Profile and genetic parameters of dairy cattle locomotion score and lameness across lactation

This study investigated the profile of locomotion score and lameness before the first calving and throughout the first (n=237) and second (n=66) lactation of 303 Holstein cows raised on a commercial farm. Weekly heritability estimates of locomotion score and lameness, and their genetic and phenotypic correlations with milk yield, body condition score, BW and reproduction traits were derived. Daughter future locomotion score and lameness predictions from their sires’ breeding values for conformation traits were also calculated. First-lactation cows were monitored weekly from 6 weeks before calving to the end of lactation. Second-lactation cows were monitored weekly throughout lactation. Cows were locomotion scored on a scale from one (sound) to five (severely lame); a score greater than or equal to two defined presence of lameness. Cows’ weekly body condition score and BW was also recorded. These records were matched to corresponding milk yield records, where the latter were 7-day averages on the week of inspection. The total number of repeated records amounted to 12 221. Data were also matched to the farm’s reproduction database, from which five traits were derived. Statistical analyses were based on uni- and bivariate random regression models. The profile analysis showed that locomotion and lameness problems in first lactation were fewer before and immediately after calving, and increased as lactation progressed. The profile of the two traits remained relatively constant across the second lactation. Highest heritability estimates were observed in the weeks before first calving (0.66 for locomotion score and 0.54 for lameness). Statistically significant genetic correlations were found for first lactation weekly locomotion score and lameness with body condition score, ranging from −0.31 to −0.65 and from −0.44 to −0.76, respectively, suggesting that cows genetically pre-disposed for high body condition score have fewer locomotion and lameness issues. Negative (favourable) phenotypic correlations between first lactation weekly locomotion score/lameness and milk yield averaged −0.27 and −0.17, respectively, and were attributed to management factors. Also a phenotypic correlation between lameness and conception rate of −0.19 indicated that lame cows were associated with lower success at conceiving. First-lactation daughter locomotion score and/or lameness predictions from sires’ estimated breeding values for conformation traits revealed a significant linear effect of rear leg side view, rear leg rear view, overall conformation, body condition score and locomotion, and a quadratic effect of foot angle.     

Modelling of lactation curves of dairy cows based on monthly test day milk yield records under inconsistent milk recording scenarios

The objective of this study was to describe the lactation curve of dairy cattle in Kenya using a suitable lactation function in order to facilitate inclusion of partial lactations in national dairy cattle evaluation and to assess the effect of data characteristics on lactation curve parameters. Six functions were fitted to test day (TD) milk yield records from six parities of Ayrshire, Guernsey, Holstein Friesian, Jersey and Sahiwal cattle. Five datasets: DS-1 (12-TD dataset with randomly missing records), DS-2 (10-TD dataset without missing records), DS-3 (10-TD dataset with randomly missing records), DS-4 (7-TD dataset, with only TD 4 to 10 records) and DS-5 (7-TD dataset, with TD 1 to 4, 6, 8 and 10 records) depicting various recording circumstances were derived to assess the effects of data characteristics on lactation curves and to assess the feasibility of reducing the number of TD samples per lactation. The fit of the functions was evaluated using adjusted R(2) and their predictive abilities were compared using mean square prediction error, percentage of squared bias and the correlation between the predicted and actual milk yield. These criteria plus the changes in the parameters of curve functions and their associated standard errors were used in determining the effects of data characteristics on lactation curves. The mechanistic functions of Dijkstra (DIJ) and Pollott (APOL), and the incomplete gamma function of Wood (WD) had the highest adjusted R(2) > 0.75. The APOL function was eliminated due to convergence failures when analysis of individual lactations within breeds was carried out. Both DIJ and WD had good predictive ability, although DIJ performed slightly better. Convergence difficulties were noted in some DIJ analysis where data were limiting. Missing records, especially at the beginning of a lactation, greatly influenced parameters a and b of the functions. It also resulted in estimates with large standard errors. Missing records in later lactation hardly affected the parameter estimates. The WD and DIJ functions showed superior fit to the data. The WD function demonstrated higher adaptability to various data characteristics than DIJ and could be used in situations where animal recording is not consistently practised and where recording of animal performance is routinely practised. DIJ function had high data requirements, which restricts it to dairy systems with consistent recording, despite easy physiological interpretation of its parameters. The number of TD per lactation could be reduced by minimising sampling frequency in the later lactation while maintaining the monthly sampling frequency in early lactation.     

Genome-wide associations for investigating time-dependent genetic effects for milk production traits in dairy cattle

Phenotypic variation in milk production traits has been described over the course of a lactation as well as between different parities. The objective of this study was to investigate whether variation in production is affected by different loci across lactations. A genome-wide association study (GWAS) using a 50-k SNP chip was conducted in 152 divergent German Holstein Friesian cows to test for association with milk production traits over different lactations. The first four lactations were analysed regarding milk yield, fat, protein, lactose, milk urea nitrogen yield and content as well as somatic cell score. Two approaches were used: (i) Wilmink curve parameters were used to assess the genetic effects over the course of a lactation and (ii) test-day yield deviations (YD) were used as a normative approach for a GWAS. The significant effects were largest for markers affecting curve parameters for which there was a statistical power <0.8 of detection even in this small design. While significant markers for YDs were detected in this study, the power to detect effects of a similar magnitude was only 0.11, suggesting that many loci may have been missed with this approach in the present design. Furthermore, all significant effects were specific for a single lactation, leading to the conclusion that the variance explained by a certain locus changes from lactation to lactation. We confirm the common evidence that most production traits vary in the degree of persistency after the peak as a result of genetic influence.     

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.     

An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows

To simulate the consequences of management in dairy herds, the use of individual-based herd models is very useful and has become common. Reproduction is a key driver of milk production and herd dynamics, whose influence has been magnified by the decrease in reproductive performance over the last decades. Moreover, feeding management influences milk yield (MY) and body reserves, which in turn influence reproductive performance. Therefore, our objective was to build an up-to-date animal reproduction model sensitive to both MY and body condition score (BCS). A dynamic and stochastic individual reproduction model was built mainly from data of a single recent long-term experiment. This model covers the whole reproductive process and is composed of a succession of discrete stochastic events, mainly calving, ovulations, conception and embryonic loss. Each reproductive step is sensitive to MY or BCS levels or changes. The model takes into account recent evolutions of reproductive performance, particularly concerning calving-to-first ovulation interval, cyclicity (normal cycle length, prevalence of prolonged luteal phase), oestrus expression and pregnancy (conception, early and late embryonic loss). A sensitivity analysis of the model to MY and BCS at calving was performed. The simulated performance was compared with observed data from the database used to build the model and from the bibliography to validate the model. Despite comprising a whole series of reproductive steps, the model made it possible to simulate realistic global reproduction outputs. It was able to well simulate the overall reproductive performance observed in farms in terms of both success rate (recalving rate) and reproduction delays (calving interval). This model has the purpose to be integrated in herd simulation models to usefully test the impact of management strategies on herd reproductive performance, and thus on calving patterns and culling rates.     

Predicting grass dry matter intake,milk yield and milk fat and protein yield of spring calving grazing dairy cows during the grazing season

Predicting the grass dry matter intake (GDMI), milk yield (MY) or milk fat and protein yield (milk solids yield (MSY)) of the grazing dairy herd is difficult. Decisions with regard to grazing management are based on guesstimates of the GDMI of the herd, yet GDMI is a critical factor influencing MY and MSY. A data set containing animal, sward, grazing management and concentrate supplementation variables recorded during weeks of GDMI measurement was used to develop multiple regression equations to predict GDMI, MY and MSY. The data set contained data from 245 grazing herds from 10 published studies conducted at Teagasc, Moorepark. A forward stepwise multiple regression technique was used to develop the multiple regression equations for each of the dependent variables (GDMI, MY, MSY) for three periods during the grazing season: spring (SP; 5 March to 30 April), summer (SU; 1 May to 31 July) and autumn (AU; 1 August to 31 October). The equations generated highlighted the importance of different variables associated with GDMI, MY and MSY during the grazing season. Peak MY was associated with an increase in GDMI, MY and MSY during the grazing season with the exception of GDMI in SU when BW accounted for more of the variation. A higher body condition score (BCS) at calving was associated with a lower GDMI in SP and SU and a lower MY and MSY in all periods. A higher BCS was associated with a higher GDMI in SP and SU, a higher MY in SU and AU and a higher MSY in all periods. The pre-grazing herbage mass of the sward (PGHM) above 4 cm was associated with a quadratic effect on GDMI in SP, on MY in SP and SU and on MSY in SU. An increase in daily herbage allowance (DHA) above 4 cm was associated with an increase in GDMI in AU, an increase in MY in SU and AU and MSY in AU. Supplementing grazing dairy cows with concentrate reduced GDMI and increased MY and MSY in all periods. The equations generated can be used by the Irish dairy industry during the grazing season to predict the GDMI, MY and MSY of grazing dairy herds.     

Effect of FASN gene on milk yield and milk composition in the Chinese Holstein dairy population

Fatty acid synthase (FASN) is a multifunctional protein that catalyzes de novo synthesis of fatty acids in cells. It plays a key role in the lipid biosynthesis as well as in the general metabolism of all living animals. We herein investigated polymorphisms of FASN. As a result, six single nucleotide polymorphisms (SNPs) were found and then genotyped in 752 Chinese Holstein cows. It was found that g.17924A>G was non‐synonymous, g.13965 C>T, g.16907 T>C and g.18663T>C were synonymous mutations and two other two SNPs, g.8948 C>T (ss491228481) and g.14439T>C (rs133498277), were in intronic sequences of the gene. All such identified SNPs were found to be associated with milk yield and composition traits (P = 0.0441 to <0.0001). Significant additive and allele substitution effects were observed for three yield traits at all six loci as well (P < 0.05 to <0.01). Complete linkage disequilibrium among the five SNPs, with the exception of g.8948 C>T, was observed.     

Production,partial cash flows and greenhouse gas emissions of simulated dairy herds with extended lactations

The transition period is the most critical period in the lactation cycle of dairy cows. Extended lactations reduce the frequency of transition periods, the number of calves and the related labour for farmers. This study aimed to assess the impact of 2 and 4 months extended lactations on milk yield and net partial cash flow (NPCF) at herd level, and on greenhouse gas (GHG) emissions per unit of fat- and protein-corrected milk (FPCM), using a stochastic simulation model. The model simulated individual lactations for 100 herds of 100 cows with a baseline lactation length (BL), and for 100 herds with lactations extended by 2 or 4 months for all cows (All+2 and All+4), or for heifers only (H+2 and H+4). Baseline lactation length herds produced 887 t (SD: 13) milk/year. The NPCF, based on revenues for milk, surplus calves and culled cows, and costs for feed, artificial insemination, calving management and rearing of youngstock, was k€174 (SD: 4)/BL herd per year. Extended lactations reduced milk yield of the herd by 4.1% for All+2, 6.9% for All+4, 1.1% for H+2 and 2.2% for H+4, and reduced the NPCF per herd per year by k€7 for All+2, k€12 for All+4, k€2 for H+2 and k€4 for H+4 compared with BL herds. Extended lactations increased GHG emissions in CO₂-equivalents per t FPCM by 1.0% for All+2, by 1.7% for All+4, by 0.2% for H+2 and by 0.4% for H+4, but this could be compensated by an increase in lifespan of dairy cows. Subsequently, production level and lactation persistency were increased to assess the importance of these aspects for the impact of extended lactations. The increase in production level and lactation persistency increased milk production of BL herds by 30%. Moreover, reductions in milk yield for All+2 and All+4 compared with BL herds were only 0.7% and 1.1% per year, and milk yield in H+2 and H+4 herds was similar to BL herds. The resulting NPCF was equal to BL for All+2 and All+4 and increased by k€1 for H+2 and H+4 due to lower costs for insemination and calving management. Moreover, GHG emissions per t FPCM were equal to BL herds or reduced (0% to −0.3%) when lactations were extended. We concluded that, depending on lactation persistency, extending lactations of dairy cows can have a positive or negative impact on the NPCF and GHG emissions of milk production.     

Environmental and cow-related factors affect cow locomotion and can cause misclassification in lameness detection systems

To tackle the high prevalence of lameness, techniques to monitor cow locomotion are being developed in order to detect changes in cows’ locomotion due to lameness. Obviously, in such lameness detection systems, alerts should only respond to locomotion changes that are related to lameness. However, other environmental or cow factors can contribute to locomotion changes not related to lameness and hence, might cause false alerts. In this study the effects of wet surfaces, dark environment, age, production level, lactation and gestation stage on cow locomotion were investigated. Data was collected at Institute for Agricultural and Fisheries Research research farm (Melle, Belgium) during a 5-month period. The gait variables of 30 non-lame and healthy Holstein cows were automatically measured every day. In dark environments and on wet walking surfaces cows took shorter, more asymmetrical strides with less step overlap. In general, older cows had a more asymmetrical gait and they walked slower with more abduction. Lactation stage or gestation stage also showed significant association with asymmetrical and shorter gait and less step overlap probably due to the heavy calf in the uterus. Next, two lameness detection algorithms were developed to investigate the added value of environmental and cow data into detection models. One algorithm solely used locomotion variables and a second algorithm used the same locomotion variables and additional environmental and cow data. In the latter algorithm only age and lactation stage together with the locomotion variables were withheld during model building. When comparing the sensitivity for the detection of non-lame cows, sensitivity increased by 10% when the cow data was added in the algorithm (sensitivity was 70% and 80% for the first and second algorithm, respectively). Hence, the number of false alerts for lame cows that were actually non-lame, decreased. This pilot study shows that using knowledge on influencing factors on cow locomotion will help in reducing the number of false alerts for lameness detection systems under development. However, further research is necessary in order to better understand these and many other possible influencing factors (e.g. trimming, conformation) of non-lame and hence ‘normal’ locomotion in cows.     

The effects of the brown ear-tick, Rhipicephalus appendiculatus, on milk production in dairy cattle

Abstract. The effect is reported of artificially controlled levels of infestation with adults of Rhipicephalus appendiculatus on the milk yield of twenty commercial Bos taurus dairy cattle on a high plane of nutrition and eighteen crossbed B.taurus × Sanga cattle on a lower plane of nutrition in the highveld of Zimbabwe. The results showed no significant effect on milk yield of infestations averaging twenty engorging ticks per animal per day, despite severe ear damage in some animals. They indicate that milk production of dairy cattle under commercial management is not sensitive to infestation with R.appendiculatus. The results have important implications for management of ticks in Africa, but need to be interpreted within the context of the control of tick-borne diseases.     

Association of IGF-I gene polymorphisms with milk yield and body size in Chinese dairy goats

The association of IGF-I gene polymorphisms with certain traits in 708 individuals of two Chinese dairy-goat breeds (Guanzhong and Xinong Saanen) was investigated. Polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and DNA sequencing methods were employed in screening for genetic variation. Two novel mutations were detected in the 5'-flanking region and in intron 4 of IGF-I gene, viz., g.1617 G > A and g.5752 G > C (accession D26119.2), respectively. The associations of the g.1617 G > A mutation with milk yield and the body size were not significant (p > 0.05). However, in the case of g.5752 G > C, Xinong Saanen dairy goats with the CG genotype presented longer bodies (p < 0.05). Chest circumference (p < 0.05) was larger in Guanzhong goats with the GG genotype. In Xinong Saanen dairy goats with the CC genotype, milk yields were significantly higher during the first and second lactations (p < 0.05). Hence, the g.5752 G > C mutation could facilitate association analysis and serve as a genetic marker for Chinese dairy-goat breeding and genetics.     

Effects of DGAT1 and GHR on milk yield and milk composition in the Chinese dairy population

Previous studies have demonstrated that the p.Lys232Ala substitution in the acylCoA: diacylglycerol acyltransferase ( DGAT1 ) gene and the p.Phe279Tyr mutation in the growth hormone receptor ( GHR ) gene are the causative quantitative trait loci underlying milk yield and composition on BTA14 and BTA20 respectively. To examine their applications in the genetic improvement of Chinese dairy cattle productivity, we herein investigated the effects of the DGAT1 p.Lys232Ala and GHR p.Phe279Tyr mutations on milk, fat and protein yield, as well as fat and protein percentage in the milk of 1222 Holstein cows. Genotyping was performed using PCR-RFLP for DGAT1 or primer-introduced restriction analysis (PCR-PIRA) for GHR . With a mixed animal model, the significant associations of the DGAT1 p.Lys232Ala substitution with 305-day milk, fat and protein yield were identified ( P  =   0.0001). The DGAT1 allele that encode lysine at position 232 was associated with increased 305-day milk fat yield, but with decreased 305-day milk and protein yield, whereas the GHR p.Phe279Tyr mutation was found to be significantly associated with protein percentage ( P  =   0.0014). The allele substitution effect of p.279Phe by p.279Tyr may lead to a significant increase in protein percentage. Our findings indicate that DGAT1 p.232Ala and GHR p.279Phe could be used to increase milk yield and protein yield of Chinese Holstein cows.     

Season of birth is associated with first-lactation milk yield in Holstein Friesian cattle

The aim of the present research was to assess factors associated with first-lactation milk yield in dairy heifers, including maternal and environmental factors, factors related to the development of the heifer and factors related to its offspring such as gender of the calf. In addition, the potential underlying mechanism, in particular metabolic adaptations, was further explored. Data on body growth, reproduction and milk yield of 74 Holstein Friesian heifers on three herds in Flanders (Belgium) were collected. At birth, body measurements of the heifers were recorded and blood samples were taken (in order) to determine basal glucose and insulin concentrations. Body measurements were assessed every 3 months until first calving, and gender and weight of their first calf were recorded. Information on fertility and milk yield of the heifer and its dam were collected from the herd databases. Daily temperature and photoperiod were recorded from the database of the Belgian Royal Meteorological Institute. Linear mixed models were run with herd as a random factor, to account for differences in herd management. Heifers grew 867±80.7 g/day during their first year of life and were inseminated at 14.8±1.34 months. First calving took place at 24.5±1.93 months, at a weight of 642±61.5 kg and heifers produced 8506±1064 kg energy corrected milk during their first 305-day lactation. Regression models revealed that none of the maternal factors such as milk yield and parity, nor the growth of the heifer during the 1^st year of life were associated with milk yield during first lactation. Age, and to a lesser extent BW at first parturition were positively associated with first-lactation milk yield. In addition, the season of birth, but not calving, had a significant influence on milk yield, with winter-born heifers producing less than heifers born in any other season. The lower yielding winter-born heifers had higher insulin concentrations at birth, whereas glucose concentrations were similar, the latter being suggestive for lower insulin sensitivity of the peripheral tissues. Furthermore, environmental temperature at the end of gestation was negatively correlated with neonatal insulin concentrations. In conclusion, results of the present study suggest heifers born during the hotter months are born with a higher peripheral insulin sensitivity, finally leading to a higher first-lactation milk yield.     

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.     

Casein haplotypes and their association with milk production traits in the Finnish Ayrshire cattle

Polymorphism of casein genes was studied in half-sib families of artificial insemination bulls of the Finnish Ayrshire dairy breed. Ten grandsires and 300 of their sons were genotyped for the following polymorphisms: α_S1-casein (B, C), β-casein (A¹, A²), the microsatellite within the K-casein gene (ms⁵, ms⁴) and K-casein (A, B, E). Nine different combinations of these alleles, casein haplotypes, were found. Associations between casein haplotypes and milk production traits (milk and protein yield, fat and protein percentage and milking speed) were studied with ordinary least-squares analysis to find a direct effect of the haplotypes or an association within individual grandsire families using the granddaughter design. Estimated breeding values of sons were obtained from cow evaluation by animal model. No direct effect of the casein haplotypes on the traits was found. Within grandsire families, in one out of four families the chromosomal segment characterized by haplotype 3 (B-A²-ms⁴-A) was associated with an increase in milk yield ( P <0.01) and a decrease in fat percentage ( P < 0.01) when contrasted with haplotype 8 (B-A¹-ms⁴-E). The results provide evidence that in the Finnish Ayrshire breed at least one quantitative trait locus affecting the genetic variation in yields traits is segregating linked to either haplotype 3 (B-A²-ms⁴-A) or 8 (B-A¹-ms⁴-E).     

Relationships between conception rate in Holstein heifers and cows and milk yield at various stages of lactation

We investigated the relationships between conception rates (CRs) at first service in Japanese Holstein heifers (i.e. animals that had not yet had their first calf) and cows and their test-day (TD) milk yields. Data included records of artificial insemination (AI) for heifers and cows that had calved for the first time between 2000 and 2008 and their TD milk yields at 6 through 305 days in milk (DIM) from first through third lactations. CR was defined as a binary trait for which first AI was a failure or success. A threshold-linear animal model was applied to estimate genetic correlations between CRs of heifers or cows and TD milk yield at various lactation stages. Two-trait genetic analyses were performed for every combination of CR and TD milk yield by using the Bayesian method with Gibbs sampling. The posterior means of the heritabilities of CR were 0.031 for heifers, 0.034 for first-lactation cows and 0.028 for second-lactation cows. Heritabilities for TD milk yield increased from 0.324 to 0.433 with increasing DIM but decreased slightly after 210 DIM during first lactation. These heritabilities from the second and third lactations were higher during late stages of lactation than during early stages. Posterior means of the genetic correlations between heifer CR and all TD yields were positive (range, 0.082 to 0.287), but those between CR of cows and milk yields during first or second lactation were negative (range, −0.121 to −0.250). Therefore, during every stage of lactation, selection in the direction of increasing milk yield may reduce CR in cows. The genetic relationships between CR and lactation curve shape were quite weak, because the genetic correlations between CR and TD milk yield were constant during the lactation period.     

Genome‐wide association analysis and gene set enrichment analysis with SNP data identify genes associated with 305‐day milk yield in Holstein dairy cows

Milk production traits, such as 305‐day milk yield (305MY), have been under direct selection to improve production in dairy cows. Over the past 50 years, the average milk yield has nearly doubled, and over 56% of the increase is attributable to genetic improvement. As such, additional improvements in milk yield are still possible as new loci are identified. The objectives of this study were to detect SNPs and gene sets associated with 305MY in order to identify new candidate genes contributing to variation in milk production. A population of 781 primiparous Holstein cows from six central Washington dairies with records of 305MY and energy corrected milk were used to perform a genome‐wide association analysis (GWAA) using the Illumina BovineHD BeadChip (777 962 SNPs) to identify QTL associated with 305MY (P < 1.0 × 10^?5). A gene set enrichment analysis with SNP data (GSEA‐SNP) was performed to identify gene sets (normalized enrichment score > 3.0) and leading edge genes (LEGs) influencing 305MY. The GWAA identified three QTL comprising 34 SNPs and 30 positional candidate genes. In the GSEA‐SNP, five gene sets with 58 unique and 24 shared LEGs contributed to 305MY. Identification of QTL and LEGs associated with 305MY can provide additional targets for genomic selection to continue to improve 305MY in dairy cattle.     

Response of milk fat concentration and yield to nutrient supply in dairy cows

Dietary changes alter dairy cow milk fat concentration (MFC) and yield (MFY) through modifications in the supply of nutrients, which act as precursors or inhibitors of mammary fat synthesis. The current models used to formulate dairy cow diets cannot predict changes in milk fat. The knowledge of the effects of the nutrients on milk fat would help to progress toward this prediction. To this end, we quantified and compared the milk fat responses to variations in the supply of seven nutrients derived from digestion: volatile fatty acids, glucose, proteins, long-chain fatty acids (LCFA) and t10,c12-conjugated linoleic acid (CLA). A database was compiled from studies involving digestive infusions of these nutrients in dairy cows. It included 147 comparisons between a nutrient infusion and a control treatment. The nutrient infusions were limited to the range of physiological variations to mimic nutrient changes after dietary modifications. We established models for the response of MFC, MFY and milk fatty acid (FA) composition to the supply of each nutrient. MFC and MFY responses to the nutrients were significant and linear, except for the MFC response to glucose that was curvilinear. The nutrients differed in their effects on MFC and MFY: acetate, butyrate and LCFA increased MFC and MFY, whereas propionate, glucose and t10,c12-CLA decreased them. Protein infusions increased MFY and decreased MFC because of an increase in milk yield. The effects of numerous interfering factors related to animals, diets or experimental conditions were tested on the residuals of the response models. The responses of milk FA percentages are also provided. When adjusted to the in vivo variations in the nutrients observed after dietary changes, the effects of the different nutrients were moderate. Finally, this study showed that several of these nutrients could contribute to the changes in milk fat production and composition observed after dietary changes. This is a first step toward predicting milk fat response to changes in nutrient supply.     

Expected early genetic gain from selection for milk yield in dairy cattle

Summary A matrix program to predict short term genetic gain from single trait selection for milk yield was developed. Rate of genetic gain was calculated as the annual change in the mean breeding value of all producing females. Several parameters sets representing various selection policies were used to examine situations pertinent to dairy populations of the United States. Approach to the asymptotic rates of genetic gain within the model varied with the choice of parameters, but even with consistent selection policies, predicted total genetic gain in the first 10 years was only half of the expected from classical theory. Considerable year to year variation in the rate of gain occurred. Early gains were more dependent on female selection decisions than gains during the steady state. In a two-phase model, the approach to the linear rate of gain in the second phase was accelerated by starting with an ongoing improvement program, but considerable delays still existed. Selection for sex- limited traits such as milk yield, which require pedigree selection and a waiting time for progeny test results reached asymptotic rates more slowly than previously assumed.     

Towards a better understanding of the respective effects of milk yield and body condition dynamics on reproduction in Holstein dairy cows

The overall reproductive performance has decreased over the last decades, involving changes in cyclicity, oestrous behaviour and fertility. High milk yield (MY), low body condition score (BCS) and large body condition (BC) loss have been identified as risk factors. However, these effects are often confounded, as high MY and body lipid reserve mobilization are correlated. The aim of this study was to evaluate the respective effects of MY and BC on post-partum ovarian cyclicity, oestrus and fertility of Holstein cows. This study provides novel information, as MY and BC change were uncoupled in the overall dataset that included 98 lactations and milk progesterone profiles. Cows were assigned to two feeding-level groups: high feed, which achieved high MY and moderate BC loss throughout lactation (8410 kg, -1.17 unit from calving to nadir BCS), and low feed, which limited MY and triggered a large BC loss (5719 kg, -1.54 unit). MY and BC had different effects at different stages of the reproductive process. Cyclicity as well as non-fertilization and early embryo mortality were mainly driven by body lipid reserves, whereas oestrous behaviour and late embryo mortality were related to MY. The results point to possible uncoupling between cyclicity, oestrus and early and late embryo survival allowing compensation along the reproductive process and leading to similar final reproductive performance. In compact calving systems, which require high pregnancy rates within a short period, higher MY strategies appear unsuitable even where BCS is maintained, owing to depressed oestrous behaviour and probably increased late embryo mortality, which delays rebreeding. Similarly, strategies that compromise cyclicity and fertility by excessively low BCS are unsuitable.