Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model

Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.     

Effects of stage of pregnancy on variance components,daily milk yields and 305-day milk yield in Holstein cows,as estimated by using a test-day model

Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (P<0.05) greater than that after the first calving. Therefore, we conclude that differences between the negative effects of early pregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open to maximize lifetime productivity in dairy cows.     

Energy Metabolites,Lipid Variables and Lactation Performance of Periparturient Murrah Buffaloes (Bubalus bubalis) Fed on Diet Supplemented with Inorganic Chromium

The aim of this study was to elucidate the effects of chromium (Cr) supplementation as inorganic Cr (CrCl₃?·?6H₂O) on energy balance, lipid peroxidation, and lactation performance in periparturient Murrah buffaloes. Twenty-four multiparous Murrah buffaloes according to lactation, parity, body mass, and expected calving date were divided equally. Experimental buffaloes were randomly assigned to four treatment diets: a control diet and three diets with an inorganic Cr supplementation at 0.5, 1.0, and 1.5 mg of Cr/kg dry matter (DM), respectively from 60 days before expected calving date until 60 days of lactation. Milk productions of buffaloes were recorded every day until 60 days in milk. Blood samples were collected at days ?60, ?45, ?30,?21, ?15, ?7, ?3, 0, 7, 15, 21, 30, 45, and 60 days relative to actual calving for determination of plasma glucose, nonesterified fatty acid (NEFA), thiobarbituric acid reactive substance (TBARS), total cholesterol, total protein, albumin, blood urea nitrogen (BUN), and minerals. Adding inorganic Cr to the diet of Murrah buffaloes increased milk yield. Percentage of fat and total solid yield increased significantly through the experiment in the Cr-supplemented group. At the day of calving, buffaloes showed a decrease in dry matter intake (DMI), plasma glucose, and zinc (Zn) and Cr concentrations. In contrast, plasma NEFA, TBARS, and copper (Cu) levels were found highest at the day of calving among all groups. Cr supplementation increased peripheral blood glucose concentration while decreased level of NEFA and TBARS was recorded in Cr-fed buffaloes. Supplemental Cr had no effect on plasma cholesterol, total protein, albumin, and BUN in periparturient period. Dietary Cr supplementation had positive effect on plasma Cr concentration, but the plasma concentration of Cu, Zn, and iron (Fe) was not affected by different dietary Cr level supplementation. The results suggest that dietary inorganic Cr supplementation improved milk yield by reducing negative energy balance and lipid peroxidation in buffaloes during periparturient period.     

Analysis of culling probability in dairy buffalo using survival models

In order to contribute to the genetic breeding programs of buffaloes, this study aimed to determine the influence of environmental effects on the stayability (ST) of dairy female Murrah buffalo in the herd. Data from 1016 buffaloes were used. ST was defined as the ability of the female to remain in the herd for 1, 2, 3, 4, 5 or 6 years after the first calving. Environmental effects were studied by survival analysis, adjusted to the fixed effects of farm, year and season of birth, class of first-lactation milk yield and age at first calving. The data were analyzed using the LIFEREG procedure of the SAS program that fits parametric models to failure time data (culling or ST = 0), and estimates parameters by maximum likelihood estimation. Breeding farm, year of birth and first-lactation milk yield significantly influenced (P < 0.0001) the ST to the specific ages (1 to 6 years after the first calving). Buffaloes that were older at first calving presented higher probabilities of being culled 1 year after the first calving, without any effect on culling at older ages. Buffaloes with a higher milk yield at first calving presented a lower culling probability and remained for a longer period of time in the herd. The effects of breeding farm, year of birth and first-lactation milk yield should be included in models used for the analysis of ST in buffaloes.     

Purging of inbreeding depression within the Irish Holstein-Friesian population

The objective of this study was to investigate whether inbreeding depression in milk production or fertility performance has been partially purged due to selection within the Irish Holstein-Friesian population. Classical, ancestral (i.e., the inbreeding of an individual''s ancestors according to two different formulae) and new inbreeding coefficients (i.e., part of the classical inbreeding coefficient that is not accounted for by ancestral inbreeding) were computed for all animals. The effect of each coefficient on 305-day milk, fat and protein yield as well as calving interval, age at first calving and survival to second lactation was investigated. Ancestral inbreeding accounting for all common ancestors in the pedigree had a positive effect on 305-day milk and protein yield, increasing yields by 4.85 kg and 0.12 kg, respectively. However, ancestral inbreeding accounting only for those common ancestors, which contribute to the classical inbreeding coefficient had a negative effect on all milk production traits decreasing 305-day milk, fat and protein yields by -8.85 kg, -0.53 kg and -0.33 kg, respectively. Classical, ancestral and new inbreeding generally had a detrimental effect on fertility and survival traits. From this study, it appears that Irish Holstein-Friesians have purged some of their genetic load for milk production through many years of selection based on production alone, while fertility, which has been less intensely selected for in the population demonstrates no evidence of purging.     

Environmental effects on lactation curves included in a test-day model genetic evaluation

A large number of environmental factors affect the daily milk production of a cow. Lactation curves included in the French test-day model are modelled as a function of days in milk with semi-parametric curves (splines). The proper modelling of environmental effects in the test-day analysis was investigated using test-day records collected from the first three lactations of French Montbéliarde cows from 1988 to 2005. Four lactation-curve effects describing calving month, length of dry period, age at calving and gestation defined within parity-class were fitted. The shape of lactation curves did not depend on year of calving, which can be modelled as a constant over the whole lactation. To reduce computational requirements and time, data were pre-adjusted in a first step for fixed effects with no year interaction, and then used for genetic evaluation. Correlations for each lactation between 305-day estimates of genetic and permanent environment effects computed using pre-adjustment factors obtained at a 4-year interval were virtually one. The use of a two-step procedure had a very limited impact on the estimates of genetic and permanent environment effects. The minimum correlations with values estimated with a one-step procedure were 0.9984 and 0.9974, respectively. The knowledge of systematic environmental effects affecting the cow daily yield through lactation curves offers interesting perspectives to predict future daily milk production.     

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

We analyzed 152,145 test-day records from 7317 first lactations of Holstein cows recorded from 1995 to 2003. Our objective was to model variations in test-day milk yield during the first lactation of Holstein cows by random regression model (RRM), using various functions in order to obtain adequate and parsimonious models for the estimation of genetic parameters. Test-day milk yields were grouped into weekly classes of days in milk, ranging from 1 to 44 weeks. The contemporary groups were defined as herd-test-day. The analyses were performed using a single-trait RRM, including the direct additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. The mean trend of milk yield was modeled with a fourth-order orthogonal Legendre polynomial. The additive genetic and permanent environmental covariance functions were estimated by random regression on two parametric functions, Ali and Schaeffer and Wilmink, and on B-spline functions of days in milk. The covariance components and the genetic parameters were estimated by the restricted maximum likelihood method. Results from RRM parametric and B-spline functions were compared to RRM on Legendre polynomials and with a multi-trait analysis, using the same data set. Heritability estimates presented similar trends during mid-lactation (13 to 31 weeks) and between week 37 and the end of lactation, for all RRM. Heritabilities obtained by multi-trait analysis were of a lower magnitude than those estimated by RRM. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. RRM using B-spline and Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data.     

Genetic correlations between production and disease traits during first lactation in Holstein cows

The aim of this study was to estimate genetic correlations between milk yield, somatic cell score (SCS), mastitis, and claw and leg disorders (CLDs) during first lactation in Holstein cows by using a threshold–linear random regression test-day model. We used daily records of milk, fat and protein yields; somatic cell count (SCC); and mastitis and CLD incidences from 46 771 first-lactation Holstein cows in Hokkaido, Japan, that calved between 2000 and 2009. A threshold animal model for binary records (mastitis and CLDs) and linear animal model for yield traits were applied in our multiple trait analysis. For both liabilities and yield traits, additive genetic effects were used as random regression on cubic Legendre polynomials of days on milk. The highest positive genetic correlations between yields and disease incidences (0.36 for milk and mastitis, 0.56 for fat and mastitis, 0.24 for protein and mastitis, 0.32 for milk and CLD, 0.44 for fat and CLD and 0.31 for protein and CLD) were estimated at about the time of peak milk yield (36 to 65 days in milk). Selection focused on early lactation yield may therefore increase the risk of mastitis and CLDs. The positive genetic correlations of SCS with mastitis or CLD incidence imply that selection to reduce SCS in the early stages of lactation would decrease the incidence of both mastitis and CLD.     

Milk yield persistency in Brazilian Gyr cattle based on a random regression model

With the objective of evaluating measures of milk yield persistency, 27,000 test-day milk yield records from 3362 first lactations of Brazilian Gyr cows that calved between 1990 and 2007 were analyzed with a random regression model. Random, additive genetic and permanent environmental effects were modeled using Legendre polynomials of order 4 and 5, respectively. Residual variance was modeled using five classes. The average lactation curve was modeled using a fourth-order Legendre polynomial. Heritability estimates for measures of persistency ranged from 0.10 to 0.25. Genetic correlations between measures of persistency and 305-day milk yield (Y305) ranged from -0.52 to 0.03. At high selection intensities for persistency measures and Y305, few animals were selected in common. As the selection intensity for the two traits decreased, a higher percentage of animals were selected in common. The average predicted breeding values for Y305 according to year of birth of the cows had a substantial annual genetic gain. In contrast, no improvement in the average persistency breeding value was observed. We conclude that selection for total milk yield during lactation does not identify bulls or cows that are genetically superior in terms of milk yield persistency. A measure of persistency represented by the sum of deviations of estimated breeding value for days 31 to 280 in relation to estimated breeding value for day 30 should be preferred in genetic evaluations of this trait in the Gyr breed, since this measure showed a medium heritability and a genetic correlation with 305-day milk yield close to zero. In addition, this measure is more adequate at the time of peak lactation, which occurs between days 25 and 30 after calving in this breed.     

Comparison of non-linear models to describe the lactation curves for milk yield and composition in buffaloes (Bubalus bubalis)

In order to describe the lactation curves of milk yield (MY) and composition in buffaloes, seven non-linear mathematical equations (Wood, Dhanoa, Sikka, Nelder, Brody, Dijkstra and Rook) were used. Data were 116 117 test-day records for MY, fat (FP) and protein (PP) percentages of milk from the first three lactations of buffaloes which were collected from 893 herds in the period from 1992 to 2012 by the Animal Breeding Center of Iran. Each model was fitted to monthly production records of dairy buffaloes using the NLIN and MODEL procedures in SAS and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination root means square error (RMSE), Durbin–Watson statistic and Akaike’s information criterion (AIC). The Dijkstra model provided the best fit of MY and PP of milk for the first three parities of buffaloes due to the lower values of RMSE and AIC than other models. For the first-parity buffaloes, Sikka and Brody models provided the best fit of FP, but for the second- and third-parity buffaloes, Sikka model and Brody equation provided the best fit of lactation curve for FP, respectively. The results of this study showed that the Wood and Dhanoa equations were able to estimate the time to the peak MY more accurately than the other equations. In addition, Nelder and Dijkstra equations were able to estimate the peak time at second and third parities more accurately than other equations, respectively. Brody function provided more accurate predictions of peak MY over the first three parities of buffaloes. There was generally a positive relationship between 305-day MY and persistency measures and also between peak yield and 305-day MY, calculated by different models, within each lactation in the current study. Overall, evaluation of the different equations used in the current study indicated the potential of the non-linear models for fitting monthly productive records of buffaloes.     

Effect of Bromocryptine on hormones and milk secretion in Murrah buffaloes ( Bubalus bubalis)

An experiment was carried out on 10 advance pregnant Murrah buffaloes to determine the role of hormones in milk secretion around parturition. Experimental animals were administered with a single injection of bromocryptine, @ 100 μg/kg BW, for 5 days before expected calving, whereas control group buffaloes were injected with placebo injections. Blood samples collected before parturition (-5,-4,-3,-2,-1 days), on day of parturition (day-0) and on day 1, 2, 3, 4, 5, 10 and 15 post partum were analyzed for growth hormone (GH), insulin like growth factor-I (IGF-I) and prolactin (PRL) by radioimmunassay methods. Milk samples were collected daily for 5 days and on day 10 and 15 after parturition. Milk fat, protein, lactose, citric acid, non-esterified fatty acids (NEFAs) and somatic cell counts (SCCs) were determined in milk samples. Bromocryptine treatment significantly (P < 0.01) decreased pre partum PRL and increased GH levels (P < 0.01) on day of parturition in experimental buffaloes without influencing plasma IGF-I level. Milk yield was significantly lower (P < 0.01) in experimental than in control group. Further, effect of bromocryptine on milk yield was only for a week. Milk yield increased (P < 0.01) gradually and was similar to control group on day 15 post partum. Bromocryptine treatment significantly increased milk SCC (P < 0.01) and protein content (P < 0.01) but there was no effect of treatment on fat, lactose, citric acid, glucose, milk and plasma NEFA concentration. It was concluded that prepartum suppression of PRL by bromocryptine impairs milk secretion temporarily in ensuing lactation. The significant rise in GH level before parturition and on day of parturition suggests a role of it in milk secretion of buffaloes.     

Application of the covariance function approach with an iterative two-stage algorithm to the estimation of parameters of a random regression test day model for dairy production traits

The covariance function approach with an iterative two-stage algorithm of LIU et al. (2000) was applied to estimate parameters for the Polish Black-and-White dairy population based on a sample of 338 808 test day records for milk, fat, and protein yields. A multiple trait sire model was used to estimate covariances of lactation stages. A third-order Legendre polynomial was subsequently fitted to the estimated (co)variances to derive (co)variances of random regression coefficients for both additive genetic and permanent environment effects. Daily and 305-day heritability estimates obtained are consistent with several studies which used both fixed and random regression test day models. Genetic correlations between any two days in milk (DIM) of the same lactation as well as genetic correlations between the same DIM of two lactations were within a biologically acceptable range. It was shown that the applied estimation procedure can utilise very large data sets and give plausible estimates of (co)variance components.     

Bayesian inference of genetic parameters for test-day milk yield, milk quality traits, and somatic cell score in Burlina cows

The aim of the study was to infer (co)variance components for daily milk yield, fat and protein contents, and somatic cell score (SCS) in Burlina cattle (a local breed in northeast Italy). Data consisted of 13576 monthly test-day records of 666 cows (parities 1 to 8) collected in 10 herds between 1999 and 2009. Repeatability animal models were implemented using Bayesian methods. Flat priors were assumed for systematic effects of herd test date, days in milk, and parity, as well as for permanent environmental, genetic, and residual effects. On average, Burlina cows produced 17.0 kg of milk per day, with 3.66 and 3.33% of fat and protein, respectively, and 358000 cells per mL of milk. Marginal posterior medians (highest posterior density of 95%) of heritability were 0.18 (0.09–0.28), 0.28 (0.21–0.36), 0.35 (0.25–0.49), and 0.05 (0.01–0.11) for milk yield, fat content, protein content, and SCS, respectively. Marginal posterior medians of genetic correlations between the traits were low and a 95% Bayesian confidence region included zero, with the exception of the genetic correlation between fat and protein contents. Despite the low number of animals in the population, results suggest that genetic variance for production and quality traits exists in Burlina cattle.     

Effects of a single nucleotide polymorphism in the leptin gene on the productive traits of dairy buffaloes (Bubalus bubalis)

The gene responsible for coding the leptin hormone has been associated with productive and reproductive traits in cattle. In dairy cattle, different polymorphisms found in the leptin gene have been associated with several traits of economic interest, such as energy balance, milk yield and composition, live weight, fertility and dry matter consumption. The aim of this study was to detect genetic variability in the leptin gene of buffaloes and to test possible associations with milk yield, fat and protein percentages, age at first calving and first calving interval. Three genotypes (AA, AG and GG) were identified by polymerase chain reaction–restriction fragment length polymorphism, which presented genotypic frequencies of 0.30, 0.54 and 0.16, respectively. The allele frequencies were 0.57 for the A allele and 0.43 for the G allele. No significant effects were found in the present study, but there is an indicative that leptin gene affects lipid metabolism.     

Single nucleotide polymorphisms in the growth hormone and insulin-like growth factor-1 genes are associated with milk production, body condition score and fertility traits in dairy cows

The somatotrophic axis (GH-IGF) is a key regulator of animal growth and development, affecting performance traits that include milk production, growth rate, body composition, and fertility. The aim of this study was to quantify the association of previously identified SNPs in bovine growth hormone (GH1) and insulin-like growth factor 1 (IGF-1) genes with direct performance trait measurements of lactation and fertility in Holstein-Friesian lactating dairy cows. Sixteen SNPs in both IGF-1 and GH1 were genotyped across 610 cows and association analyses were carried out with traits of economic importance including calving interval, pregnancy rate to first service and 305-day milk production, using animal linear mixed models accounting for additive genetic effects. Two IGF-1 SNPs, IGF1i1 and IGF1i2, were significantly associated with body condition score at calving, while a single IGF-1 SNP, IGF1i3, was significantly associated with milk production, including milk yield (means ± SEM; 751.3 ± 262.0 kg), fat yield (21.3 ± 10.2 kg) and protein yield (16.5 ± 8.0 kg) per lactation. Only one GH1 SNP, GH33, was significantly associated with milk protein yield in the second lactation (allele substitution effect of 9.8 ± 5.0 kg). Several GH1 SNPs were significantly associated with fertility, including GH32, GH35 and GH38 with calving to third parity (22.4 ± 11.3 days) (GH32 and GH38 only), pregnancy rate to first service (0.1%) and overall pregnancy rate (0.05%). The results of this study demonstrate the effects of variants of the somatotrophic axis on milk production and fertility traits in commercial dairy cattle.     

Genetic (co)variances between milk mineral concentration and chemical composition in lactating Holstein-Friesian dairy cows

Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 test-day records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31±0.05 (5 DIM) to 0.67±0.04 (181 DIM) for Ca, from 0.18±0.03 (60 DIM) to 0.24±0.05 (305 DIM) for K, from 0.08±0.03 (15 DIM) to 0.37±0.03 (223 DIM) for Mg, from 0.16±0.03 (30 DIM) to 0.37±0.04 (305 DIM) for Na and from 0.21±0.04 (12 DIM) to 0.57±0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38±0.21 (5 DIM) to 0.79±0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.     

中国荷斯坦牛IL8基因遗传多态性与泌乳性状以及体细胞评分的关联

以上海某奶牛场30个公牛家系的610头中国荷斯坦牛为试验材料,采用聚合酶链式反应-单链构象多态性(PCR-SSCP)技术对Interleukin-8(IL8)基因的遗传多态性进行了分析,采用混合动物模型分析了IL8基因突变位点与测定日产奶量、测定日乳脂率、测定日乳蛋白率、305d校正产奶量、305d乳脂量、305d乳蛋白量及测定日体细胞评分7个性状的相关性,寻找可用于生产实际的分子标记。共检测到KK、KA和AA3种基因型,频率分别为0.187、0.451和0.362,等位基因K和A的频率分别为0.412和0.588。该位点突变对测定日产奶量、305d乳蛋白量、305d校正产奶量和305d乳脂量以及体细胞评分影响达到极显著水平(P0.01),对测定日乳蛋白率的影响达到显著水平(P0.05),对测定日乳脂率影响不显著(P0.05)。多重比较表明:KK基因型对测定日产奶量、305d校正产奶量、305d乳蛋白量和305d乳脂量极显著高于AA和KA基因型(P0.01)。KK基因型的体细胞评分(SCS)最小二乘均值极显著低于KA、AA基因型(P0.01)。对于测定日的乳蛋白率AA基因型显著低于KA、KK型(P0.05)。IL8基因遗传突变对中国荷斯坦牛泌乳性状和乳房炎抗性有较大的遗传效应,可用于中国荷斯坦牛的分子标记辅助选择。     

Body condition score and live-weight effects on milk production in Irish Holstein-Friesian dairy cows

The objective of the present study was to quantify the relationships among body condition score (BCS; scale 1 to 5), live weight (WT) and milk production in Irish Holstein-Friesian spring calving dairy cows. Data were from 66 commercial dairy herds during the years 1999 and 2000. The data consisted of up to 9886 lactations with records for BCS or WT at least once pre-calving, or at calving, nadir or 60 days post-calving. Change in BCS and WT was also calculated between time periods. Mixed models with cow included as a random effect were used to quantify the effect of BCS and WT, as well as change in each trait, on milk yield, milk fat concentration and milk protein concentration. Significant and sometimes curvilinear associations were observed among BCS at calving or nadir and milk production. Total 305-day milk yield was greatest in cows calving at a BCS of 4.25 units. However, cows calving at a BCS of 3.50 units produced only 68 kg less milk than cows calving at a BCS of 4.25 units while cows calving at 3.25 or 3.00 BCS units produced a further 50 and 114 kg less, respectively. Cows that lost more condition in early lactation produced more milk of greater fat and protein concentration, although the trend reversed in cows that lost large amounts of condition post-calving. Milk yield increased with WT although the marginal effect decreased as cows got heavier. Milk fat and protein concentration in early lactation also increased with WT pre-calving, calving and nadir, although WT did not significantly affect average lactation milk fat concentration.     

Genetic diversity analysis of an indigenous Chinese buffalo breed and hybrids based on microsatellite data

Chinese native buffaloes have faced the threat of extinction, along with an increase in crossbreeding with domesticated river buffaloes; consequently, conservation of local buffalo genetic resources has become a priority. A Chinese native breed, Jianghan, is often crossed intentionally and unintentionally with imported breeds from India and Pakistan, Murrah, and Nili-Ravi. A total of 128 buffaloes of the breeds Jianghan, Murrah, and Nili-Ravi and their presumed hybrid offspring were genotyped for 10 microsatellite markers. Heterozygosity and Wright's F-statistics were calculated to determine the genetic variation in those populations. The observed average heterozygosities ranged from 0.836 (Murrah) to 0.986 (Jianghan), higher than the expected heterozygosities and all the inbreeding values within the populations were negative. The genetic distances between the presumed hybrid buffaloes and the two imported river type dairy buffalo breeds (Murrah and Nili-Ravi) were lower than with the native Jianghan, indicating strong contributions of the imported breeds to this presumed hybrid buffalo population. This information will be useful for the development of rational breeding for the dairy buffalo industry and for conservation strategies for the Jianghan buffalo.     

Genetic parameters for milk mineral content and acidity predicted by mid-infrared spectroscopy in Holstein–Friesian cows

The aim of the present study was to estimate genetic parameters for calcium (Ca), phosphorus (P) and titratable acidity (TA) in bovine milk predicted by mid-IR spectroscopy (MIRS). Data consisted of 2458 Italian Holstein−Friesian cows sampled once in 220 farms. Information per sample on protein and fat percentage, pH and somatic cell count, as well as test-day milk yield, was also available. (Co)variance components were estimated using univariate and bivariate animal linear mixed models. Fixed effects considered in the analyses were herd of sampling, parity, lactation stage and a two-way interaction between parity and lactation stage; an additive genetic and residual term were included in the models as random effects. Estimates of heritability for Ca, P and TA were 0.10, 0.12 and 0.26, respectively. Positive moderate to strong phenotypic correlations (0.33 to 0.82) existed between Ca, P and TA, whereas phenotypic weak to moderate correlations (0.00 to 0.45) existed between these traits with both milk quality and yield. Moderate to strong genetic correlations (0.28 to 0.92) existed between Ca, P and TA, and between these predicted traits with both fat and protein percentage (0.35 to 0.91). The existence of heritable genetic variation for Ca, P and TA, coupled with the potential to predict these components for routine cow milk testing, imply that genetic gain in these traits is indeed possible.