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Celem pracy było zbadanie zależności między zawartością mocznika w mleku a takimi czynnikami, jak: numer laktacji, faza laktacji, miesiąc i sezon pobrania próby, wiek krów przy wycieleniu, poziom wydajności mleka i zawartość białka. Do obliczeń wykorzystano dane z 7731 próbnych udojów 1078 krów rasy polskiej holsztyńsko-fryzyjskiej odmiany czarno-białej. Próbne udoje z pierwszej, drugiej i trzeciej laktacji wykonano w okresie od grudnia 2010 roku do grudnia 2011 roku. Obliczenia wykonano przy użyciu procedury MIXED z pakietu SAS/STAT. Zastosowano model liniowy mieszany, w którym parametry estymowane były za pomocą metody największej wiarogodności z ograniczeniami (REML). Średnie najmniejszych kwadratów dla efektów stałych w modelu porównano testem Tukeya-Kramera. Stwierdzono, że laktacja pierwsza różniła się istotnie od laktacji drugiej i trzeciej pod względem zawartości mocznika w mleku, natomiast między laktacją drugą i trzecią nie występowały istotne różnice. U pierwiastek zawartość mocznika w mleku rosła przez cały okres laktacji, natomiast u krów starszych tylko do siódmego, ósmego miesiąca laktacji. Nie stwierdzono statystycznie istotnych różnic między zawartością mocznika w tych samych fazach sąsiednich laktacji, tzn. pierwszej i drugiej oraz drugiej i trzeciej. Natomiast między laktacją pierwszą i trzecią statystycznie istotne różnice w zawartości mocznika wystąpiły tylko w 9. i 10. miesiącu laktacji. Zmiany zawartości mocznika związane z sezonem pobrania próby miały różny charakter w zależności od numeru laktacji. W laktacji pierwszej najniższa zawartość mocznika w mleku wystąpiła w sezonie wiosennym, a najwyższa w sezonie jesiennym. Tendencja ta nie powtórzyła się w kolejnych laktacjach, tj. drugiej i trzeciej. Odnotowano, że wraz ze wzrostem zawartości białka w mleku rosła również zawartość mocznika w mleku. Podobnie, wraz ze wzrostem wydajności mleka rosła zawartość mocznika w mleku.
The objectives of this study were to analyze the genetic properties of three measures of lactation persistency in Polish Holstein-Friesian cows, and possibly to choose one measure which could be used for estimation of breeding value for lactation persistency in the Polish dairy cattle population.Data included 117,327 first three lactations of 110,141 cows calved in 1995-2009. The lactation curie model of Ali and Schaeffer was fitted to test-day milk yields. The first definition of persistency (P2:1)was milk yield in the second 100 days in milk (DIM) divided by yield in the first 100 DIM. The second definition (P3:1) was milk yield in the third 100 DIM divided by yield in the first 100 DIM, and the third definition (Pd) was milk yield at 280 DIM divided by milk yield at 60 DIM. The multipletrait REML method was applied for (co)variance component estimation. Heritabilities for three measures of persistency were very low, and ranged from 0.01 to 0.08. Genetic correlations were highest between P3:1 and Pd (0.96-0.99), and lowest between P2:1 and Pd (0.66-0.81),in the first three lactations. The correlations between 305-d milk yield and P3:1 or Pd in each of the first three lactations, and P2:1 in the second lactation, were negative and moderate. The phenotypic correlations between 305-d milk yield and persistency measures were low in the first three lactations.The phenotypic correlation between milk yield and Pd in each lactation was almost the same (0.14-0.15); the correlation between milk yield and P3:1 (0.11-0.17) or P2:1 (0.08-0.13) showed little variation in the first three lactations. All three compared measures of persistency were low-heritable and practically uncorrelated with total milk yield of 305-d lactations, so any of them could be used in the breeding program. However, the Pd measure could be recommended for use in practice because it is easy to calculate and interpret.
The aim of the study was to estimate the genetic parameters of milk fat-to-protein ratio in the first three lactations of Polish Holstein-Friesian cows. Data included 104 875 test-day records of 6299 cows calving from years 2000–2012. Genetic parameters were estimated with a multitrait random regression model using the Bayesian method via Gibbs sampling. The linear model for fat-to-protein ratio and milk traits (milk yield, lactose percentage, milk urea concentration) included fixed herd-test-day effect, fixed regressions within age at calving by season of calving subclasses, and random regressions for additive genetic and permanent environmental effects. All regressions were modelled using fourth-order Legendre polynomials. The average daily heritability of fat-to-protein ratio ranged from 0.24 to 0.31. Fat-to-protein ratio was negatively genetically correlated with milk yield for almost every day in milk in each lactation, with means of −0.52, −0.24 and −0.05 in the first, second and third lactations, respectively. Average genetic correlations of fat-to-protein ratio with lactose percentage and milk urea concentration were rather low or close to zero (−0.08 to 0.10) except for the genetic correlation with milk urea content in the second lactation (0.32). The results suggest that fat-to-protein ratio is a heritable trait and might be used in the selection of Polish Holstein-Friesians assuming that the relationship between fat-to-protein ratio and economically important traits will be investigated.
The objective of this study was to estimate genetic correlations of lactose percentage and urea concentration in milk with conformation traits related to udder and legs of Polish Holstein-Friesian cows. Data consisted of 5,813 test-day records and type scores of 791 primiparous cows. The analysis involved two descriptive traits (udder, feet and legs, scored from 50 to 100) and 11 linearly scored traits (describing udder: fore udder height, rear udder height, central ligament, udder depth, udder width, fore teat placement, teat length, rear teat placement; describing legs: rear legs - side view, foot angle, rear legs - rear view; on a scale of 1 to 9). Genetic correlations were calculated based on (co)variances estimated using the Bayesian method via Gibbs sampling and the multitrait animal model. Genetic correlations between lactose content and conformation traits ranged from -0.18 to 0.23, while those between milk urea concentration and conformation traits ranged between -0.02 and 0.43, respectively. Absolute values of average genetic correlations with daily lactose percentage exceeded 0.15 only for udder (descriptive trait) and several linearly scored traits, i.e. central ligament, udder depth, rear teat placement, and rear legs - rear view. Milk urea content was weakly or moderately genetically correlated with six type traits: udder, and five linearly scored traits: fore udder height, central ligament, udder width, teat length, and rear legs - side view. Absolute values of genetic correlations between these traits exceeded 0.15. Our results showed that type traits connected with udder were more highly genetically correlated with both lactose and milk urea contents than type traits describing legs. It meant that an increase in both lactose percentage and urea concentration in milk might be expected as an indirect response to selection for better udder, whereas selection for improvement of legs would not affect lactose percentage and milk urea content.
Genetic parameters for lactose percentage in the milk of Polish Holstein-Friesian cows were estimated using 48,859 test day records from six lactations of 8,418 cows and the Gibbs sampling method. The multiple-trait random regression model was applied for data from the first and subsequent (up to the sixth) lactations treated as two traits. Variance components and heritabilities changed in a similar way through the first and subsequent lactations, reaching the highest values at peripheries and relatively stable values in the middle of lactations. All estimates were smaller in the first than in the later parities. Heritabilities of daily lactose percentage ranged from 0.17 to 0.31 with a mean of 0.24 (SD=0.034), and from 0.23 to 0.36 with a mean of 0.28 (SD=0.026) in first and subsequent lactations. Genetic correlations for lactose percentage between the same days of the first and subsequent parities were less than 0.30, with the average equal to 0.26 (SD=0.047) and the minimum (less than 0.15) occurring in the first days after calving.
The purpose of this study was to find early indicators of cow fertility. Genetic correlations of two types of conformation evaluations, routine and modified, with reproduction traits were estimated. Data consisted of type evaluations and fertility measures of primiparous Holstein-Friesian cows born from 2005 to 2006. The number of records ranged between 4731 and 8041 depending on the trait. Type traits with intermediate optima were evaluated using routine and modified scales. In the modified system, the more desirable form of a trait received the higher score. A multi-trait animal model and Gibbs sampling were applied. Among modified type traits the highest genetic correlations were found between non-return rates for cows and rear legs side view (–0.36), between days open and rump angle (0.36), and between interval from calving to first insemination and rump angle (0.35). Genetic correlations of routine type traits with fertility measures were low for udder traits and rump angle (–0.08 to 0.10) and moderate for leg traits (–0.34 to 0.44) and body depth (–0.41 to 0.36). Modified scores for rear legs side view and rump angle, and routine scores for body depth and foot angle may be used as early indicators of cow fertility in Polish Holstein-Friesians
Daughter yield deviations (DYDs) of bulls and yield deviations (YDs) of cows, besides estimated breeding values (EBVs), are standard measures of animals’ genetic merits in routine genetic evaluations worldwide. In this contribution, we first point out differences and similarities between DYDs and EBVs calculated for milk, fat and protein yields. While the latter measure represents the additive polygenic value of an animal, the former consists of both the additive polygenic and residual components. Then, a summary of DYDs and YDs calculated for the Polish population of dairy cattle is presented. The estimated correlations between DYDs and EBVs are generally high, but vary considerably depending on the minimum number of daughters used for calculation of DYDs and on the accuracy of calculated DYDs. Using DYDs estimated for each production year for 16 452 bulls, we demonstrate how to use DYDs for the validation of genetic trend estimated in the model used for genetic evaluation. Based on genotypic data of 252 bulls, we show that DYDs can be used for the estimation of candidate gene effects. For each of the yield traits, the within-bull genetic trend was relatively high, ranging between 1.39% of genetic standard deviation per production year for milk and 7.67% of genetic standard deviation per production year for fat, both in the 2nd lactation. Out of 8 polymorphisms tested, 5 showed a significant correlation with DYD, with the highest effect attributed to the polymorphism within the leptin receptor gene, whose additive effect was estimated as 247.33 kg of milk at 2nd parity.
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