coefficient; n – number;
* correlation significant at the 0.05 level; ** correlation significant at the 0.01 level.
the Ca to P ratio is positive and highly
significant.
CONCLUSIONS
Study brought to following conclusions:
– calcium in the blood and milk during
lactation was physiologically normal,
except for the seventh month of the
second year of the study (blood) and
the fourth month of the second year of
the study (milk);
– phosphorus level in the blood in full
lactation period was physiologically
normal except for the first and the
seventh month of the first year of the
study and the ninth of the second year
of the study, while the content of the
milk showed a declining trend during
lactation;
– magnesium concentration in the blood
during a full lactation was physiologically normal with the exception of the
eighth month of the first year of the
study, while the milk was lower than
the reference values (except the first
and the tenth month of lactation);
– there were significant correlation
between blood and milk minerals.
In summary, the properly fed an managed high-milk yielding cows at various
stages of the lactation may suffer from
slight calcium, phosphorus and magnesium deficiency what is reflected in blood
and milk tests.
Acknowledgements
The research was carried out under a the
National Science Centre’s grant entitled
“The content of biologically active components in milk during lactation full in
conjunction with high blood biochemical parameters cows PHF” (NCN grant
N N311 558840), who was conducted by
the Warsaw University of Life Sciences
– SGGW, Cattle Breeding Division.
REFERENCES
BRODZIAK A., LITWIŃCZUK A., KĘDZIERSKA-MATYSEK M., KRÓL J., 2011: Zawartość wybranych makro- i mikroelementów
w mleku krów różnych ras i serwatce podpuszczkowej. Ochr. Środ. i Zas. Natur. 48:
467–474.
DYMNICKA M., 1998: Wpływ żywienia krów
oraz wielkości produkcji mleka, stadium laktacji i kolejnych laktacji na zawartość wybranych wskaźników biochemicznych we krwi.
Fundacja „Rozwój SGGW”, Warszawa: 8–11,
25–32.
GABRYSZCZUK M., SŁONIEWSKI K, METERA E., SAKOWSKI T., 2010: Content of mineral elements in milk and hair of cows from
organic farm. J. Elem. 15 (2): 259–267.
GÓRSKA A., 2002: Jakość mleka towarowego
w regionie południowego Podlasie z uwzględnieniem wpływu niektórych czynników wa-
69
runkujących. Rozprawa Naukowa nr 67, Akademia Podlaska Siedlce: 48–54.
JAMROZ D., 2001: Składniki mineralne. In:
Żywienie zwierząt i paszoznawstwo. Fizjologiczne i biochemiczne podstawy żywienia
zwierząt. D. Jamroz (Ed.). Wydawnictwo Naukowe PWN, Warszawa: 61–91.
JAWORSKI J., KUNCEWICZ A., 2008: Składniki mineralne mleka. (In:) Mleczarstwo. S. Ziajka (Ed.). Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego Olsztyn: 82–84.
KŁOBUKOWSKI J., KOZIKOWSKI W., 2008:
Składniki mineralne. (In:) Mleczarstwo.
S. Ziajka (Ed.). Wydawnictwo Uniwersytetu
Warmińsko-Mazurskiego Olsztyn: 118–122.
KOWALSKI Z.M., 2012: Uwaga na subkliniczną hipokalcemię u krów mlecznych w okresie
okołoporodowym. Wet. w Terenie 3: 55–57.
KRÓL J., LITWIŃCZUK Z., BARŁOWSKA J.,
KĘDZIERSKA-MATYSEK M., 2006: A content of macro- i microelements in milk of
Black-White and Simentals cows troughout the
summer and winter feeding seasons. Pol. J. Environ. Stud. 15 (2A): 395–397.
KRZYŻEWSKI J., STRZAŁKOWSKA N.,
JÓŹWIK A., BAGNICKA E., HORBAŃCZUK J.O., 2009: Nutritive value and functional properties of goat milk. (In:) Proceedings
of the international conference on Improvement
of quality of animal products obtained in sustainable production systems with special reference to bioactive components and their benefit
for human health. Jastrzębiec: 41–47.
KUCZYŃSKA B., 2011: Składniki bioaktywne
i parametry technologiczne mleka produkowanego w gospodarstwach ekologicznych i konwencjonalnych. Wydawnictwo SGGW, Warszawa: 25–26, 56–57.
KUCZYŃSKA B., PUPPEL K., NAŁĘCZ-TARWACKA T., NIŻNIKOWSKI R., ŁOJEK J.,
BEYGA K., 2009: Wartość odżywcza mleka
i siary pochodzących od różnych gatunków
zwierząt. Przeg. Hod. 11: 12–17.
LITWIŃCZUK Z., 2004: Skład chemiczny mleka. (In:) Surowce zwierzęce. Ocena i wykorzystanie. Z. Litwińczuk (Ed.). PWRiL, Warszawa: 72–73.
SOSZKA M., 2012: Mieszanki witaminowo-mineralne w żywieniu bydła. Bydło 9: 18–23.
70
WINNICKA A., 2011: Wartości referencyjne
podstawowych badań laboratoryjnych w weterynarii. Wydawnictwo SGGW, Warszawa:
52–53, 55–56, 64–65, 66–67, 71–72.
Streszczenie: Zmiany zawartości wybranych
składników mineralnych w mleku i krwi wysokomlecznych krów w okresie pełnej laktacji. Celem
badań była analiza zawartości wapnia, fosforu
oraz magnezu w mleku i we krwi wysokomlecznych krów w okresie pełnej laktacji. Badania przeprowadzono na 100 krowach rasy PHF w okresie
dwóch lat (50 krów w każdym roku). Próbki mleka i krwi pobierano w każdym miesiącu laktacji
(10 pobrań) i określano w nich zawartość składników mineralnych. Dodatkowo pobrano próby
pasz. Wykazano, że poziom wapnia w dawkach
jest zbyt niski, poziom fosforu optymalny, a zawartość magnezu w dawkach przekraczała zapotrzebowanie zwierząt. Stwierdzono statystycznie
istotne różnice w zawartości Ca, P i Mg w poszczególnych miesiącach laktacji krów. Zawartość
składników mineralnych we krwi była w normie,
podobną sytuację zaobserwowano w przypadku
zawartości wapnia oraz fosforu w mleku. Wyjątek stanowi stężenie magnezu w mleku, które jest
zbyt niskie i najbardziej zróżnicowane w okresie
laktacji.
Authors’ address:
Teresa Nałęcz-Tarwacka
Poland
e-mail: teresa_nalecz_tarwacka @sggw.pl
Analysis of results assessment of growth of Charolais beef cattle
in Poland
TOMASZ PRZYSUCHA, MARCIN GOŁĘBIEWSKI,
HENRYK GRODZKI, KAROLINA WNĘK, JAN SLÓSARZ,
MAŁGORZATA KUNOWSKA-SLÓSARZ, PIOTR TOKARSKI
Abstract: Analysis of results assessment of growth
of Charolais beef cattle in Poland. The aim of
the study was to assess the utility of selected results of the French Charolais breed with respect
to their compliance with the goal of racial breeding and standards adopted by the Polish Association of Breeders and Producers of Beef Cattle
(PABPBC). The subject of the analysis were recording results of the French Charolais beef cattle
breed in Poland. The study was based on data for
the years 2002–2013 of PABPBC and the National
Center of Animal Breeding (NCAB) for 1996–
2001. The data set included: n – the number of
animals tested, min. – minimum values in the studied traits, max. – maximum value of the selected
features, average – average values of the analyzed
traits, SD – standard deviation. Evaluated properties are: average weight of cows (kg), the average
body weight of calves after birth (kg), the average
daily gains for age 210 days (g), the average body
weight of calves at the age of 210 days (kg), the average milk yield (kg), the terms of cows and heifers
calving aptitude, the distribution of the population
according to the order of calving cows. One can
observe a gradual decline in the share of Charolais
breed in national beef cattle population, also shows
a significant decrease in the number of crossbreds
with Charolais breed. The average weight of cows
in 2005–2006 amounting to 559.4 and 570.2 kg
meet the standards for breeding of cows entered in
the initial part of the herd book, which define the
minimum weight of Charolais cows after first calving as 550 kg. The average weight at birth of heifer
calves in each year assessment was similar, but
after 2008 began more than 40 kg. In purebred bull
calves was seen a systematic increase in the average birth weight. The difference in birth weights
between heifers and bulls ranged from 1 kg in 1999
to 3.6 kg in 2012. High average daily weight gains
of bulls to 210 days of age, at short extra supplementary fattening period of about one month allow to export the animals weighing about 300 kg
at a good price. The average daily gains of heifers
(550–560 g), guarantee obtaining at 15 months of
age body weight allowing the commencement of
breeding. From 30.4 to 47.8% Charolais cows in
recent years delivered in the relevant period.
Key words: beef cattle, Charolais, beef cattle recording
INTRODUCTION
Twenty years the Programme of Beef
Cattle Breeding Development in Poland
finished in 2014 (Jasiorowski et al. 1996).
Due to the sparse pure-bred female
population is difficult to talk about own
national breeding program. Therefore, the
maintenance of high standards of breed
is the main task of PABPBC. Its implementation is, inter alia, beef recording
conducted in cattle herds. The aim of beef
recording is, in addition to collecting data
on the relevant parameters of herd repro-
72
T. Przysucha et al.
duction, potential growth and fattening
traits and maternal characteristics, on the
basis of which herds are improving by use
of information processed in the current
breeding advisory service to farmers, in
order to improve the economic performance of stocks and the implementation of
a breeding program in the herd breed and
use this information in analytical studies
on beef cattle breeding and research work
and publications.
The weight of a cow by its relationship
with a caliber, has a direct impact on the
course of calving (more cows tend to have
a larger area of the pelvis channel) and
body weight of calf, which, along with
nutrition, has a significant impact on daily
gains of calves during rearing. The weight
of the calf at birth has an influence not
only on the course of calving, but also on
the subsequent results of its rearing. Daily
gains of calves to 210 days of age determine their body weight at weaning, this
in turn has an impact on the profit from
the sale of reared calves (mainly bulls),
or the cost of winter feeding of heifers
for breeding, which must receive the
required, minimum weight at the moment
their mating at the age of 15 months. Calving season has a direct impact on the cost
of maintaining the basic herd (maximum
utilization of the entire grazing season)
and the quality of breeding calves (health,
growth rate). Distribution of cows calving
aptitude in order of calving tells us about
the longevity of cows, which particularly
in the herds of beef cattle is one of the
main factors affecting the reduction of
costs of the herd.
The aim of the study was to assess the
utility of selected results of the French
Charolais breed with respect to their
compliance with the goal of breeding
standards adopted by PABPBC. Height
at sacrum for females was 135 cm, and
145 cm for males at maturity and body
weight for females 850 kg, 1300 kg for
males. An important selection factor is to
maintain a high level of milk production
and the exclusion of breeding males with
a tendency to transmit high weight of
calves at birth. Charolais breed in terms
of breeding is an excellent paternal line
to be crossed and this aspect on a par with
good results in pure bred breeding will
be given special attention in the course
of selection work. In the national beef
cattle breeding program there are set out,
inter alia, the following standards for
breeding of cows entered in the Table 1.
TABLE 1. The following standards for breeding of cows (PZHiPBM, 2001–2014)
Breed
LIM CHA SAL HEF AAG SIM PMT WBL BDQ
Min. body weight gain from birth
850 950 870 800 800 900 830 780 950
to 210 day of age (g)
Min. body weight after 1st calving
480 550 500 460 460 530 470 450 550
(kg)
Delivery
easy, taking place by the nature forces, without human assistance
Calves vitality
alive, without body building defects
Evaluation of type and construction
min. 70 points
The degree of massiveness and
good good
sufficient
good
musculature
Colour
in accordance with the breed standard
Analysis of results assessment of growth of Charolais beef cattle in Poland
The subject of the analysis were beef
cattle evaluation results for the French
Charolais breed in Poland. With respect
to their compliance with the goal of
racial breeding and standards adopted by
the Polish Association of Breeders and
Producers of Beef Cattle (PABPBC). The
subject of the analysis were recording results of the French Charolaise beef cattle
breed in Poland. The study was based on
data for the years 2002–2013 of PABPBC
and the National Center of Animal Breeding (NCAB) for 1996–2001. The data
set included: N – the number of animals
tested, min. and minimum values in the
studied traits, max. and maximum value
of the selected features, average – average
values of the analyzed traits, SD – standard deviation. Evaluated properties are:
average weight of cows (kg), the average
body weight of calves after birth (kg), the
average daily gains for age 210 days (g),
the average body weight of calves at the
age of 210 days (kg), the average milk
yield (kg), the terms of cows and heifers
calving aptitude, the distribution of the
population according to the order of calving cows.
The calculation of standardized animal
body weight for given day in its life was
done according to the following formula:
MCS = [(MCB – MCU) / WW] ×
× WS + MCU
where:
MCS – standardized animal body
weight (kg);
MCB – mean body weight of the animal
on the actual weighing (kg);
MCU – actual body weight set for 48
hours at birth (kg);
73
WW – mean age of the animal on the
weighing (days);
WS – standardized age of the animal
(s).
There were calculated the average daily
weight gain of the animal from the day
of birth to 210 days of age, according to
the formula:
PDMC = (MCC – MCP) ×
× 1000 / (WK – WP)
where:
PDMC – mean increase in daily body
weight (g);
MCC – final body weight of the animal
on the weighing day (kg);
MCP – initial body weight of the
animal on the weighing (kg);
WK
– mean age of the animal on the
final weighing (days);
WP
– mean age of the animal on
the initial weighing (days
milk yield in dairy cows – is
expressed in kg of milk per
convention.
The conversion 210 day lactation and is
calculated according to the formula:
WMM210 = (McOds × 1700) / calf age
where:
WMM210 – value of mother milk – milk
yield for 210 day lactation conversion
assuming calf birth weight 35 kg, per
1 kg body weight gain, which drank
10 kg milk a day during the first
3 months, and the remaining months of
8–9 kg a day;
McOds – the actual weight of the calf at
weaning (kg);
calf age – actual age of the calf at the time
of weaning from the mother (days).
74
T. Przysucha et al.
Table 2 presents the quantitative changes
of the female purebred population of
Charolaise cattle in the years 1996–2013.
It should be noted that in 2000–2006 the
data included both cows and heifers, and
since 2007, the data relate only to cows
and excluding heifers. One can observe
a gradual decrease in the breed discussed
in the national cattle population, also
shows a significant decrease in the number
of crossbreds with Charolais breed.
Table 3 shows the mean body weight
of pure bred Charolais cows in the period
in which this trait was evaluated. The
average body weight of cows were much
smaller than the predefined by PABPBC,
according to which the weight of adult
cow of discussed breed should be about
850 kg. Average weight of cows in
2005 amounting to 559.4 and 570.2 kg
meet the standards for breeding of cows
entered in the initial part of the herd
book, which define the minimum weight
of Charolais cows after first calving as
550 kg. It should be noted that the average weight of the cow did not change
significantly over 8 years of evaluation
of this trait, but rather high standard
deviations indicate the wide variety of
cows of the breed body weight. Genotype and weight of the mother cows are
always described among the many factors
involved in normal growth and development of calves. Numerous studies have
TABLE 2. Quantitative changes of the female population of Charolais cattle in Poland*
Beef breed female population
Year
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
pure bred cross bred
3 939
6 063
7 227
8 375
9 085
9 129
9 735
11 768
13 884
17 130
19 597
14 541
17 481
15 435
16 436
16 216
16 724
17 481
4 952
5 772
7 601
8 243
9 468
9 748
8 968
9 382
10 925
11 710
13 100
11 676
12 097
7 711
7 576
7 459
7 070
6 633
total
Charolais
breed
(purebred)
Charolais
breed
(crossbred)
8 891
11 835
14 828
16 618
18 553
18 877
18 703
21 150
24 809
28 840
32 697
26 217
29 578
23 146
24 012
23 675
23 794
24 114
908
1 162
1 427
1 417
1 749
1 821
2 119
2 201
2 890
2 793
3 400
2 512
2 956
2 417
2 538
2 335
2 265
2 253
655
565
1 082
1 118
939
770
885
1 007
1 002
1 057
1 098
983
998
490
340
302
261
248
*From 2007 the list includes only the cows.
Charolais
breed
(purebred +
+ crossbred)
1 563
1 727
2 509
2 535
2 688
2 591
3 004
3 208
3 892
3 850
4 498
3 495
3 954
2 907
2 878
2 637
2 526
2 501
Charolais
breed share
in the
population
17.6
14.6
16.9
15.3
14.5
13.7
16.1
15.2
15.7
13.3
13.8
13.3
13.4
12.6
12.0
11.1
10.6
10.3
75
TABLE 3. Body weight of purebred Charolais cows
Year
N
1999
2000
2001
2002
2003
2004
2005*
2006*
560
846
951
944
1017
1190
302
534
min.
340
400
470
450
480
460
500
400
Cow body weight (kg)
max.
average
1090
648.3
1050
640.8
1050
656.8
890
634.7
910
626.0
940
630.0
680
559.4
770
570.2
SD
108.4
94.3
90.0
81.5
78.8
82.4
45.3
36.2
*Body weight after first calving.
shown that the weight of the cow has
a significant impact on calf birth weight
and daily gains during the rearing (Przysucha et al. 2002abcd, Przysucha et al.
2003). Therefore, the weight of a cow in
adulthood is an important trait to be considered for breeding programs (Andersen
1978, Brown et al. 1989). Breeding goals
for most beef breeds are focused on massive cow with a high caliber.
Tables 4 and 5 how the average natal
weight of calves. The average weight at
birth of heifers in each year assessment
was similar, but after 2008 began more
than 40 kg. In purebred bulls a systematic
increase in the average birth weight was
noticed. The difference in birth weights
between heifers and bulls ranged from
1 kg in 1999 to 3.6 kg in 2012. The birth
weight of calves has a significant effect
TABLE 4. Average body weight of purebred heifers at birth
Year
N
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Average
36
448
497
426
489
582
731
795
832
960
1063
1143
926
1014
896
600
min.
20
17
20
18
25
21
24
20
20
20
20
20
14
16
25
20.6
Body weight (kg)
max.
average
65
39.3
63
38.6
70
39.2
60
37.8
60
38.3
55
37.8
59
37.8
71
39.0
61
39.5
64
40.9
59
40.3
64
40.5
63
41.2
68
41.1
70
42.1
62.4
38.4
SD
6.2
6.1
6.7
5.8
4.8
4.8
4.5
8.0
4.6
6.2
5.3
4.9
5.4
3.0
5.6
5.7
76
T. Przysucha et al.
TABLE 5. Average body of weight purebred bulls at birth
Year
N
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
400
408
435
436
494
590
769
753
826
933
980
1023
953
1004
916
min.
15
19
17
18
27
21
25
27
23
23
26
20
23
25
27
on weaning weight of calves and usually
the calf is heavier at birth the greater the
weight at the time of weaning (Przysucha
et al. 2002abc).
Tables 6 and 7 present data on the average daily gains of heifers and bulls from
Body weight (kg)
max.
average
50
40.3
64
41.1
70
41.1
59
39.5
62
39.9
58
39.1
65
39.7
68
40.7
68
41.7
66
43.1
69
42.4
70
42.6
68
43.4
73
44.7
70
44.9
SD
4.4
6.7
7.8
5.7
5.0
5.1
4.9
5.2
5.0
6.2
5.6
5.8
6.0
6.4
6.2
birth up to 210 days of age. Average daily
gains of heifers evaluated ranged from 897
to 1141 g in various years of assessment.
While the average daily gains of bulls
evaluated (1100 g) exceeded eight times
during the 14 years of the assessment.
TABLE 6. Average daily gains of purebred heifers to 210 days of age
Year
N
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
190
290
166
152
429
426
384
636
900
1040
1038
891
992
897
min.
509
509
527
614
629
561
457
629
1036
700
145
664
421
387
Daily gains (g)
max.
average
1478
896.6
1496
1039.9
1580
1057.2
1571
1059.4
1446
1036.3
1576
1056.5
1465
1049.8
1531
1039.9
1204
1140.9
1793
1019.5
1585
1030.8
1712
1055.1
1861
1114.0
1882
1057.0
SD
187.9
205.4
188.3
140.5
135.3
130.4
116.9
147.1
37.1
182.9
144.0
105.0
141.6
105.6
77
TABLE 7. Average daily gains of purebred bulls to 210 days of age
Year
N
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
157
226
136
147
426
404
385
557
860
988
922
819
955
789
min.
504
505
520
528
540
510
714
759
494
523
309
400
607
427
Analyzing the data presented, it should
be noted the large difference between the
minimum and maximum daily gains in
both heifers and bulls. High average daily
weight gains of bulls to 210 days of age.
at short extra supplementary fattening
period of about one month allow to export
the animals weighing about 300 kg at an
good price. Dobicki (1995) study showed
that the average daily gains of heifers
(550–560 g), guarantee obtaining at 15
months of age body weight allowing the
commencement of breeding.
Table 8 includes the mean body weight
of Charolais breed heifers at the age of
210 days in the different years of assessment. The average weight of heifers
was evaluated 278 kg in 2012 and only
227 kg in 2000.
Table 9 presents the data on body
weight of Charolais bulls at the age of
210 days. The average weight of bulls
evaluated in this age was 241.1 kg in
1999 and 291.9 kg in 2012 (a difference
of more than 50 kg).
Daily gains (g)
max.
average
1597
1054.7
1492
1093.4
1666
1088.3
1485
1120.4
1679
1109.9
1690
1159.5
1520
1145.0
1612
1125.7
1693
1073.1
2010
1118.3
1746
1081.6
1861
1129.3
1879
1146.3
1548
1115.3
SD
199.4
194.7
210.9
140.6
169.0
149.6
126.5
142.8
183.9
180.3
161.1
121.9
49.8
88.1
Table 10 includes the average milk
yield of purebred cows in different years
of assessment. As can be seen from the
following statement, the average milk
yield of cows of the breed was about
2100 kg and has not undergone significant changes in subsequent years. Since
2010 PABPBC stopped evaluation of this
trait because the data presented should be
approached with great caution because
milk yield was calculated based on the
weight gain of calves and as we know in
the herd calves can always be found that
approach to other cows and choke or are
additionally fed by the breeder.
Table 11 contains a summary of the
terms of cows and heifers calving aptitude of analyzed breed in the following
months of the year in 2000–2007. Seasonality in breeding beef herds calving
aptitude is very important. because it
allows more appropriate term of calving to receive in the future a very good
quality breeding material with the least
amount of cost of rearing (maximum
78
T. Przysucha et al.
TABLE 8. Average body weight of purebred heifers at 210 days of age
Year
N
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
206
190
285
175
152
429
426
384
636
900
1040
1038
891
992
887
min.
120
150
152
140
165
168
151
116
178
140
120
173
178
125
120
Body weight (kg)
max.
average
394
231.1
346
227.0
349
257.4
376
259.6
372
262.6
348
255.1
375
260.1
351
259.4
380
256.7
393
245.5
400
256.3
412
260.4
389
265.1
396
278.0
410
259.6
SD
47.0
38.8
41.8
43.6
31.2
29.8
28.1
30.6
33.7
43.1
43.5
34.1
32.0
24.6
23.4
TABLE 9. Average body weight of purebred bulls at 210 days of age
Year
N
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
206
156
222
139
148
426
404
385
557
860
988
922
819
940
901
min.
120
174
152
141
150
144
160
180
185
55
155
110
120
145
130
utilization of pastures). Many authors
believe (Dobicki 1996, Jasiorowski
1999, Jasiorowski and Przysucha 2004),
that the period of mating and the resulting of calving aptitude time should not
be longer than 2–3 months. Beef cows,
Body weight (kg)
max.
average
394
241.1
375
263.6
347
269.5
396
270.0
362
277.8
396
272.1
400
283.6
357
269.0
440
275.3
425
267.3
450
275.1
452
271.7
440
282.9
450
291.9
420
280.2
SD
37.0
42.8
40.4
46.7
31.5
37.2
32.0
28.6
36.0
45.1
44.3
39.6
31.1
20.8
37.0
maintained all year round in grazing
system should make the best offspring in
the winter. Calves born in the period after
the completion of the first period of milk
drinking are prepared to make full use of
the pasture, then their growth rate is fast.
79
TABLE 10. The average milk yield of purebred cows
Year
N
2000
2001
2002
2003
2004
2005
2006
2009
542
517
289
300
261
804
769
2062
min.
785
1055
1094
1214
1220
1004
1234
322
Estimated milk yield of cows (kg)*
max.
average
4365
2040.7
3422
2196.2
3206
2137.8
3011
2186.3
2744
1906.3
2510
2170.0
2980
2133.7
3829
2170.4
SD
361.1
420.3
368.9
260.7
282.9
229.9
212.5
319.7
*Milk yield estimated based on calf weight gain from birth to weaning.
TABLE 11. Time of purebred cows and heifers calvings
Year Unit
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
N
%
I
95
12.3
83
9
91
9
67
7
71
7
92
8
121
8
134
9
132
6
143
6.9
147
7.0
191
8.6
133
6.6
158
7.9
216
11
II
70
9.1
92
10.1
80
8.1
69
7.2
74
7.3
103
8.6
177
11.9
234
15.1
126
7.8
167
9.0
214
10.2
192
8.6
170
8.5
178
8.9
177
9.5
III
144
18.7
193
21.2
158
16.1
176
18.4
128
12.6
204
17.1
187
12.6
323
20.9
272
13
276
13.2
254
12.0
268
12.0
237
11.8
262
13.2
259
13.2
IV
121
15.7
160
17.6
143
14.5
150
15.7
162
15.9
200
16.8
218
14.6
321
20.7
296
14.2
277
13.3
333
15.8
299
13.4
291
14.5
256
12.9
242
12.4
V
91
11.8
81
8.9
122
12.4
108
11.3
124
12.2
115
9.6
145
9.7
123
7.9
218
10.5
214
10.3
221
10.5
270
12.1
202
10.1
238
11.9
174
8.9
Months
VI
VII
63
43
8.2
5.6
65
48
7.2
5.3
71
56
7.2
5.7
92
56
9.6
5.8
102
81
10
8
132
76
11.1 6.4
167
86
11.2 5.8
67
45
4.3
2.9
221 170
10.6 8.2
200 133
9.6
6.4
171 161
8.1
7.6
231 168
10.4 7.5
254 129
12.7 6.4
158 143
7.9
7.2
147 162
7.5
8.3
VIII
18
2.3
24
2.6
48
4.9
56
5.8
64
6.3
78
6.5
91
6.1
65
4.2
140
6.7
122
5.8
162
7.7
115
5.2
144
7.2
91
4.6
99
5.1
IX
21
2.7
24
2.6
48
4.9
56
5.8
76
7.5
69
5.8
87
5.8
65
4.2
92
4.4
139
6.7
114
5.4
109
4.9
115
5.7
88
4.4
101
5.2
X
19
2.5
49
5.4
57
5.8
50
5.2
45
4.4
55
4.6
65
4.4
73
4.7
122
5.9
137
6.6
86
4.1
110
4.9
106
5.3
105
5.3
94
4.8
XI
34
4.4
43
4.7
57
5.8
55
5.7
55
5.4
34
2.8
56
3.8
55
3.6
133
6.4
148
7.1
142
6.7
142
6.4
121
6.0
118
5.9
114
5.8
XII
51
6.6
47
5.2
52
5.3
23
2.4
36
3.5
36
3
89
6
43
2.8
127
6.1
111
5.3
103
4.9
136
6.1
99
4.9
97
9.9
170
8.7
Total
770
100.0
909
100.0
983
100.0
958
100.0
1018
100.0
1194
100.0
1489
100.0
1548
100.0
2085
100.0
2087
100.0
2108
100.0
2231
100.0
2001
100.0
1992
100.0
1955
100.0
80
T. Przysucha et al.
Calves are healthy and good developed
and breeder bear the smallest rearing
costs. It should also be noted that in the
winter calvings weaning calves moment
coincides with the impoverishment of
pastures in autumn. the consequence
is natural dry-off pregnant cows. With
winter calvings cows mostly deliver in
the barn so that it is easier to monitor
deliveries and possible assistance in the
event of complications. Analyzing the
obtained results and assuming that the
most favorable period of cows calving
aptitude is the period from December
to March. It should be noted that from
30.4 to 47.8% of the Polish Charolaise
cows delivered in recent years during
the relevant period cows. It follows that
more than half of the calves born at other
times of the year only to a small degree
can take full advantage of the pasture.
Table 12 shows the percentage distribution of calving aptitude of purebred
Charolaise cows according to calving
order. The greatest number of cows
calved in the years of evaluation was
TABLE 12. Distribution of the order of calvings
Year Unit
2000
2001
2002
2003
2004
2005
2006
2010
2011
2012
2013
Months
Total
I
II
III
IV
V
VI
VII
VIII
IX
X
XI
≥ XII
N
145
310
160
173
79
16
6
14
4
1
1
–
909
%
16.0
34.1
17.6
19.0
8.7
1.8
0.7
1.5
0.4
0.1
0.1
0.0
100.0
N
191
128
269
162
137
57
17
5
7
2
–
–
975
%
19.6
13.1
27.6
16.6
14.1
5.8
1.7
0.5
0.7
0.2
0.0
0.0
100.0
N
207
137
114
217
122
97
33
14
7
7
2
–
957
%
21.6
14.3
11.9
22.7
12.7
10.1
3.4
1.5
0.7
0.7
0.2
0.0
100.0
N
252
180
115
94
173
97
73
22
5
3
3
1
1018
%
24.8
17.7
11.3
9.2
17.0
9.5
7.2
2.2
0.5
0.3
0.3
0.1
100.0
N
318
204
180
104
86
133
77
63
21
4
2
2
1194
%
26.6
17.1
15.1
8.7
7.2
11.1
6.4
5.3
1.8
0.3
0.2
0.2
100.0
N
412
285
188
163
84
87
106
64
66
24
7
3
1489
%
27.7
19.1
12.6
10.9
5.6
5.8
7.1
4.3
4.4
1.6
0.5
0.2
100.0
N
534
468
234
134
45
34
22
22
32
23
–
–
1548
%
34.5
30.2
15.1
8.7
2.9
2.2
1.4
1.4
2.1
1.5
0.0
0.0
100.0
N
505
462
402
327
227
156
75
34
25
14
1
3
2231
%
22.6
20.7
18.0
14.6
10.1
6.9
3.3
1.5
1.1
0.6
0.0
0.1
100.0
N
405
390
335
295
213
163
98
48
24
23
6
1
2001
%
20.2
19.4
16.7
14.7
10.6
8.1
4.8
2.3
1.1
1.1
0.2
N
427
334
339
288
227
150
98
71
29
10
15
4
1992
%
21.4
16.7
17.0
14.4
11.3
7.5
4.9
3.5
1.4
0.5
0.7
0.2
100.0
N
372
338
273
275
238
193
127
58
49
19
5
8
1955
%
19.0
17.3
14.0
14.1
12.2
9.9
6.5
3.0
2.5
1.0
0.3
0.5
100.0
0.05 100.0
reported in primiparous cows and cows
calving for the second time. It should be
noted that in 2000 primiparous cows and
the animals calving for the second time
constituted more than 50% and in 2013
36.3% of the population. It means that
the life of the cow increases, which is of
particular economic importance. Long
life of cows in herds of beef cattle is one
of the main factors allowing for reducing
the cost. so the breeders should try to use
cows as long as possible.
CONCLUSIONS
One can observe a gradual decline
in the share of the national Charolais
beef cattle population. it also shows
a significant decrease in the number of
crossbreds with Charolais breed. The
average weight of cows in 2005–2006
amounting to 559.4 and 570.2 kg meet
the breeding standards for of cows entered in the initial part of the herd book.
which define the minimum weight of
Charolais cows after first calving as
550 kg. The average weight of heifers at
birth in each year assessment was similar,
but after 2008 began more than 40 kg. In
purebred bulls it was seen a systematic
increase in the average birth weight.
The difference in birth weights between
heifers and bulls ranged from 1 kg in
1999 to 3.6 kg in 2012. High average
daily weight gains of bulls to 210 days
of age, at short extra supplementary
fattening period of about one month
allow to export the animals weighing
about 300 kg at an good price. The average daily gains of heifers (550–560 g),
guarantee obtaining at 15 months of age
body weight allowing the commencement of breeding. It should be noted
81
that the Polish Charolais cows in recent
years during the relevant period from
30.4 to 47.8% of cows.
REFERENCES
ANDERSEN B.B., 1978: Animal size and efficiency. with special reference to growth and
feed conversion in cattle. Anim. Prod. 27:
381–391.
BROWN C.J., JOHNSON Z.B., BROWN A.H.
jr., 1989: Between and within breed variation
in mature weight and maturing interval of beef
cattle. J. Anim. Sci. 67 (Suppl.) 2: 9.
DOBICKI A., 1995: Technologiczne aspekty
efektywności produkcji w populacjach mięsnych bydła. Zeszyty Naukowe Przeglądu Hodowlanego 17: 57–71.
DOBICKI A., 1996: Hodowla i użytkowanie bydła ras mięsnych. Chów Bydła 11: 19–21.
GRODZKI H., 1999: Chów bydła mięsnego. Wieś
Jutra 7–8: 29–30.
JASIOROWSKI H., 1999: Blaski i cienie hodowli bydła mięsnego w Polsce. Wieś Jutra 7–8:
27–28.
JASIOROWSKI H., KIJAK Z., POCZYNAJŁO S.,
WAJDA S., 1996: Program rozwoju hodowli
bydła mięsnego w Polsce. Fundacja „Rozwój
SGGW”: 5–67.
JASIOROWSKI H., PRZYSUCHA T., 2004:
Bydło mięsne: wybór rasy. Top Agrar Polska 1:
102–104.
Krajowe Centrum Hodowli Zwierząt, 1997–2000:
Ocena wartości użytkowej krów oraz ocena
i selekcja buhajów. Wyniki za lata 1996–1999.
Polski Związek Hodowców i Producentów Bydła
Mięsnego, 2001–2014: Ocena wartości użytkowej bydła ras mięsnych. Wyniki za lata 2000–
–2013.
PRZYSUCHA T., CZARNECKI vel SARNECKI
M., GRODZKI H., ZDZIARSKI K., 2002b:
The influence of selected factors on body
weight and daily gains of Angus calves. Rocz.
Nauk. Zoot. (Suppl.) 15: 225–230.
PRZYSUCHA T., CZARNECKI vel SARNECKI M., GRODZKI H., ZDZIARSKI K., 2002a:
Analiza wpływu wybranych czynników na
tempo wzrostu cieląt rasy hereford. Zesz. Nauk.
Przegl. Hod. 60: 233–243.
82
T. Przysucha et al.
PRZYSUCHA T., GRODZKI H., CHARŁAMPOWICZ A., ZDZIARSKI K., 2002c: The
effect of selected factors on growth rate of
Limousine calves. Anim. Sci. Pap. Rep. 20.
(Suppl.) 1: 221–228.
PRZYSUCHA T., GRODZKI H., NAŁĘCZ-TARWACKA T., ZDZIARSKI K., 2002d: Analiza
wpływu wybranych czynników na masę ciała
i przyrosty cieląt rasy charolaise. Zesz. Nauk.
Przegl. Hod. 62: 203–210.
PRZYSUCHA T., GRODZKI H., PRAWDZIK B.,
SLÓSARZ J., ZDZIARSKI K., 2003: Analiza
wpływu wybranych czynników na masę ciała
i przyrosty cieląt rasy piemontese. Rocz. Nauk
Zoot. (Supl.) 17: 881–884.
Streszczenie: Analiza wyników oceny wzrostu
bydła charolaise w Polsce. Celem pracy była
analiza wybranych wyników oceny użytkowości
francuskiej rasy charolaise w odniesieniu do ich
zgodności z celem hodowlanym i standardami rasowymi przyjętymi przez PZHiPBM. Przedmiotem analiz były wyniki oceny użytkowości francuskiej rasy bydła mięsnego charolaise w Polsce.
Opracowanie oparte jest na danych Polskiego
Związku Hodowców i Producentów Bydła Mięsnego (PZHiPBM) za lata 2002–2013 oraz Krajowego Centrum Hodowli Zwierząt (KCHZ) za lata
1996–2001. Zbiór danych obejmował: N – liczbę
badanych zwierząt, min. – minimalne wartości
w badanej cechy, max. – maksymalne wartości badanej cechy, średnia – uśrednione wartości badanej cech, SD – odchylenie standardowe. Oceniane
cechy to: średnie masy ciała krów (kg), średnie
masy ciała cieląt po urodzeniu (kg), średnie przyrosty dobowe do wieku 210 dni (g), średnie masy
ciała cieląt w wieku 210 dni (kg), średnia mleczność krów (kg), terminy ocieleń krów i jałowic,
rozkład populacji krów według kolejności ocielenia. Można zaobserwować stopniowy spadek
udziału rasy charolaise w krajowej populacji bydła
mięsnego. Widać również znaczący spadek liczby
mieszańców z rasą charolaise. Średnie masy krów
w latach 2005–2006, wynoszące odpowiednio
559,4 i 570,2 kg, spełniają standardy hodowlane
dla krów wpisywanych do części wstępnej księgi hodowlanej, które określają minimalną masę
ciała krowy rasy charolaise po 1. ocieleniu jako
550 kg. Średnia masa ciała przy urodzeniu jałówek w poszczególnych latach oceny była zbliżona, ale po 2008 roku zaczęła przekraczać 40 kg.
U buhajków czystorasowych widać systematyczny wzrost średniej masy urodzeniowej. Różnica
średnich mas urodzeniowych między jałówkami
a buhajami wynosiła od 1 kg w 1999 roku do
3,6 kg w 2012 roku. Wysokie średnie przyrosty
dobowe masy ciała buhajków do 210. dnia życia
pozwalają przy niedługim, dodatkowym, uzupełniającym okresie opasu, wynoszącym około jednego miesiąca, sprzedaż na eksport za korzystną
cenę opasów o masie ciała około 300 kg. Uzyskane średnie dobowe przyrosty cieliczek dają gwarancję, że dalsze żywienie gwarantujące przyrosty dobowe w granicach 550–560 g pozwolą na
uzyskanie przez nie w wieku 15 miesięcy masy
ciała pozwalającej na rozpoczęcie użytkowania
rozpłodowego. W polskich stadach bydła charolaise cieliło się w ostatnich latach we właściwym
okresie od 30,4 do 47,8% krów.
Authors’ address:
Tomasz Przysucha
Poland
Analysis of Limousine beef cattle recording results in Poland
TOMASZ PRZYSUCHA, MARCIN GOŁĘBIEWSKI,
HENRYK GRODZKI, KAROLINA WNĘK, JAN SLÓSARZ,
MAŁGORZATA KUNOWSKA-SLÓSARZ, PIOTR TOKARSKI
Abstract: Analysis of Limousine beef cattle recording results in Poland. The aim of the study
was to assess the utility of selected results of the
French Limousine breed with respect to their
compliance with the breeding goal and standards
adopted by the Polish Association of Breeders and
Producers of Beef Cattle (PABPBC). The subject
of the analysis were the results of the assessment
of recording results of the French Limousine breed
in Poland. The study is based on data for the years
2002–2013 of PABPBC and the National Center
of Animal Breeding (NCAB) for 1996–2001. The
data set included: N – the number of animals tested,
min. – minimum values in the studied traits, max.
– maximum value of the selected traits, average
– average values of the analyzed traits, SD – standard deviation. Evaluated traits are: average weight
of cows (kg), average body weight of calves after
birth (kg), average daily gains for age 210 days (g),
average body weight of calves at the age of 210
days (kg), average milk yield (kg), terms of cows
and heifers calving aptitude, distribution of the
population according to the order of calving cows.
The share of purebred and crossbred Limousine
cows in the national beef cattle population is dominant and in 2013 constituted 81.2%. The average
body weight of cows do not depart from the masses
assumed to culture. Higher birth weight bulls had
reached in 2013. Weight of 37.5 kg. The difference between bulls and heifers was 3 kg. Calves
were characterized by high body weight daily
gains during rearing: 900–1009 g respectively for
heiferss and 973–1088 g for the bulls. It should be
noted that since 2002 bulls exceeded daily gains
of 1000 g. The Polish Limousine cattle herds in
recent years from 30.1 to 44.7% of cows calved
during the relevant period. Thanks to the consistent
growth of the population of Limousine, primiparous cows and cows calving for the second time
amounted to about 40% of the population, despite
the growing number of older cows. In 2000, only
2 cows were after 7 calvings, and in 2013 there
were 1416 already (12.6%). It mean that the life of
the cow increases, which is of particular economic
importance.
Key words: beef cattle, Limousine, beef cattle recording
INTRODUCTION
Currently in Poland there are registered
14 specialized breeds of beef cattle for
which records are kept and evaluation of
breeding value is conducted. Herdbook
and recording assessment are conducted
by the Polish Association of Breeders
and Producers of Beef Cattle (PABPBC).
PABPBC breeding goal for Limousine
breed is to maintain high performance
slaughter parameters, good weight,
ease of calving course maintaining and
improving weight gain of calves as an
indicator of maternal milk production.
The parameters for the growth of adult
cows – body weight of 600–650 kg with
a height of 135 cm in sacrum, bulls – body
84
T. Przysucha et al.
weight 1100 kg with height of 145 cm in
sacrum. In the national breeding program
for Limousine cattle there are defined,
inter alia, the following breeding standards for cows entered in the introductory
part of the book: the minimum weight
gain from birth to 210 days of age – 850 g,
the minimum weight after first calving
– 480 kg. The aim of the study was to
assess selected recording results of the
French Limousine breed with respect to
their compliance with the breeding goal
and standards adopted by PABPBC.
The subject of the analysis were beef
cattle recording results for the French
Limousine breed in Poland. with respect
to their compliance with the goal of
racial breeding and standards adopted by
the Polish Association of Breeders and
Producers of Beef Cattle (PABPBC). The
subject of the analysis were recording results of the Limousine beef cattle breed
in Poland. The study was based on data
for the years 2002–2013 of PABPBC and
the National Center of Animal Breeding
(NCAB) for 1996–2001. The data set
included: N – number of animals tested,
min. – minimum values in the studied
traits, max. – maximum value of the
selected features, average – average
values of the analyzed traits, SD – standard deviation. Evaluated properties are:
average weight of cows (kg), the average
body weight of calves after birth (kg), the
average daily gains for age 210 days (g),
the average body weight of calves at the
age of 210 days (kg), the average milk
yield (kg), the terms of cows and heifers calving aptitude, the distribution of
the population according to the order of
calving cows. The calculation of standardized animal body weight for given
day in its life was done according to the
following formula:
MCS = [(MCB – MCU) / WW] ×
× WS + MCU
where:
MCS – standardized animal body
weight (kg);
MCB – mean body weight of the animal
on the actual weighing (kg);
MCU – actual body weight set for
48 hours, at birth (kg);
WW – mean age of the animal on the
weighing (days);
WS – standardized age of the animal
(s).
There were calculated the average daily
weight gain of the animal from the day
of birth to 210 days of age, according to
the formula:
PDMC = [(MCC – MCP) ×
× 1000] / (WK – WP)
where:
PDMC – means of increase in daily
body weight (g);
MCC – final body weight of the
animal on the weighing day
(kg);
MCP – initial body weight of the
animal on the weighing (kg);
WK
– mean age of the animal on the
final weighing (days);
WP
– mean age of the animal on
the initial weighing (days
milk yield in dairy cows is
expressed in kg of milk per
convention.
The conversion 210 day lactation and
is calculated according to the formula:
WMM210 = (McOds × 1700) / calf age
where:
WMM210 – value of mother milk
– milk yield for 210 day lactation
conversion assuming calf birth weight
35 kg, per 1 kg body weight gain,
which drank 10 kg milk a day during
the first 3 months, and the remaining
months of 8–9 kg a day;
McOds (kg) – actual weight of the calf
at weaning;
calf age (days) – actual age of the calf at
the time of weaning from the mother.
85
Table 1 presents the quantitative changes
of the female population of Limousine
cattle in Poland in the years 1996–2013.
It may be noticed a systematic increase in
population from 1998 to 2006, while in
2007, a noticeable decrease. The reason
is not a drastic decrease in the number
of purebred cows and heifers, but the
changes in the presentation of results.
Until 2006 statement included heifers and
cows, while in 2007, is given only the
number of cows. The share of purebred
and crossbred Limousine cows in the national beef cattle population is dominant
and in 2013 constituted 81.2%.
TABLE 1. Quantitative changes of the female population of Limousine cattle in Poland*
Beef breed female population
Year
Limousine
breed
(purebred)
Limousine
breed
(crossbred)
Limousine
breed
(purebred +
+ crossbred)
Limousine
breed share
in the
population
pure-bred
crossbred
1996
3 939
4 952
8 891
1 109
3 211
4 320
48.6
1997
6 063
5 772
11 835
1 846
3 344
5 190
43.9
1998
7 227
7 601
14 828
2 362
4 314
6 676
45.0
1999
8 375
8 243
16 618
2 882
4 919
7 801
46.9
2000
9 085
9 468
18 553
3 226
6 176
9 402
50.7
2001
9 129
9 748
18 877
3 159
6 837
9 996
53.0
2002
9 735
8 968
18 703
3 248
6 564
9 812
52.5
total
2003
11 768
9 382
21 150
4 653
6 925
11 578
54.7
2004
13 884
10 925
24 809
5 684
8 125
13 809
55.7
2005
17 130
11 710
28 840
8 578
9 073
17 651
61.2
2006
19 597
13 100
32 697
9 689
10 108
19 797
60.5
2007
14 541
11 676
26 217
7 443
9 070
16 513
63.0
2008
17 481
12 097
29 578
9 856
10 142
19 998
67.6
2009
15 435
7 711
23 146
9 995
6 682
16 677
72.1
2010
16 436
7 576
24 012
11 037
6 684
17 721
73.8
2011
16 216
7 459
23 675
11 310
6 653
17 963
75.9
2012
16 724
7 070
23 794
11 879
6 389
18 268
76.8
2013
17 481
6 633
24 114
12 586
6 987
19 573
81.2
*From 2007 the list includes only the cows.
86
T. Przysucha et al.
The average body weight of purebred
cows is shown in Table 2. Optimum
weight and dimensions depend mainly
on cattle production system (Morris and
Wilton 1976, Andersen 1978, Dickerson
1978, Fitzhugh 1978, Nogalski et al.
2000). Genotype and weight of mother
cows are always described among the
many factors responsible for normal
growth and development of calves. Many
studies have shown that the weight of the
cow has a significant impact on calf birth
weight, as well as daily gains during
rearing (Przysucha et al. 2002). Therefore, the weight of a cow in adulthood
is an important feature to be considered
for breeding programs (Anderson 1978,
Brown et al. 1989). According to the
breeding goal of PABPBC, cows body
weight in adulthood should be 600–
–650 kg for Limousine breed. Analysis
of the recording results shows that the
average body weight of cows did not
differ from the breeding goal.
to a calf body weight at weaning at the
age of 210 days. The calves with highest
body weight at birth also typically have
the highest body weight at the end of the
rearing (Przysucha et al. 2002, Przysucha
et al. 2005). Bulls had reached higher
birth weight in 2013 (37.5 kg). The difference between bulls and heifers was 3 kg.
Nogalski et al. (2000) reported a greater
number of falls of small, less vital calves.
They also noticed that the mothers of
dead calves were significantly lighter
and in worse condition, and consequently
created worse conditions for the development of the fetus, and were less prepared
to make the effort in delivery.
Average daily weight gains of purebred calves to the age of 210 days are
shown in Tables 5 and 6. The data presented show that the calves were characterized by high body weight gains
during rearing: 900–1009 g respectively
for heifers and 973–1088 g for the bulls.
It should be noted that since 2002 bulls
TABLE 2. Body weight of purebred Limousine cows
Year
N
1999
Cow body weight (kg)
min.
max.
average
SD
1126
350
900
634.0
73.0
2000
1504
382
890
619.1
76.0
2001
1568
430
890
618.0
72.1
2002
1557
370
850
606.2
76.7
2003
1999
420
850
596.6
73.0
2004
2190
320
850
597.1
71.7
2005*
733
480
710
543.2
33.5
2006*
1489
440
796
552.1
36.1
*Body weight after first calving
Tables 3 and 4 present the mean body
weight of purebred calves after birth.
Many authors have shown a significant
effect of calves body weight after birth
exceeded daily gains of 1000 g. These
gains make, that after a short (about
1 month) supplementary fattening, bulls
with a body weight of about 300 kg
TABLE 3. Average body weight of purebred heifers at birth
Year
N
1999*
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
1284
650
736
785
939
1036
1784
2935
3377
4705
5522
5732
5936
6466
6107
min.
16
22
17
20
20
17
15
17
19
16
20
15
15
15
14
Body weight (kg)
max.
average
67
34.3
55
33.1
58
34.6
55
34.7
60
33.7
49
33.4
48
33.1
50
34.7
55
33.5
58
34.2
56
34.3
57
34.3
54
34.4
57
34.5
56
34.5
SD
5.9
5.2
5.0
4.4
4.2
3.9
3.8
3.4
4.2
4.1
4.2
3.9
3.9
4.1
4.2
*Regardless of sex.
TABLE 4. Average body weight of purebred bulls at birth
Year
N
1999*
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
1284
655
716
723
994
1103
1745
2774
2924
4249
4995
5349
5506
5879
5626
*Regardless of sex.
min.
16
18
18
23
20
15
18
20
20
16
20
18
20
20
15
Body weight (kg)
max.
average
67
34.3
57
34.5
53
36.2
52
36.0
50
35.3
50
35.3
52
35.3
55
36.2
65
35.7
61
36.8
60
37.0
65
37.2
65
37.4
70
37.7
60
37.5
SD
5.9
6.4
5.5
4.7
4.3
4.4
4.1
4.2
4.8
4.5
4.6
4.5
4.4
4.4
4.6
87
88
T. Przysucha et al.
TABLE 5. Average daily gains of purebred heifers to 210 days of age
Year
N
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
241
497
494
641
654
1 007
1 574
2 544
4 202
4 999
5 430
5 381
5 932
5 632
min.
550
518
494
429
417
510
509
401
343
351
372
489
332
332
Daily gains (g)
max.
average
12 989
900.4
1 495
954.8
1 421
915.5
1 619
937.8
1 514
974.2
1 686
991.5
1 389
1 005.0
2 241
959.9
1 611
963.0
1 482
964.9
1 548
967.8
1 480
983.3
1 676
1 009.7
1 676
1 000.9
SD
136.2
163.9
124.3
142.2
122.1
136.5
99.9
126.6
126.4
124.7
106.9
88.7
63.6
133.7
TABLE 6. Average daily gains of purebred bulls to 210 days of age
Year
N
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
280
463
369
603
692
834
1 624
2 011
3 671
4 359
4 677
4 681
5216
5053
min.
617
522
546
541
541
420
381
417
474
348
405
346
346
378
previously eliminated from breeding
can be sold for export at a good price.
The gains considerably in excess of the
gains of heifers defined in the breeding
standard ensure that after weaning with
proper nutrition they obtain the required
Daily gains (g)
max.
average
1 446
973.7
1 478
986.8
1 427
1 007.1
1 575
1 014.9
1 452
1 047.8
1 748
1 088.5
2 324
1 064.1
1 828
1 064.2
1 835
1 051.1
1 693
1 051.6
1 599
1 051.2
1 746
1 071.4
1 746
1 076.6
1 913
1 094.6
SD
164.4
177.8
122.3
152.4
125.7
155.4
152.1
137.5
128.6
121.7
116.2
88.6
46.8
152.1
body weight for mating (Przysucha et al.
2006) at the age of 15 months. Among
the Limousine breed calves there is very
low percentage of mortality by as much
as 3% lower in the French breeding conditions. Besides they are characterized
by rapid growth and development, and
vitality (Przysucha et al. 2005). In study
of Pogorzelska et al. (1998) Limousine
bulls daily gains from birth to weaning
were more than 1000 g, and at the age
of 3–4 months obtained body weight
of approximately 170 kg. It should be
emphasized that the average daily gains
of calves ranged considerably in the last
years of assessment. This is confirmed
by the high standard deviations.
The average body weight of purebred
calves at 210 days of age are presented
in Tables 7 and 8. The body weights at
the time of weaning were at the level
of the 222–253 kg for heifers and 238–
–274 kg for bulls. The highest weight
at the age of 210 days for heifers was
reached in 2006 and for the bulls in 2007.
The studies lead to the conclusion that by
the breeding standards weights at weaning for both heifers and bulls were at
medium level, but fall within the French
standards. The average weight of bulls
was evaluated by approximately 20 kg
higher than the average weight of heifers
of the same age.
Table 9 shows the average milk yield
of purebred cows in different years of
assessment. As can be seen from the following statement, the average milk yield
of Limousine cows was 2002.4 kg in the
last year of the assessment and did not
undergo significant changes in subsequent
years. The minimum value of this trait
was 640 kg and the maximum 3312 kg.
The data should be approached with great
caution because milk yield was calculated
based on the weight gain of calves, and as
we know in the herd calves can always be
found that approach to other cows choke
or are fed by the breeder. For this reason,
since 2010, evaluation of this feature was
a ceased.
TABLE 7. Average body weight of purebred heifers at 210 days of age
Year
N
1999*
2000
Body weight (kg)
min.
max.
average
SD
873
70
213
140.6
21.5
241
149
315
221.7
29.7
2001
499
155
347
237.2
34.3
2002
497
128
329
227.0
26.8
2003
642
120
370
230.2
30.6
2004
654
118
350
238.2
26.4
2005
1007
110
380
241.6
29.1
2006
1574
120
397
246.2
34.3
2007
2544
103
395
236.4
31.5
2008
4202
127
371
237.7
32.5
2009
4999
110
398
240.1
32.8
2010
5430
120
500
239.0
31.4
2011
5381
122
365
247.1
22.3
2012
5918
104
401
253.3
13.7
2013
5632
135
410
251.7
11.7
*Regardless of sex.
89
90
T. Przysucha et al.
TABLE 8. Average body weight of purebred bulls at 210 days of age
Year
N
1999*
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
873
280
466
370
608
692
834
1624
2011
3671
4359
4677
4681
5216
5053
min.
70
162
153
143
146
142
119
113
120
150
119
126
128
138
107
Body weight (kg)
max.
average
213
140.6
351
238.5
348
245.5
336
247.5
363
248.0
339
255.4
393
246.3
430
249.0
450
260.7
406
258.7
440
261.6
430
259.4
420
269.2
431
271.5
450
274.7
SD
21.5
36.6
37.8
27.6
32.6
27.1
33.6
48.9
36.1
34.8
34.3
33.6
28.1
11.7
33.6
Estimated milk yield of cows (kg)
max.
average
3 250.0
1 884.8
3 311.9
1 951.4
2 833.3
1 914.2
2 995.2
1 933.8
2 833.1
1 999.8
2 395.0
1 881.0
3 087.0
2 069.2
2 958.0
2 002.4
SD
315.9
354.1
232.4
265.6
227.5
206.5
238.6
231.6
*Regardless of sex.
TABLE 9. The average milk yield of purebred cows
Year
N
2000
2001
2002
2003
2004
2005
2006
2009
858
795
796
1 249
1 346
1 628
3 205
9 157
min.
745.0
1020.0
971.4
971.4
951.9
640.0
1 009.0
899.0
Table 10 summarizes the terms of
cows and heifers calving aptitude in
the coming months in the year, in the
years 1999–2013. Season of birth has
a significant impact on the vitality and
growth pace of reared calves. which
directly affects the economic effects
of the rearing (Makulska et al. 2002,
Przysucha et al. 2005). Seasonality
in calvings in breeding herds is very
important. because appropriate term of
calving in the future allows to receive
breeding material of a very good quality with the least amount of cost of
rearing (maximum utilization of pastures). Many authors believe (Dobicki
1996, Jasiorowski 1999, Jasiorowski
and Przysucha 2004). that the period
91
TABLE 10. Time of purebred cows and heifers calving
Year Unit
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Months
Total
I
II
III
IV
V
VI
VII
VIII
IX
X
XI
XII
N
127
127
172
177
171
103
101
71
58
81
68
73
1329
%
9.6
9.6
12.9
13.3
12.9
7.8
7.6
5.3
4.4
6.1
5.1
5.5
100.0
N
107
135
235
191
166
115
111
88
70
95
83
122
1518
%
7.0
8.9
15.5
12.6
10.9
7.6
7.3
5.8
4.6
6.3
3.5
8.0
100.0
N
174
156
203
211
159
104
123
110
79
84
83
90
1576
%
11.0
9.9
12.9
13.4
10.1
6.6
7.8
7.0
5.0
5.3
5.3
5.7
100.0
N
148
142
214
244
182
135
79
97
89
71
85
84
1570
%
9.4
9.0
13.6
15.5
11.6
8.6
5.0
6.2
5.7
4.5
5.4
5.4
100.0
N
147
236
276
279
241
191
150
96
73
96
91
126
2002
%
7.3
11.8
13.8
13.9
12.0
9.5
7.5
4.8
3.6
4.8
4.5
6.3
100.0
N
165
177
323
336
233
223
172
111
124
131
89
107
2191
%
7.5
8.1
14.7
15.3
10.6
10.2
7.9
5.1
5.7
6.0
4.1
4.9
100.0
N
232
356
435
325
365
286
245
216
220
152
122
156
3110
%
7.5
11.4
14.0
10.5
11.7
9.2
7.9
6.9
7.1
4.9
3.9
5.0
100.0
N
750
768
843
567
332
456
567
456
312
345
123
190
5709
%
13.1
13.5
14.8
9.9
5.8
8.0
9.9
8.0
5.5
6.0
2.2
3.3
100.0
N
389
484
678
893
800
624
497
428
464
447
389
403
6496
%
6.0
7.5
10.4
13.7
12.3
9.6
7.7
6.6
7.1
6.9
6.0
6.2
100.0
N
531
673
927
936
1085
787
481
485
484
424
404
406
7623
%
7.0
8.8
12.2
12.3
14.2
10.3
6.3
6.4
6.4
5.6
5.3
5.3
100.0
N
670
676
1087 1335 1208
805
596
560
500
459
590
581
9067
100.0
%
7.4
7.5
12.0
13.3
8.9
6.6
6.2
5.5
5.1
6.5
6.4
N
739
762
1175 1581 1201
14.7
835
694
591
550
447
533
580
9688
%
7.6
7.9
12.1
8.6
7.2
6.1
5.7
4.6
5.5
6.0
100.0
16.3
12.4
N
913
761
1195 1349 1417 1016
733
546
604
473
494
635
10136
%
9.0
7.5
11.8
14.0
10.0
7.2
5.4
6.0
4.7
4.9
6.3
100.0
13.3
N
953
942
1374 1491 1439
976
738
664
595
547
562
762
1043
%
8.6
8.5
12.4
8.8
6.7
6.0
5.4
5.0
5.1
6.9
100.0
N
1058
960
1257 1508 1337 1046
818
727
598
600
677
600
11186
%
9.5
8.6
11.2
7.3
6.5
5.3
5.4
6.1
5.4
100.0
13.5
13.5
13.0
12.0
9.4
of mating and the resulting of calving
aptitude time should not be longer than
2–3 months. Beef cows maintained all
year round in grazing system should
make the best offspring in the winter.
Calves born in the period after the completion of the first period of milk drinking are prepared to make full use of the
pasture. then their growth rate is fast.
calves are healthy and good developed
92
T. Przysucha et al.
and breeder bear the smallest rearing
costs. It should also be noted that in the
winter calvings weaning calves moment
coincides with the impoverishment of
pastures in autumn. the consequence
is natural dry-off pregnant cows. With
winter calvings cows mostly deliver in
the barn so that it is easier to monitor
deliveries and possible assistance in the
event of complications. Analyzing the
obtained results and assuming that the
most favorable period of cows calving
aptitude is the period from December
to March. It should be noted that from
30.1 to 44.7% of the Polish Limousine
cows delivered in recent years during
the relevant period cows. It follows
that more than half of the calves born at
other times of the year only to a small
degree can take full advantage of the
pasture.
Table 11 shows the percentage distribution of calving aptitude of purebred
Limousine cows according to calving
order. Limousine breed is considered to
be long-lived and early maturing breed.
TABLE 11. Distribution of the order of calving
Year Unit
2000
2001
2002
2003
2004
2005
2006
2010
2011
2012
2013
Months
I
II
III
IV
V
VI
VII
VIII
IX
X
XI
≥ XII
Total
N
360
282
323
364
158
25
2
–
–
–
–
–
1514
%
23.8
18.6
21.3
24.0
10.4
1.7
0.1
–
–
–
–
–
100.0
N
363
299
222
274
278
124
12
2
–
–
–
–
1574
%
23.1
19.0
14.1
17.4
17.7
7.9
0.8
0.1
–
–
–
–
100.0
N
387
300
193
164
186
196
104
19
–
–
–
–
1549
%
25.0
19.4
12.5
10.6
12.0
12.7
6.7
1.2
–
–
–
–
100.0
N
474
369
353
218
191
156
146
67
12
–
–
–
1986
%
23.9
18.6
17.8
11.0
9.6
7.9
7.4
3.4
0.6
–
–
–
100.0
N
544
412
287
271
179
174
149
122
45
8
–
–
2191
%
24.8
18.8
13.1
12.4
8.2
7.9
6.8
5.6
2.1
0.4
–
–
100.0
N
919
573
412
326
268
166
148
149
102
40
7
–
3110
%
29.5
18.4
13.2
10.5
8.6
5.3
4.8
4.8
3.3
1.3
0.2
–
100.0
N
1484 1235 1123
943
345
359
56
76
56
12
8
12
5709
%
26.0
16.5
6.0
6.3
1.0
1.3
1.0
0.2
0.1
0.2
100.0
21.6
19.7
N
2362 2124 1960 1352
803
403
248
169
117
67
34
49
9688
%
24.3
8.2
4.1
2.5
1.7
1.2
0.6
0.3
0.4
100.0
21.9
20.2
13.9
N
2335 2090 1717 1586 1047
616
303
172
115
79
42
34
10 136
%
23.0
10.3
6.0
2.9
1.6
1.1
0.7
0.4
0.2
100.0
N
2564 1947 1756 1477 1396
834
482
273
135
77
53
49
11 043
%
23.2
17.6
15.9
13.3
7.5
4.3
2.4
1.2
0.6
0.4
0.3
100.0
N
2153 2110
619
1522 1262 1105
636
346
216
100
61
56
11 186
%
19.2
14.5
13.6
5.7
3.1
1.9
0.9
0.5
0.5
100.0
20.6
18.9
16.9
15.6
12.6
11.3
9.9
Average life expectancy of cows is 8–11
years, and the number of calves born
during the lifetime of a single cow an
average 7 pieces. Cows of this breed very
well take care of their offspring – are very
good and caring mothers (Pogorzelska et
al. 1998). It should be noted that due to
the systematic increase in the population
of Limousine breed cows, primiparous
cows and cows calving for the second
time constitute about 40% of the population, despite the growing number of
older cows. In 2000, only 2 cows were
after 7 calving, and in 2013 there were
already 1416 (12.6%). It proves that the
life of the cow increases. which is of
particular economic importance. Long
life of cows in herds of beef cattle is one
of the main factors allowing for reducing
the cost. so the breeders should try to use
cows as long as possible.
CONCLUSIONS
Analysis of selected results of the evaluation of the French utility Limousine
with regard to their compliance with the
breeding goal and standards adopted by
PABPBC shows maintenance of high
standards of the national breeding population of this breed of cattle.
REFERENCES
ANDERSEN B.B., 1978: Animal size and efficiency, with special reference to growth and
feed conversion in cattle. Anim. Prod. 27:
381–391.
BROWN C.J., JOHNSON Z.B., BROWN A.H.
jr., 1989: Between and within breed variation
in mature weight and maturing interval of beef
cattle. J. Anim. Sci. 67 (Suppl. 2): 9.
DICKERSON G.E., 1978. Animal size and efficiency: basic concepts. Anim. Prod. 27: 367–
–379.
93
DOBICKI A., 1996: Technologiczne aspekty efektywności produkcji w populacjach mięsnych
bydła. Zesz. Nauk. Przegl. Hod. 17: 57–71.
FITZHUGH H.A., 1978. Animal size and efficiency, with special reference to the breeding
female. Anim. Prod. 27: 393–401.
JASIOROWSKI H., 1999: Blaski i cienie hodowli bydła mięsnego w Polsce. Wieś Jutra 7–8:
27–28.
JASIOROWSKI H., KIJAK Z., POCZYNAJŁO S., WAJDA S., 1996: Program rozwoju
hodowli bydła mięsnego w Polsce. Fundacja
„Rozwój SGGW”, Warszawa: 5–67.
JASIOROWSKI H., PRZYSUCHA T., 2004:
Bydło mięsne: wybór rasy. Top Agrar Polska 1:
102–104.
KRAJOWE CENTRUM HODOWLI ZWIERZĄT, 1997–2000: Ocena wartości użytkowej
krów oraz ocena i selekcja buhajów. Wyniki za
lata 1996–1999.
MAKULSKA J., WEGLARZ A., SZAREK J.,
2002: Wpływ sezonu urodzenia na produkcyjno-ekonomiczne wyniki odchowu cieląt
rasy limousinee. Rocz. Nauk. Zoot. (Supl.) 15:
213–218.
MORRIS C.A., WILTON J.W., 1976: The influence of body size on the biological efficiency of
cows: A review. Can. Anim. Sci. 56: 613–647.
NOGALSKI Z., KLUPCZYŃSKI J., MICIŃSKI
J., 2000. Przebieg porodu, wielkość i żywotność cieląt w zależności od wymiarów ciała
krów. Rocz. Nauk. Zoot. 27 (3): 43–57.
POGORZELSKA J., ROMANOWSKI A., PUCHAJDA Z., 1998: Analiza użytkowania rozpłodowego i rozwój importowanego z Francji
bydła limousinee i charolaise. Zesz. Nauk. AR
we Wrocławiu XIX (336): 143–148.
Polski Związek Hodowców i Producentów Bydła Mięsnego, 2001–2014: Ocena wartości
użytkowej bydła ras mięsnych. Wyniki za lata
2000–2013.
PRZYSUCHA T., GRODZKI H., BRZOZOWSKI P., ZDZIARSKI K., 2005: Wpływ wybranych czynników na przebieg porodów krów
rasy limousine. Medycyna Weterynaryjna
61 (9), 1036–1038.
PRZYSUCHA T., GRODZKI H., CHARŁAMPOWICZ A., ZDZIARSKI K., 2002: The effect
of selected factors on growth rate of Limousinee calves. Anim. Sci. Pap. Rep. 20, (Suppl.)
1: 221–228.
94
T. Przysucha et al.
STĄPOREK K., ZIEMIŃSKI R., 2006: Aktualne trendy w chowie i hodowli rasy Limousine.
Przegl. Hod. 7: 1–4.
Streszczenie: Analiza wyników oceny użytkowości francuskiej rasy limousine w Polsce. Celem
pracy była analiza wybranych wyników oceny
użytkowości francuskiej rasy limousine w odniesieniu do ich zgodności z celem hodowlanym
i standardami rasowymi przyjętymi przez Polski
Związek Hodowców i Producentów Bydła Mięsnego. Przedmiotem analiz były wyniki oceny
użytkowości francuskiej rasy bydła mięsnego
limousine w Polsce. Opracowanie oparte jest na
danych PZHiPBM za lata 2002–2013 oraz Krajowego Centrum Hodowli Zwierząt (KCHZ) za lata
1996–2001. Zbiór danych obejmował: N – liczbę
badanych zwierząt, min. – minimalne wartości
w badanej cechy, max. – maksymalne wartości badanej cechy, średnia – uśrednione wartości badanej cech, SD – odchylenie standardowe. Oceniane
cechy to: średnie masy ciała krów (kg), średnie
masy ciała cieląt po urodzeniu (kg), średnie przyrosty dobowe do wieku 210 dni (g), średnie masy
ciała cieląt w wieku 210 dni (kg), średnia mleczność krów (kg), terminy ocieleń krów i jałowic,
rozkład populacji krów według kolejności ocielenia. Udział czystorasowych i mieszańcowych
krów rasy limousine w krajowej populacji bydła
mięsnego jest dominujący i w 2013 roku stanowił 81,2%. Średnie masy ciała krów nie odbiegają
od mas założonych w celu hodowlanym. Większą masą urodzeniową miały buhajki, osiągając
w 2013 roku wagę 37,5 kg. Różnicą między buhajkami a jałówkami wynosiła 3 kg. Cielęta charakteryzowały się dużymi przyrostami w okresie
odchowu: 900–1009 g odpowiednio dla cieliczek
i 973–1088 g dla buhajków. Należy zauważyć, iż
od 2002 roku buhajki przekroczyły 1000-gramowe przyrosty dobowe. W polskich stadach bydła
limousine cieliło się w ostatnich latach we właściwym okresie od 30,1 do 44,7% krów. Dzięki
systematycznemu wzrostowi populacji krów rasy
limousine pierwiastki i krowy cielące się po raz
drugi stanowią około 40% populacji, mimo stale
rosnącej liczby krów starszych. W 2000 roku tylko 2 krowy były po 7. ocieleniu, a w 2013 roku
było ich już 1416 (12,6%). Wynika z tego, że wydłuża się czas użytkowania krów, co ma szczególne znaczenie ekonomiczne.
Authors’ address:
Tomasz Przysucha
ul. Ciszewskiego 8
02-786 Warszawa
Poland
Influence of lactation stage on selected blood parameters
and biological value of cow milk during pasture season in organic
system of production
TOMASZ SAKOWSKI1, KAMILA PUPPEL2, MARCIN GOŁĘBIEWSKI2,
BEATA KUCZYŃSKA2, EWA METERA1, GRZEGORZ GRODKOWSKI2
Department of Animal Science, Institute of Genetics and Animal Breeding, Polish Academy
of Science
2
1
Abstract: Influence of lactation stage on selected blood parameters and biological value of
cow milk during pasture season in organic system of production. The disproportion between
the cow’s genetically determined ability to produce milk and the limits to improving the energy
value of feed may be the cause of the metabolic
stress of animals kept at organic farms. Negative
energy balance has a major impact on the body’s
hormonal balance and the function of the organs;
it also affects the content of basic components
(protein, fat and lactose) in cows’ milk. The aim
of the study was to investigate changes in the
biological value of organic milk obtained from
high producing dairy cows at different stages of
lactation during pasture season. The study was
carried out on 68 Polish Holstein-Friesian primiparous. 272 milk samples were collected from
cows which were in one of the following phases:
the beginning of lactation (BL): 5–30 days post
partum; peak of lactation (PL): 60–90 days post
partum; full lactation (FL): 120–150 days post
partum; end/final phase of lactation (EL): 250
days post partum. Stage of lactation had an overriding effect on the majority of analyzed milk
constituents including: whey proteins, vitamins
soluble in fat, phospholipids and fatty acids. The
highest levels of lactoferin were found at the
beginning of lactation (BL). At the same time,
the β-hydroxybutyrate (BHBA) concentration
increased, which confirmed that the fast growing
milk yield at the peak of lactation is linked to an
increase in energy demand. The lowest alanine
aminotransferase and non esterified fatty acids
activity was measured during BL. The study has
shown a significant influence of lactation stage
on the biological value of organic milk obtained
from high producing dairy cows during pasture season. In addition, there is evidence that
the organic production system has no influence
on the metabolic profile of cows as the plasma
parameters were within their standard norms.
This might be the result of the positive effect of
grass antioxidants.
Key words: cow’s milk, lactation stage, organic
system
INTRODUCTION
Recent studies have pointed out significant differences in the chemical composition and nutritional quality of milk
and dairy products between organic and
conventional farming systems (Bisig et
al. 2007). Previous studies stated that the
feeding regime had a major effect on the
FA profiles of milk (Dewhurst et al. 2006,
Elgersma et al. 2006) but that other factors (including breed, genotype or both,
the stage and number of lactations) may
also influence milk composition (Walker
96
T. Sakowski et al.
et al. 2004, Chilliard et al. 2007). One
of the biggest issues in organic herds is
to provide high yielding cows with sufficient amounts of nutrients to meet their
needs while maintaining environmental
standards for the composition of the ratio
and type of feed (Hermansen 2003). In
conventional farms negative energy
balance usually appears at the beginning
of lactation (Ingvartsen et al. 2003) and
is associated with a simultaneous rapid
increase in the milk productivity of
animals and limited capacity for feed
intake. Due to seasonal changes in the
composition and quality of the feed cows
from organic farms might also suffer an
energy deficit in other stages of lactation.
A more direct insight into the physiological state of the cow’s organism is
provided by the concentration of certain
metabolites in the blood plasma, milk
or both. It was reported that the level of
β-hydroxybutyric acid (BHBA) presented an accurate picture of the energy
balance in grazing dairy cows. Moreover,
there was a direct link between an excess
of free radicals in cows’ organisms and
decreased disease resistance. There are
many components in plants that might
prevent lipid peroxidation through
limitation of free radicals, stimulation of
antioxidant enzymes activity (i.e.: superoxide dismutase, catalase, glutathione
peroxidase and glutathione reductase) or
both. These properties strongly depend
upon the presence of phenolic compounds
in plants such as flavonoids, tannins,
phenolic acids and terpenes, phenols as
well as certain vitamins (i.e. E, C and A).
Of all plant components the flavonoids,
also called bioflavonoids, are the most
powerful antioxidants. They have the
ability to inhibit the enzymes responsible
for the production of superoxide anions
(i.e. xanthine oxidase, protein kinase
C), as well as the chelation of transition
metals; “cleaning up” free radicals and
initiating and stimulating antioxidant
protection of other factors. Flavonoids
are predominantly found in legumes and
especially grassland legumes such as
clovers (Steinshamn et al. 2008).
There is a direct relationship between
the availability of excess free radicals
and a decrease in animal disease resistance. Therefore, increasing the level of
antioxidants in the diet of cows through
pasturing is a natural way to stimulate
the immune system of cows in organic
production systems. The nutritional
value of organic pastures is mainly
associated with herbage variety (different species of grasses, legumes and
herbs).
The disproportion between the cow’s
genetically determined ability to produce
milk and the limitations on improving
the energy value of the ration may be the
cause of the metabolic stress of animals
kept at organic farms. Negative energy
balance has a major impact on the body’s
hormonal balance and the functioning of
the organs and it also affects the content
of basic components (protein, fat and
lactose) of milk cows. Physiological
changes in the cow’s body, which occur
during lactation, might have significant
influence on the biological value of
milk and milk products. Little is known
about the influence of lactation stage on
the chemical composition and biological value of organic milk obtained from
high-yielding Holstein-Friesian cows
during pasture season.
The aim of the study was to investigate
the influence of lactation stage on the
Influence of lactation stage on selected blood parameters and biological value of cow milk...
biological value of organic milk obtained
from high producing dairy cows during
pasture season.
Animals
The study was carried out on 68 Polish
Holstein-Friesian primiparous cows
at the Polish Organic Dairy Farm located in Juchowo (Western-Pomeranian
Region). Juchowo Farm produces milk
according to the legislation on organic
farming issued by the Polish Ministry of
Agriculture and Rural Development. All
cows were handled in accordance with
the regulations of the Polish Council on
Animal Care, and the Polish Academy
of Science Care Committee reviewed
and approved the experiment and all
procedures carried out in the study. Observations were conducted during two
consecutive calendar years.
97
Treatments and pasture
For better representation, only cows
calved in the spring season (lactating
on pasture) were chosen for the experiment. The nutritional requirements of the
animals and the nutritive value of their
diet were calculated in accordance with
the nutritional standards set out in the
INRATION 4.0 software. The nutrient
composition of the feedstuffs and diet
are presented in Tables 1 and 2.
The feed intake for the organic production systems, including the pasture intake,
was calculated according to standards
based on the difference between herd
demand and recorded intake of supplements. The use of additional vitamins as
supplement to the feed was recorded.
During the study, cows were stripgrazed on a multispecies pasture (Dactylis glomerata L., 12.8%; Phalaris
arundinacea L., 4.2%; Agrostis stolonifera L., 5.8%; Poa pratensis L., 17.5%;
TABLE 1. Nutrient composition of the diets at different stages of lactation
Stage of lactation
Component
BL
PL
(5–30 days (60–90 days
post partum) post partum)
FL
(120–150
days post
partum)
EL
(250 days
post partum)
DM (%)
56.52
60.29
60.55
58.67
Crude protein (CP) (% of DM)
14.55
14.42
14.54
14.71
Acid detergent fiber (ADF)
(% of DM)
24.40
29.11
29.76
28.50
Neutral detergent fiber (NDF)
(% of DM)
38.84
39.35
41.42
41.83
Ether extract (% of DM)
3.86
3.98
4.30
3.89
Ash (% of DM)
5.76
6.38
6.02
5.86
Ca (% of DM)
0.53
0.48
0.51
0.47
P (% of DM)
0.35
0.36
0.36
0.37
UFL (kg of DM–1)
0.90
0.92
0.89
0.97
98
T. Sakowski et al.
TABLE 2. Diet of experimental cow at various stage of lactation
Stage of lactation
Ingredient
Pasture with legumines (% of DM)
BL
(5–30 days
post partum)
PL
(60–90 days
post partum)
71.42
58.84
63.67
Hay (% of DM)
FL
EL
(120–150 days (250 days post
post partum)
partum)
79.30
–
12.07
18.86
7.42
Total roughage (% of DM)
71.42
70.91
82.53
86.72
Concentrates1 (% of DM)
27.64
28.05
16.50
12.27
Supplements2 (% of DM)
0.92
0.96
0.94
0.99
Total (offered) (kg of DM)
21.70
20.70
21.20
20.20
Daily intake (kg)
17.80
19.20
19.80
20.10
Concentrates: sum of cereals, by-products, and commercial concentrate mix.
Supplements: calcium 18%, phosphorus 7%, sodium 8.2%, magnesium 4.5%, vitamin A 1,000,000 IU, vit. D3
100,000 IU, vitamin E 3000 mg, manganese 3000 mg, zinc 9000 mg, copper 1200 mg, iodine 100 mg, cobalt 20
mg, selenium 40 mg.
1
2
Lolium perenne L., 19.4%; Festuca
rubra L., 7.3%; Trifolium repens, 9.4%;
Poa annua, P. trivialis, 8.3%; and broadleaf weeds, 10.3%; others 5.0%) at 7 AM
to 4 PM every day. The cows received
other feed or mineral supplements before
evening milking and had ad libitum
access to fresh water.
Measuring and sampling scheme
Animal performance parameters. 272
milk samples were collected from cows
which were in one of the following phases
(LS): the beginning of lactation (BL):
5–30 days post partum; peak of lactation
(PL): 60–90 days post partum; full lactation (FL): 120–150 days post partum;
end or final phase of lactation (EL): 250
days post partum. The cows were milked
daily at 5.30 AM and 5.30 PM and milk
yield was recorded at each milking.
During the experiment milk samples
were obtained twice from each cow from
the morning and evening milking (according to sampling scheme). Milk was
placed in sterile bottles, preserved with
Mlekostat CC and immediately submitted to the Cattle Breeding Division (Milk
Testing Laboratory of WULS) for composition analysis. The basic parameters
of the milk, i.e. fat, protein, lactose, urea
content, were determined by automated
infrared analysis with a Milkoscan FT
– 120 instrument (Foss Electric; Hillerod, Denmark). An evaluation of the
hygienic status of the milk was based on
somatic cell count using the Somacount
– 150 (Bentley, Warsaw, Poland).
Whey proteins. The determination
of lactoferrin concentration were established using an Agilent 1100 Series
reverse phase high-performance liquid
chromatograph (Agilent Technologies,
Waldbronn, Germany) according to the
methodology described by Puppel et al.
(2014).
Vitamins soluble in fat and β-carotene. Analysis of the fat soluble
vitamins: β-carotene and α-tocopherol
were established using an Agilent 1100
Series reverse phase high-performance
liquid chromatograph (Agilent Technologies, Waldbronn, Germany) and
Zorbax Eclipse XDB C8 column (4.6 ×
× 150 mm, 5 μm film thickness) according to the method described by Puppel et
al. (2013).
Blood. Blood samples were collected
from the animal’s tail vein by an authorized veterinarian (empty test tubes, for
clotted blood, and test tubes containing
lithium heparin were used). Blood was
collected before the morning feeding.
After collection the samples were transported on ice, at temperatures around
0–6°C. In the laboratory blood was centrifuged at 3500 RPM for 10 min and put
to Eppendorf type tubes of 1.5 ml capacity, and then frozen at –30° C for further
analysis.
Levels of the following blood parameters were estimated with the help of
UV-VIS spectrophotometer ULTROSPEC 2000 (PHARMACIA BIOTECH)
in the blood serum probes: β-hydroxybutyric acid (BHBA), enzymatic method,
the BHB RANBUT test (Randox), aspartate aminotransferase (AST), colorimetric method, AST test (Pointe Scientific)
and alanine aminotransferase (ALT),
colorimetric method, ALT test (Pointe
Scientific), non-esterified fatty acids
(NEFA), colorimetric method, NEFA
test (Pointe Scientific).
Statistical analysis
The data obtained were analyzed statistically using a ANOVA procedure by
means of the SPSS 12.0 packet software
(SPSS, Chicago, IL, USA). The mathematical model that describes the influence of lactation stage on analyzed traits
is given by
99
Yij = μ + τi + öij
where:
Yij – the j-th observation (j = 1, 2, …, ni);
μ – common effect for the whole experiment;
τi – the i-th lactation stage effect ((i = BL
(5–30 days), PL (60–90 days), FL
(120–150 days), EL (> 250 days));
öij – the random error present in the j-th
observation on the i-th stage of
lactation.
The level of significance was determined after performing preliminary statistical analyses.
Milk production is a function of the
number and activity of mammary epithelial cells, regardless of lactation stage.
The highest level of protein was observed in EL. A similar trend was noted
in the case of fat concentration. This was
probably due largely to the concentrating
effect of decreasing milk volumes, since
yields of fat and protein decreased with
advancing lactation (Table 3). DePeters
and Cant (1992) observed that the reduction in protein concentration in milk is
often caused by the dilution effect, rather
than its reduced synthesis in the mammary gland, and is always associated
with an increase in milk yield. Similar
results were reported by Auldist et al.
(1998) and Dewhurst et al. (2006). The
lowest fat, protein and dry matter content
in PL was probably caused through the
use of energy from adipose tissue in the
BL (Pedron et al. 1993). At this time the
cow cannot satisfy its energy needs from
feed intake alone, which is still too small
100
T. Sakowski et al.
TABLE 3. Changes in milk performance of analyzed cows during different stages of lactation
Stage of lactation
Item
Sample number
BL
(5–30 days post
partum)
PL
(60–90 days
post partum)
FL
(120–150 days
post partum)
EL
(250 days
post partum)
LSM1 (SEM2)
LSM (SEM)
LSM (SEM)
LSM (SEM)
68
68
68
68
22.7Ac (3.05)
23.5Bd (3.58)
18.3cd (3.21)
15.8AB (3.59)
42.8a (1.1)
38.5b (1.30)
43.4a (1.40)
43.5 (1.60)
30.9 (0.40)
29.3 (0.50)
30.5A (0.50)
33.1B (0.60)
46.9 (0.20)
47.6 (0.30)
47.1 (0.30)
47.5 (0.40)
Somatic cell count (10 ·ml )
95.72 (12.59)
53.09 (11.47)
62.66 (13.25)
69.82 (12.89)
Urea (mg·l–1)
270.5a (18.45)
285.4 (20.32)
279.1 (21.45)
259.5a (23.65)
Milk yield (kg·d–1)
Fat (g·kg–1)
Protein (g·kg )
–1
Aa
Lactose (g·kg–1)
3
–1
a
Ab
a
SEM – standard error of the mean; 2 LSM – least square of mean; values in the same row marked with the same
letters differ significantly AA, BB at P ≤ 0.01; aa, bb at P ≤ 0.05.
1
(Reist et al. 2002) in this lactation phase.
Milk lactose percentages were, however,
very similar for all periods. The content
of lactose in milk is subject to the smallest changes. The higher content of lactose
in organic milk can be explained by the
higher concentrations of sugar in feed
grasses on organic farms. In BL cows
primarily mobilize body fat. Nevertheless, a limited amount of body proteins
will be mobilized as well and can result
in elevated plasma urea concentrations.
The content of urea is influenced by
the following factors: feed composition
and dose, the weight of cows, milk yield,
season, month and lactation period.
During pasture feeding high levels of
urea can be tolerated and even economically justified. Cows grazed ad libitum on
young pasture (excess of easily degradable protein) consume much more protein
than they can turn into milk. Therefore,
the pasture grazing cows may produce
milk with a high level of urea (even
higher than 300 mg·l–1). The urea content
in organic milk samples ranged between
259.5 and 270.5 mg·l–1 (Table 3). Urea
and protein content in milk are indicators of a diet balanced in terms of energy
and protein, so if the protein content is
within normal ranges (3.2–3.8%), and
urea concentration is between 15–30 mg
and 100 m·l–1, it is considered that the
energy and crude protein supply are at an
optimum level (Bendelja et al. 2011).
The main source of fat-soluble vitamin
in milk fat is feed. The concentration of
β-carotene in milk depends on the level
of β-carotene in feed and on the breed of
cow. Reported by Prache et al. (2003),
β-carotene content in pasture herbage
collected between May and June fluctuated between 620–720 mg·kg–1 of DM,
and was significantly reduced in late
August to 430 mg kg–1 DM. In the BL the
lowest content of fat-soluble vitamins in
milk were observed. At the same time,
the BHBA concentration increased,
which may confirm energy demand for
fast growing milk yield in the first lacta-
101
TABLE 4. Changes in analyzed components of milk and blood during different stages of lactation
Stage of lactation
Item
Lactoferin (g·l )
–1
BL
(5–30 days
post partum)
PL
(60–90 days
post partum)
FL
(120–150 days
post partum)
EL
(250 days
post partum)
LSM1 (SE2)
LSM (SE)
LSM (SE)
LSM (SE)
0.283 (0.001)
0.147 (0.001)
0.158 (0.001)
0.330 (0.001)
Vitamin E (μg·dm–3)
1339.7 (15.668)
β-carotene (μg·dm–3)
349.95 (5.365)
598.5 (7.658)
701.6 (6.568)
483.3 (6.547)
BHBA (mmol·dm–3 )
0.613A (0.045)
0.420A (0.025)
0.440A (0.034)
0.421A (0.029)
AST (U·dm–3 )
51.75A (5.895)
49.1B (6.346)
57.25AB (4.985)
56.75AB (5.678)
ALT (U·dm )
14.05 (0.345)
20.2 (0.457)
22.15 (0.587)
22.25A (0.398)
NEFA (g·0.1 kg of milk
fat–1)
0.475A (0.004)
0.580b (0.003)
0.845Ab (0.007)
0.912Ab (0.008)
–3
A
1954.1 (19.896) 28774.7 (25.357) 2411.4 (22.158)
A
A
SEM – standard error of the mean; 2 LSM – least square of mean; values in the same row marked with the same
letters differ significantly AA, BB at P ≤ 0.01; aa, bb at P ≤ 0.05.
1
tion phase (Table 4). The highest level of
β-carotene in milk was achieved in the
EL (701.6 μg·dm–3). The highest vitamins E and A level was observed in the
FL, where energy could be used for synthesis of the antioxidants. Dairy cattle
consuming stored forages are often low
in vitamin E, and vitamin E deficiencies
are frequently observed during the periparturient period. Vitamin E can quench
peroxidation reactions in cell membranes
and is probably the most important antioxidant located in membranes (Putnam
and Comben 1987). In cows near calving, Paterson (1965) reported a positive
relationship between NEFA and the carotenoid content of plasma, suggesting the
ability of bovine adipose tissue to release
β-carotene.
β-hydroxybutyrate acid (BHBA),
along with acetone and acetoacetate, is
considered a ketone. Ketones are produced during the metabolism of non
esterified fatty acids (NEFAs) and volatile fatty acids. BHBA values above 27
mg·dl–1 are considered compatible with
clinical ketosis. Cows with underlying
hepatic lipidosis may have concurrent
elevations in liver leakage enzymes: AST
or cholestatic enzymes ALP. The level
of BHBA concentration in blood is an
indicator of a positive or negative energy
balance in the cow. Additionally, cows
with BHB values above or equal to 12.5
mg·dl–1 (1200 μmol·l–1) were eight times
more likely to experience a left-displaced
abomasum. The highest level of BHBA
was observed in BL – 0.615 mmol·dm–3
(Table 4). Alanine aminotransferase
(ALT) and aspartate aminotransferase
(AST) are important catabolic enzymes,
which play an important role in the liver
function of animals. Alanine aminotransferase activity in cows differs during
certain production periods. The lowest
ALT activity was measured during BL,
while activity increased in the PL, FL,
EL (Table 4). The aspartate aminotransferase activity changes irregularly during
lactation. NEFA concentration reflects
102
T. Sakowski et al.
the mobilization of lipid reserves to
compensate for the imbalance between
nutrients consumed by the cow and
nutrients secreted in milk. Serum NEFA
greater than 0.4 mEq·l–1 has been proposed to identify excessive prepartum NEB. NEFA concentrations were
relatively low because energy balance
becomes positive and cows replete the
mobilized tissue reserves. The highest concentration was found in the EL
(22.5 U·dm–3) and the lowest in the BL
(Table 4). NEFA respond much quicker
than BHBA to homeostasis changes. The
emergence of an energy deficit results
in a rapid increase of blood NEFA, and
its rapid decline. Blood levels of NEFA
usually show a strong variation related
primarily to time of feeding. Radloff et
al. (1966) noted that plasma NEFA levels
decreased at 4 to 6 h after feeding while
blood ketones increased.
CONCLUSION
Stage of lactation had a significant effect
on the most analyzed milk constituents
including: whey proteins, fat soluble
vitamins, phospholipids. The study has
shown a significant influence of lactation
stage on the biological value of organic
milk obtained from high producing dairy
cows during pasture season. In addition, there is evidence that the organic
intensity of the production system has no
influence on the metabolic profile of high
yielded cow’s as the plasma parameters
were in norm.
Acknowledgement
Research was realized within the project
POIG.01.01.02-014-090/09,
entitled
“BIOFOOD – innovative, functional
products of animal origin”, co-financed
by the European Union from the European Regional Development Fund within
the Innovative Economy Operational
Programme 2007–2013.
REFERENCES
AOAC, 1990: Official Methods of Analysis (15th
ed.), Vol. 1. Association of Official Analytical
Chemists, Arlington, VA.
AULDIST M.J., WALSH B.J., THOMSON N.A.,
1998: Seasonal and lactation influences on
bovine milk composition in New Zealand. J.
Dairy Res. 65 (3): 401–411.
BENDELJA D., PRPIĆ Z., MIKULEC N., IVKIĆ
Z., HAVRANEK J., ANTUNAC N., 2011:
Milk urea concentration in Holstein and Simmental cows. Mljekarstvo 61 (1): 45–55.
BISIG W., EBERHARD P., COLLOMB M., REHBERGER B., 2007: Influence of processing on
the fatty acid composition and the content of
conjugated linoleic acid in organic and conventional dairy products – a review. Lait 87: 1–19.
CHILLIARD Y., GLASSER F., FERLAY A.,
BERNARD L., ROUEL J., DOREAU M.,
2007: Diet, rumen biohydrogenation and nutritional quality of cow and goat milk fat. European J. Lipid Sci. Technol. 109: 828–855.
DePETERS E.J., CANT J.P., 1992: Nutritional
factors influencing the nitrogen composition
of bovine milk: A review. J. Dairy Sci. 75:
2043–2070.
DEWHURST R.J., SHIGFIELD K.J., LEE
M.R.F., SCOLLAN N.D., 2006: Increasing the
concentrations of beneficial polyunsaturated
fatty acids in milk produced by dairy cows in
high-forage systems. Anim. Feed Sci. Technol.
131: 168–206.
ELGERSMA A., TAMMINGA S., ELLEN G.,
2006: Modifying milk composition through forage. Anim. Feed Sci. Technol. 131: 207–225.
EN ISO 5509, 2000. Animal and vegetable fats
and oils-preparation of methyl esters of fatty
acids (ISO 5509:2000).
HERMANSEN J.E., 2003: Organic livestock production systems and appropriate development
in relation to public expectations. Livestock
Prod. Sci. 80: 3–15.
INGVARTSEN K.L., DEWHURST R.J.,
FRIGGENS N.C., 2003: On the relationship
between lactational performance and health:
is it yield or metabolic imbalance that cause
production diseases in dairy cattle? A position
paper. Livestock Prod. Sci. 83 (2–3): 277–308.
PEDRON O., CHELI F., SENATORE E., BAROLI D., RIZZII R., 1993: Effect of Body Condition Score at Calving on Performance, Some
Blood Parameters, and Milk Fatty Acid Composition in Dairy Cows. J. Dairy Sci. 76: 2528–
–2535.
PETERSON D.G., KELSEY J.A., BAUMAN
D.E., 2002: Analysis of variation in cis-9,
trans-11 conjugated linoleic acid (CLA) in milk
fat of dairy cows. J. Dairy Sci. 85: 2164–2172.
PRACHE S., PRIOLO A., GROLIER P., 2003:
Effect of concentrate finishing from the caretonoid content of perirental fat in grazing sheep:
its significance to discriminating grass-feed,
concentrate-fed and concentrate-finished grazing lambs. Anim. Sci. 77: 225–234.
PUPPEL K., NAŁĘCZ-TARWACKA T.,
KUCZYŃSKA B., GOŁĘBIEWSKI M., KORDYASZ M., 2013: Effect of different fat supplements on the antioxidant capacity of cows’
milk. Archiv Tierzucht 56 (17): 178–190.
PUPPEL K., KUCZYŃSKA B., NAŁĘCZ-TARWACKA T., SAKOWSKI T., GOŁĘBIEWSKI
M., KUNOWSKA-SLÓSARZ M., BUDZIŃSKI A., GRODZKI H., 2014: Effect of fish
oil and linseed supplementation on the protein
composition of milk from cows with different
β-lactoglobulin phenotype. J. Sci. Food Agri.
94: 1253–1257.
PUTMAN M.E., COMBEN N., 1987: Vitamin E. Vet. Rec. 121: 541–545, doi:10.1136/
vr.121.23.541.
STEINSHAMN H., PURUP S., THUEN E.,
HANSEN-MØLLER J., 2008: Effects of Clover-Grass Silages and Concentrate Supplementation on the Content of Phytoestrogens in
Dairy Cow Milk. J. Dairy Sci. 91: 2715–2725.
RADLOFF H.D., SCHULTZ L.H., HOEKSTRA
W.G., 1966: Relationship of plasma free fatty
acids to other blood components in ruminants
under various physiological conditions 1, 2, 3
and 4. J. Dairy Sci. 49 (2): 179–182.
REIST M., ERDIN D., Von EUW D.,
TSCHUEMPERLIN K., LEUENBERGER H.,
CHILLIARD Y., HAMMON H.M., MOREL
103
C., PHILIPONA C., ZBINDEN Y., KUENZI
N., BLUM J.W., 2002: Estimation of energy
balance at the individual and herd level using
blood and milk traits in high-yielding dairy
cows. J. Dairy Sci. 85 (12): 3314–3327.
WALKER G.P., DUNSHEA F.R., DOYLE P.T.,
2004: Effects of nutrition and management on
the production and composition of milk fat and
protein: a review. Australian J. Agric. Res. 55:
1009–1028.
Streszczenie: Wpływ stadium laktacji wysokowydajnych krów rasy PHF na kształtowanie się
parametrów profilu metabolicznego krwi oraz
bioaktywnych składników ich mleka w trakcie
sezonu pastwiskowego w ekologicznym systemie
produkcji. Dysproporcja między zapotrzebowaniem bytowym krów a możliwością jego pokrycia
powoduje obciążenie metaboliczne organizmu.
W przypadku krów mlecznych główną przyczyną
obciążenia metabolicznego jest brak równowagi
między genetycznie uwarunkowanym potencjałem dużej produkcji mlecznej a ograniczonymi
możliwościami pokrycia potrzeb pokarmowych
energią zawartą w pobranych paszach. Skutkuje
to ujemnym bilansem energii i nadmierną mobilizacją tłuszczu z rezerw organizmu, jak również
zmianą w koncentracji bioaktywnych składników
frakcji białkowej oraz frakcji tłuszczowej. Celem
pracy było określenie wpływu stadium laktacji
na kształtowanie się podstawowego składu chemicznego mleka oraz profilu metabolicznego wysokowydajnych krów w ekstensywnym systemie
żywienia. Badaniami objęto 68 krów rasy polskiej
holsztyńsko-fryzyjskiej (pierwiastki). W trakcie
realizacji doświadczenia pobrano 272 próbki mleka od krów, które znajdowały się w jednym z następujących stadiów laktacji: 5.–30. dzień laktacji (BL); 60.–90. dzień laktacji (szczyt laktacji;
PL); 120.–150. dzień laktacji; powyżej 250. dnia
laktacji (EL). Badania wykazały, że faza laktacji
w istotny sposób kształtowała koncentrację laktoferyny, witaminy E oraz β-karotenu w mleku krów
w trakcie sezonu pastwiskowego. Najwyższą koncentrację laktoferyny wykazano w początkowym
okresie laktacji (BL), podobną zależność wykazano w przypadku kwasu β-hydroksymasłowego
(BHBA). Największą aktywność aminotransferazy alaninowej i wolnych kwasów tłuszczowych
wykazano w końcowej fazie laktacji (EL). Wyniki
104
T. Sakowski et al.
badań potwierdzają, że również w przypadku systemu ekstensywnego wzrost wydajności jest ściśle związany ze wzrostem zapotrzebowania krów
na energię. Uzyskane wartości dla wskaźników
profilu metabolicznego uzyskane dla czterech
faz laktacji znajdowały się na niższym poziomie
względem wartości uzyskiwanych przez krowy
w intensywnym systemie produkcji. Dowodzi to,
że stosowanie systemu ekologicznego gwarantuje
zarówno lepszy pod względem wartości biologicznej produkt finalny, jak i zdrowe zwierzę (bez
zaburzeń metabolicznych).
Authors’ address:
Tomasz Sakowski
Zakład Doskonalenia Zwierząt
Instytut Genetyki i Hodowli Zwierząt PAN
ul. Postępu 1, 05-552 Jastrzębiec
Wólka Kosowska, Poland
KAROLINA WNĘK1, MARCIN GOŁĘBIEWSKI1, TOMASZ PRZYSUCHA1,
ALICJA WOŹNIAK², JERZY WIERZBICKI2
Polish Association of Beef Cattle Producers
1
2
Abstract: Differences in the assessment of beef
carcasses in EUROP system. Classification of
slaughter animals in EUROP system is obligatory for all EU countries. Visual assessment of
beef carcasses determines the level of muscle
and fat in scales from E to P and from 1 to 5. At
the same time beef carcass is classified into one
of five categories of cattle for slaughter from
A to E. Visual assessment is not fully objective
and is fraught with classifier error, which has an
impact on the final assessment of the carcass.
2689 beef carcasses were classified in different categories for slaughter. Assessments were
performed by three classifiers independently
and in the same conditions in the slaughter line.
Based on the results of evaluations of beef carcasses were performed statistical analysis. The
average value for the conformation was class
O, which accounted for 52.66% of all beef carcasses and at a comparable level fat classes 2
and 3 – 39.54, 32.54% respectively, which is
characterized by a low content of meat and average fat content in carcase. CV (coefficient of
variation) for the SE (standard deviation) in
the conformation class was around 3% for the
three categories slaughter A, B and E, and D
was 2.16%. For the fat class regardless of the
category slaughter CV for the SE was three
times larger. The results suggest that visual assessment of beef carcasses is not objective and
is fraught with error evaluator.
INTRODUCTION
Introduced in 1981, EUROP grid is currently the most popular in the European
Union grading system, which allows for
visual determination of conformation
and fatness of the carcass. The primary
purpose of the EUROP is sort carcasses
according to their value for further
processing and to ensure fair payment
to beef producers. Additionally, EUROP
method was developed by countries
trading within the common EU market
to uniform principles and criteria of beef
carcasses assessment.
The conformation score ranges from S
(superior), used to describe rare double-muscled carcasses, via E (excellent)
through to P (poor) and from 1 (low) to
5 (high) for fat cover. Each conformation and fat class is subdivided into low
medium and high classes marked as
“+” for high, “without indication” for
medium and “–” for low, respectively
(Commission Regulation 1249/2008).
According to the Polish regulation,
all large plants that slaughter over 75
head of cattle and over 200 pigs a week
on average during the entire year are
Key words: beef carcass, classification, EUROP obligated to introduce EUROP carcass
system, conformation, fat class
classification system (Pawelec 2010).
106
K. Wnęk et al.
The carcasses are visually evaluated
by adequately trained person who has
a valid license (Choroszy and Choroszy
2011). The main disadvantage of carcass
evaluation by classifiers is subjective
assessment of the carcass, which makes
this system not fully accurate and objective. Moreover, it is essential for performance recording that the measured
phenotype reflects the true genetic value
for the animal with minimal variation
arising from the assessment method.
In response to these issues, there has
been a drive to move away from visual
classification. The modern assessment
systems of carcass grading do not take
into account the small differences in
the quality of the carcass, which often
are the result of breeding improvement
directed to improve the cattle conformation (Cegiełka 2013, Wnęk et al. 2014a).
Sometimes, the determined by classifier
values of the carcass is far away from its
true value.
The aim of the study was to determine
the differences in beef carcasses evaluation with the EUROP grid by independent classifiers.
The material for the analysis consisted
of 2689 beef carcasses (breed Polish
Holstein-Friesian) classified according
to EUROP guidelines contained in the
Commission Regulation No 1249/2008,
including:
– 905 carcasses belonged to A slaughter
category (carcasses of castrated males
aged from 12 to 24 months);
− 427 carcasses belonged to B slaughter
category (carcasses of castrated males
animal aged above 24 months);
− 856 carcasses belonged to D slaughter
category (carcasses of cows);
− 501 carcasses belonged to E slaughter category (carcasses of other male
animal aged above 12 months).
Slaughter and classification were
held in a slaughterhouse ECO-BEEF at
Węgrzynów. Each carcass was classified
by three professional classifiers with
valid certificate. Carcass evaluation was
processed independently and under the
same conditions (including lightening)
in slaughterhouses. The carcasses were
arranged in random order for each repetition. The unified 5-grade scale of carcass
assessment involving fat and conformation evaluation, which has been used by
the classifiers is shown in Table 1. The
results of the carcasses classification
were written on sheets of paper, and then
MS Excel database was created. For
each of the EUROP grades and slaughter
categories coding system presented in
Tables 2 and 3 was applied.
TABLE 1. Description of the EUROP conformation and fat evaluation system
Conformation
class
Carcase
quality
Fat
class
Fat
cover
E
excellent
1
low
U
very good
2
slight
R
good
3
average
O
fair
4
high
P
poor
5
very high
Presented average x– describes the
arithmetic average of three independent
classifications. The experimental data
were evaluated by running ANOVA on
IBM SPSS 21 (Statistical Product and
Service Solution) according to following
statistical model
107
TABLE 2. Coding system of conformation and fat class of beef carcasses
Conformation
Numerical value
Conformation
Numerical value
Conformation
Numerical value
Conformation
Numerical value
Conformation
Numerical value
E
1
U
2
R
3
O
4
P
5
E=
1.75
U=
2.75
R=
3.75
O=
4.75
P=
5.75
E–
1.5
U–
2.5
R–
3.5
O–
4.5
P–
5.5
E+
1.25
U+
2.25
R+
3.25
O+
4.25
P+
5.25
Fat class
Numerical value
Fat class
Numerical value
Fat class
Numerical value
Fat class
Numerical value
Fat class
Numerical value
1
1
2
2
3
3
4
4
5
5
1=
1.75
2=
2.75
3=
3.75
4=
4.75
5=
5.75
1–
1.5
2–
2.5
3–
3.5
4–
4.5
5–
5.5
1+
1.25
2+
2.25
3+
3.25
4+
4.25
5+
5.25
TABLE 3. Coding system of categories slaughter beef carcass
Categories slaughter
Numerical value
A – carcasses of castrated male animal aged from 12 to less than 24 months
1
B – carcasses of castrated male animal aged above 24 months
2
D – carcasses of female animal that has calved
3
E – carcasses of other male animal aged above 12 months
4
Yij = μ + Ai + ej
where:
Yij – dependent variable;
μ – overall mean;
Ai – effect of slaughter category (i =
= 1–4, Table 3);
ej – residual error.
Any significant differences were
present among the means at a 95.0%
confidence level. The analysis of distribution of EUROP grading differences was performed by non-parametric
chi-square test.
The results of conformation and fatness
grading are presented in Table 4. The
most frequent assessment of the confor-
mation was the class O and in the 2 and 3
in fatness (independently of age or sex).
Figures 1 and 2 show the percentage of
carcasses in the various categories of
conformation and fatness. The largest
share of the carcasses were in the O
– 52.66% (for conformation) and categories 2 and 3 – 39.57 and 32.54% (for
fatness) respectively. These carcasses
were characterized by low quantity of
meat and average fat content (Guzek
et al. 2013). Beef production in Poland
TABLE 4. Statistical parameters of evaluations
for carcasses fatness and conformation
Factor
x–
x– conformation
x– fatness
4.58
3.07
Me
4.67
2.92
D0
4.75
2.75
SE
0.735
0.962
108
K. Wnęk et al.
E. 0.1%
U. 2.16%
5. 2.34%
1. 10.75%
P. 27.3%
R. 17.78%
4. 14.8%
O. 52.66%
3. 32.54%
2. 39.57%
FIGURE 1. Percentage of carcasses in the various
conformation categories
FIGURE 2. Percentage share of carcasses in the
various categories of fatness
is mostly based on dairy breeds (Pilarczyk and Wójcik 2007, Litwińczuk and
Grodzki 2014). Contribution of breeding
beef cattle to animal production is minimal – currently less than 1% of the whole
cattle population. Black-and-White cattle
crossed with Holstein-Friesians were the
basic breed – over 85% in the structure
of beef production in Poland (Węglarz
2010). Consequently, in Polish grading
system, dominates class “O” – which
consists more than 60% of all classified
carcasses (Seredyn 2006). Therefore,
our beef producers do not have a strong
argument in prices negotiations.
Table 5 presents the correlation coefficients between the fatness and conformation evaluations. The objective
assessment depends on human judgment,
which can be subjective, and inconsistent (Allen and Finnerty 2000, Wnęk et
al. 2014b). Differences in the assessment
of fat classes were more frequent than
for the carcass conformation (P ≤ 0.05).
Carcass evaluation affects its economic
value and therefore precision and repeatability of carcass grading is necessary.
TABLE 5. The correlation coefficients between
the evaluations carcass fatness and conformation
Fatness
x–
Conformation
x–
SE
Me
–0.28
1.5**
–0.24
SE
–1.94**
0.32
–1.92*
Me
–0.34
–0.07
–0.31
* significance at P ≤ 0.05; **significance at P ≤ 0.01.
Figures 3, 4, 5 and 6 present the
percentage of carcasses according to
the slaughter category and carcass
conformation. For conformation class
E only three carcasses were classified
and the rest were classified in slaughter
category A. In the class P the majority
were carcasses in slaughter category D
– carcasses of adult female, characterized by low dressing percentage. Figure
7, 8, 9, 10 and 11 present the percentage
of carcasses according to the slaughter
category and fat classes. In the slaughter
category D was the majority were carcasses with high fatness. Dairy cows are
of poorer quality livestock (Rycombel
2004).
109
A. 51.72%
A. 48.22%
B. 18.97%
B. 22.64%
D. 13.79%
D. 8.39%
E. 15.52%
E. 20.75%
FIGURE 3. The percentage of the carcasses in the
conformation U
conformation R
A. 36.95%
A. 16.1%
B. 17.41%
B. 8.32%
D. 23.61%
D. 64.53%
E. 22%
E. 11.05%
conformation O
conformation P
A. 20.07%
A. 42.28%
B. 13.15%
B. 21.56%
D. 60.9%
D. 24.77%
E. 5.88%
E. 11.39%
fatness 1
fatness 2
110
K. Wnęk et al.
A. 39.12%
A. 13.45%
B. 14.28%
B. 8.38%
D. 25.28%
D. 39.85%
E. 21.32%
E. 38.32%
fatness 3
FIGURE 10. The percentage of the carcasses in
the fatness 4
A 0.00%
B. 1.6%
D. 59.68%
E. 38.72%
FIGURE 11. The percentage of the carcasses in
the fatness 5
Conformation and fatness grades
largely depends on the age and sex
of animals for slaughter (Raesa et al.
2003, Bureš et al. 2006, Mach et al.
2008). Tables 6 and 7 presents an effect
of slaughter category on the results of
EUROP evaluation for conformation
and fatness. In category slaughter 3 – D
– carcasses of cows, average grade was
5.03 which was an equivalent of P class,
characterized by the lowest level of conformation (Pawelec 2010). The CV for
the SE is more than three times higher
in fat assessments in relation to muscle
assessments independently of slaughter category. Also, SE was higher in fat
classes than conformation class, irrespective of slaughter category. Fat can be
deposited not only in the subcutaneous
tissue, but also between muscle fibers–
–intramuscular fat and carcass evaluation
is based on the profiles of the carcass.
Therefore, such an assessment is usually
TABLE 6. Effect of slaughter category on the results of assessments for conformation
x–
N
1
x–
SE
N
2
x–
SE
N
3
x–
SE
N
4
x–
SE
905
4.33
0.231
427
4.36
0.327
856
5.03
0.218
501
4.45
0.292
SE
905
0.14
0.064
427
0.12
0.117
856
0.1
0.059
501
0.14
0.009
Me
905
4.33
0.237
427
4.37
0.337
856
5.04
0.224
501
4.47
0.298
CV (%)
905
3.38
0.157
427
3.03
0.3
856
2.16
0.125
501
3.41
0.221
Factor
111
TABLE 7. Effect of slaughter category on the results of assessments for fatness
Factor
x–
N
x–
905
SE
Me
1
SE
N
x–
2.92
0.713
427
905
0.26
0.301
905
2.95
0.757
CV (%) 905
9.7
2
SE
N
x–
2.87
0.788
856
427
0.23
0.286
427
2.87
0.822
11.933 427
8.82
3
4
SE
N
x–
3.04
1.155
501
3.58
0.951
856
0.21
0.282
501
0.25
0.314
856
3.07
1.167
501
3.61
0.978
11.557 856
7.81
11.051 501
7.59
10.085
SE
fraught with some error. Lack of precision and accuracy in the classification of
carcasses can be also caused by classifier
fatigue, abnormal color of fat, or/and fat
thickness that accompanies with high
percentage of muscle tissue (Craigie et
al. 2012, Cegiełka 2013).
grading on the basis of properties and
market requirements, depending on software and system calibration (Craigie et
al. 2012). In practice, a visual assessment
of the EUROP system performs only one
person, so it is not fully representative.
CONCLUSIONS
This research was supported by the
project, entitled “Optymalizacja produkcji wołowiny w Polsce, zgodnie ze
strategią »od widelca do zagrody«”
(“Optimizing of beef production in
Poland according to »from fork to farm
strategy«”), co-financed by the European
Regional Development Fund under the
Innovative Economy Operational Programme (Contract UDA-POIG.01.03.01-00-204/09-08) – Task 2a.
Improving the competitiveness and
profitability of Polish beef production
requires an increase in the supply of
good beef quality livestock, mainly
terminal
crossbreeds
(Jasiorowski
2003, Seredyn 2006). An important
factor in the beef cattle herds is selection of appropriate breed, which should
be dependent on production system,
nutrition and knowledge of the breeder
(Przysucha et al. 2007). Crossbreeding
dairy breeds with beef breeds is the most
suitable method for improving beef livestock quality (Węglarz 1997, Trela et al.
2002, Voříšková et al. 2002, Bartoń et al.
2005). An important factor in the growth
of consumer satisfaction, as well as the
supply of beef would be to improve the
precision and accuracy of the evaluation
beef carcasses and automated technologies of objective grading systems offers
such opportunity. The objective grading
system has the ability to accurate carcass
Acknowledgements
REFERENCES
ALLEN P., FINNERTY N., 2000: Objective beef
carcass classification. A report of a trial of three
via classification systems. Teagasc and Department of Agriculture, Food and Rural Development Publication, Dublin: 1–34.
BARTOŇ L., KUDRNA V., BUREŠ D.,
KREJČOVÁ M., ZAHRÁDKOVÁ R., 2005:
Factors affecting fatty acid composition and
dietetic value of beef. Anim. Sci. Pap. Rep.
23 (4): 261–267.
BUREŠ D., BARTOŇ L., ZAHRÁDKOVÁ R.,
TESLÍK V., KREJČOVÁ M., 2006: Chemical
composition, sensory characteristics, and fatty
112
K. Wnęk et al.
acid profile of muscle from Aberdeen Angus,
Charolais, Simmental, and Hereford bulls.
Czech J. Anim. Sci. 51 (7): 279–284.
CEGIEŁKA A., 2013: Przegląd rozwoju i wykorzystania analizy obrazu wideo (VIA) do oceny
tusz wołowych jako alternatywy wobec systemu EUROP i innych subiektywnych systemów.
Gosp. Mięsna 01: 22–23.
CHOROSZY B., CHOROSZY Z., 2011: Przydatność bydła simentalskiego do produkcji wołowiny. Wiad. Zoot. 49, 4: 69–76.
Commission Regulation (EC) 1249/2008 of 10
December 2008.
CRAIGIE C.R., NAVAJAS E.A., PURCHAS
R.W., MALTIN C.A., BÜNGER L., HOSKIN
S.O., ROSS D.W., MORRIS S.T., ROEHE R.,
2012: A review of the development and use
of video image analysis (VIA) for beef carcass evaluation as an alternative to the current
EUROP system and other subjective systems.
Meat Sci. 92: 307–318.
GUZEK D., GŁĄBSKA D., KONARSKA M.,
WIERZBICKA A., 2013: Evaluation of the
relationship between intramuscular fat and
connective tissue quantity in beef rib eye cross
section, measured using a computer image
analysis, with confirmation and fat class of
carcasses. J. Res. Appl. Agric. Engng. 58 (2):
43–46.
JASIOROWSKI H., 2003: Ocena stanu produkcji
żywca wołowego w Polsce i Unii Europejskiej
w okresie przedakcesyjnym. In: Materiały
szkoleniowe SAPARD PL-06-02/00: 4.
LITWIŃCZUK Z., GRODZKI H., 2014: Stan hodowli i chowu bydła w Polsce oraz czynniki
warunkujące rozwój tego sektora. Przegl. Hod.
6: 1–4.
MACH N., BACH A., VELARDE A., DEVANT
M., 2008: Association between animal, transportation, slaughterhouse practices, and meat
pH in beef. Meat Sci. 78, 232–238.
PAWELEC A., 2010: System EUROP klasyfikacja
tusz zwierząt rzeźnych. Przemysł Spożywczy
03: 12–14.
PILARCZYK R., WÓJCIK J., 2007: Comparison of calf rearing results and nursing cow
performance in various beef breeds managed
under the same conditions in north-western Poland. Czech J. Anim. Sci. 52 (10): 325–333.
PRZYSUCHA T., GRODZKI H., SLÓSARZ J.,
2007: Wpływ masy ciała krowy, kolejności
i sezonu ocielenia oraz płci masy cielęcia przy
urodzeniu na wyniki odchowu cieląt rasy salers. Med. Wet. 63: 357–359.
RAESA K., BALCAENA A., DIRINCKB P., De
WINNEB A., CLAEYSA E., DEMEYERA D.,
De SMET S., 2003: Meat quality, fatty acid
composition and flavour analysis in Belgian
retail beef. Meat Sci. 65: 1237–1246.
RYCOMBEL D., 2004: Rynek żywca wołowego
w Polsce – stan aktualny i perspektywy po integracji. Hodowla i produkcja bydła mięsnego.
In: Materiały konferencyjne Poznań 8 października 2004. POLAGRA FARM: 19–23.
SEREDYN K., 2006: Wartość rzeźna tusz
wołowych w Polsce i ich pozycja na rynku
wspólnotowym. Retrieved from: http://www.
ipmt.waw.pl/content/File/Seredyn.pdf.
TRELA J., WICHŁACZ H., CHOROSZY Z.,
2002: Quality of meat from crosses of cows of
dairy breeds with beef bulls. Anim. Sci. Pap.
Rep. 20 (1): 229–234.
WĘGLARZ A., 1997: Estimate of commercial
crossing results between Black-and-White cattle and White beef breeds from Italy. Part II.
Slaughter value. Act. Agr. et Silv. 35: 75–91.
WĘGLARZ A., 2010: Quality of beef from semi-intensively fattened heifers and bulls. Anim.
Sci. Pap. Rep. 28 (3): 207–218.
WNĘK K., GOŁĘBIEWSKI M., PRZYSUCHA T., 2014a: System oceny obiektywnej
tusz wołowych. Przegl. Hod. 5: 19–21.
WNĘK K., GOŁĘBIEWSKI M., PRZYSUCHA T., WÓJCIK A., 2014b: Powtarzalność
i dokładność oceny wizualnej tusz wołowych
w systemie EUROP. Farmer 5: 155–159.
VOŘÍŠKOVÁ J., FRELICH J., ŘÍHA J., ŠUBRT
J., 2002: Relationships between parameters of
meat performance in Czech Pied bulls and their
crossbreds with beef. Czech J. Anim. Sci. 47
(9): 357–364.
Streszczenie: Różnice w ocenie tusz wołowych
w systemie EUROP. Klasyfikacja tusz zwierząt
rzeźnych w systemie EUROP jest obowiązkowa dla wszystkich państw UE. Wizualna ocena
tusz wołowych określa poziom umięśnienia oraz
otłuszczenia w pięciostopniowych skalach od E
do P i od 1 do 5. Jednocześnie każda tusza wołowa klasyfikowana jest do jednej z pięciu kategorii bydła rzeźnego od A do E. Niestety wizualna
ocena nie jest w pełni obiektywna i jest obarczona
błędem oceniającego, co ma wpływ na ostateczną
ocenę tuszy. Sklasyfikowano 2689 tusz wołowych
w różnych kategoriach rzeźnych. Ocen dokonywało trzech klasyfikatorów niezależnie od siebie
i w tych samych warunkach panujących na linii
ubojowej. Na podstawie uzyskanych ocen dokonano analizy statystycznej. Najczęściej występującą klasą umięśnienia była klasa O, co stanowiło 52,66% wszystkich sklasyfikowanych tusz.
W klasie otłuszczenia były to na porównywalnym
poziomie dwie klasy: 2 i 3 – 39,57 i 32,54%, co
charakteryzuje tusze o małej zawartości mięsa
i średniej zawartości tłuszczu. CV dla SE wynosił
dla klasy umięśnienia około 3% dla trzech kategorii rzeźnych: A, B i E, a dla D wynosił 2,16%. Dla
klasy otłuszczenia niezależnie od kategorii rzeź-
113
nej CV w przypadku SE był trzy razy większy.
Otrzymane wyniki sugerują, że wizualna ocena
tusz wołowych nie jest obiektywna i jest obarczona błędem oceniającego.
Authors’ address:
Karolina Wnęk
Poland
Agriculture
Animal Science
Land Reclamation
Editorial Board
Bogdan Brzeziecki
Ewa Dobrowolska
Włodzimierz Kluciński
Anna Kołłajtis-Dołowy
Andrzej Lenart
Małgorzata Łobocka
Józef Mosiej
Jan Niemiec
Arkadiusz Orłowski
Maria Parlińska
Aurelia Radzik-Rant
Stanisław Stępka
Marek Szyndel
Czesław Waszkiewicz
Distribution
Annals are distributed by the Bookshop
of Warsaw University of Life Sciences
Press, 166 Nowoursynowska St., Warsaw,
Poland.
WARSAW UNIVERSITY
166 Nowoursynowska St., 02-787 Warsaw
Poland, tel. (48 22) 593 55 20
www.wydawnictwosggw.pl
Agriculture
Animal Science
Land Reclamation
Annals of Warsaw University of Life
Sciences were originally published in 1957
as Zeszyty Naukowe SGGW (Scientific Fascicles of SGGW). In 1980 the name was changed to Annals of Warsaw
University of Life Sciences.
The Annals (5 subject series) are published once or twice a year and will carry previously unpublished papers that are mainly
in English, but also in French, German or
Russian, followed by a short summary in
Polish. Manuscripts for publication should
be typewritten and submitted to the Warsaw
University of Life Sciences Press in two
copies. Papers submitted for consideration
by the Editorial board should not exceed 0.5
of a printed sheet (about 11 pages including illustrations, and should consist of the
following elements: 1) name and surname
of the author, 2) title of the paper, 3) abstract
(about 20 lines), 4) text of the paper, 5) date
when the paper was sent to the Warsaw University of Life Sciences Press and mailing
address of the author, 6) summary (one page),
7) tables and figures with captions. Authors
receive twenty five offprints free of change.

Annals of Warsaw University of Life Sciences

Transkrypt

Podobne dokumenty