Genetic evaluation of heat tolerance in Holstein cows in Japan

We used test‐day records and daily records from provincial weather stations in Japan to evaluate heat tolerance (HT) in Holstein cows according to a random regression test‐day model. Data were a total of 1,641,952 test‐day records for heritability estimates and 17,245,694 test‐day records for genetic evaluation of HT by using milk yield and somatic cell score (SCS) in Holstein cows that had calved for the first time in 2000 through 2015. Temperature–humidity index (THI) values were estimated by using average daily temperature and average daily relative humidity records from 60 provincial Japanese weather stations. The model contained herd–test‐day, with lactation curves on days in milk within month–age group as a fixed effect. General additive genetic effect and HT of additive genetic effect were included as random effects. The threshold value of THI was set to 60. For milk yield, estimated mean heritabilities were lower during heat stress (THI = 78; 0.20 and 0.28) than when below the heat stress threshold (THI ≤ 60; 0.26 and 0.31). For SCS, heritability estimates (range 0.08–0.10) were similar under all heat stress conditions. Genetic trends of HT indicated that EBVs of HT are changing in an undesirable direction.     

Dual-purpose Guzerá cattle exhibit high dairy performance under heat stress

The present study evaluated the heat stress response pattern of dual-purpose Guzerá cattle for test-day (TD) milk yield records of first lactation and estimated genetic parameters and trends related to heat stress. A total of 31,435 TD records from 4,486 first lactations of Guzerá cows, collected between 1986 and 2012, were analysed. Two random regression models considered days in milk (DIM) and/or temperature × humidity-dependent (THI) covariate. Impacts of −0.037, −0.019 and −0.006 kg/day/THI for initial and intermediate stages of lactation were observed when considering the mean maximum daily temperature and humidity to calculate THI. Heritability estimates ranged from 0.16 to 0.35 throughout lactation and THI values, suggesting the possibility to expect gains from selection for such trait. The variable trajectory of breeding values for dual-purpose Guzerá sires in response to changes in THI values confirms that the genotype × environment interaction due to heat stress can have some effect on TD milk yield. Despite the high dairy performance of Guzerá cattle under heat stress, estimated genetic trends showed a progressive reduction in heat tolerance. Therefore, new strategies should be adopted to prevent negative impacts of heat stress over milk production in Guzerá animals in future.     

Genetic variation of adaptation to heat stress in two Spanish dairy goat breeds

Monthly test-day records of milk yield and composition in Murciano-Granadina (MG) and Payoya (PYA) dairy goats were combined with weather data from meteorological stations, to analyse the effects of heat stress on dairy traits, measured with an index of temperature and relative humidity (THI). A 'repeatability animal model' and a 'reaction norm animal model' were used to estimate genetic (co)variance components. Estimates obtained with both models were very similar. The h(2) of daily yields in MG did not vary throughout the THI scale, but the pattern of variation of content traits showed negative trends for increasing THI values. In PYA, a slight positive tendency throughout the THI scale was observed for the same traits. The genetic correlations between subsequent points in the THI scale were lower than 0.80 when they were computed between low and high THI points. The same reaction norm was observed for all traits. Using the 'reaction norm animal model', it was possible to identify those animals that show the same performance throughout the THI trajectory (robust) and those with varying performances (tolerant and non-tolerant to heat stress). Results in this study also show that heat tolerance decreases, while the genetic level for milk traits increases. Losses because of heat stress were equivalent to 1.9 and 3.1% in the yearly yield of fat and protein for MG and PYA, respectively.     

Genetic associations between milk fat‐to‐protein ratio,milk production and fertility in the first two lactations of Thai Holsteins dairy cattle

The aims of this study were to estimate, simultaneously, the genetic parameters of test‐day milk fat‐to‐protein ratio (FPR), test‐day milk yield (MY), and days‐open (DO) in the first two lactations of Thai Holsteins. A total of 76 194 test‐day production records collected from 8874 cows with 8674 DO records between 2001 and 2011 from different lactations were treated as separated traits. The estimates of heritability for test‐day FPR in the first lactation showed an increasing trend, whereas the estimates in the second lactation showed a U‐shape trend. Genetic correlations for FPR‐DO and MY‐DO showed a decreasing trend along days in milk (DIM) in both lactations, whereas genetic correlations for FPR‐MY increased along DIM in the first lactation but decreased in the second lactation. Genetic correlations of FPR between consecutive DIM were moderate to high, which showed the effectiveness of simultaneous analyses. Selection of FPR in the early stage has no adverse effect on MY and DO for the first lactation but has a negative effect on MY and positive effect on DO for the second lactation. This study showed that genetic improvement of the energy balance using FPR, MY and DO with multi‐trait test day model could be applied in a Thailand dairy cattle breeding program.     

Length of lags in responses of milk yield and somatic cell score on test day to heat stress in Holsteins

We used daily records from provincial Japanese weather stations and monthly test‐day records of milk production to investigate the length of the lags in the responses of cows’ milk yield and somatic cell score (SCS) to heat stress (HS). We also investigated the HS thresholds in milk yield and SCS. Data were a total of 17,245,709 test‐day records for milk and SCS in Holstein cows that had calved for the first time between 2000 and 2015, along with weather records from 60 weather stations. Temperature–humidity index (THI) values were estimated by using average daily temperature and average daily relative humidity. Adjusted THI values were calculated by using temperature, relative humidity, wind speed, and solar radiation. The model contained herd, calving year, month of test day, age group, days in milk, and THI as a fixed effect. THIs for each day from 14 days before the test day until the test day were used to represent the HS effects. The HS occurring 3 days, and between 8 and 10 days, before the test day had the greatest effect on the milk yield and SCS, respectively. The threshold THI values for the HS effect were about 60–65 for both traits.     

Non-additive effects on milk production in Czech dairy cows

Crossbreeding effects on milk production traits of Czech dual‐purpose and dairy cattle breeds were estimated. Nearly 370 000 cows with known gene proportions from Czech Pied, Ayrshire or Holstein cattle were selected from the national milk recording data base. Single‐trait animal models were calculated for milk, fat and protein yield, fat and protein content. The model of Dickerson including additive, additive maternal, heterotic and recombination effects was used for the part of the animal model describing the crossbreeding effects in all calculations. For milk yield, the additive genetic effect (defined as deviation from Czech Pied cattle) was 850–900 kg for Holstein and 240–480 kg for Ayrshire. The maternal effects were low and negative. Low significant positive heterotic effects were observed being up to approximately 100 kg for Czech Pied × Holstein. The recombination effects were negative and statistically significant for Czech Pied × Holstein. The results for fat and protein yield were similar to the results for milk yield. For fat and protein content, nearly no statistically significant crossbreeding effects were found.     

Development of genetic evaluation for milk production traits of Holsteins in Japan

The procedure used for the genetic evaluation of dairy cattle in Japan has developed from a lactation sire–MGS model to a multiple‐lactation random regression test‐day animal model. Genetic evaluation of Holstein bulls in Japan began in 1989 with the use of field‐style progeny testing; dairy herd improvement program data from all over Japan were used, along with a sire and maternal grandsire model. In 1993, an animal model was introduced to estimate breeding values for yield and type traits. A random regression test‐day model was first applied in 2010. In the business of breeding dairy cattle, it is very important to users that estimated breeding values are reliable and stable among subsequent routine evaluations. With experience in the genetic evaluation of dairy cattle in Japan, Japanese researchers have found ways to improve the stability of estimated breeding values. These modifications involve changes in data editing, development of evaluation models, changes to the structures of unknown‐parent groups, awareness of the problems of predicting lactation yield from partial test‐day records, and adjustment for heterogeneity within herd variances. Here, I introduce developments in, and our experiences with, the genetic evaluation of yield traits of Holstein cattle in Japan.     

Utility of on- and off-farm weather records for studies in genetics of heat tolerance

Utility of weather information from on-farm and weather stations was evaluated for the application in studies on the genetics of heat stress. Daily milk yield of 31 primiparous Holstein cows was collected at Tifton, GA, from April 28 to July 19, 1993. Weather information was recorded on-farm and was available from weather stations in Georgia. Analyses used daily average of temperature–humidity index (THI). Effects of threshold of heat stress and the rate of decline in milk after the threshold were estimated. With on-farm weather data, threshold was at THI = 22 and rate of decline was − 1.12 kg of milk per unit of THI measured 2 days before milking. At the Tifton weather station, 3 km away from the farm, the threshold was THI = 20 and the rate was the same. With data from Macon, Columbus, Atlanta, and Athens stations, the threshold was at 20, 21, 20, and 20, respectively, and the rate of decline with a 2 day lag was − 0.88, − 1.02, − 0.90, and − 0.97 kg of milk per unit of THI. Subsequent analysis included 2260 test day records from the same farm from 1993 to 2003 and weather data from Tifton station. The highest rate of decline on milk yield of − 0.22 kg per unit of THI occurred at the threshold of 20 and no lag. For data restricted to 1999–2003, the threshold increased to 22 and the rate to − 0.46 kg per THI unit. Public stations provide satisfactory information for national genetic evaluation for heat stress. Critical parts in such an evaluation are modeling of test days and accounting for changes among farms and weather stations over time.     

Exploration of factors determining milk production by Holstein cows raised on a dairy farm in a temperate climate area

In this study, we examined factors that affected milk production by cows raised in a temperate climate area. We conducted this study on a large dairy farm containing approximately 2000 Holstein cows, located in a temperate climate area. We collected 7803 calving records for 4069 cows from 2012 to 2016. We then assessed the effect of hot weather on milk yield by examining three climate factors: season, maximum temperature (MAX), and the temperature and humidity index (THI). We found that increases in heat stress caused linear decreases in milk yield (P?<?0.05). Additionally, the effects of the three climate factors on milk yield varied depending on cow parity and days open (P?<?0.05). Thus, management procedures should consider cow parity and lactating stage to minimize the negative effects of heat stress on milk production. We also found that the lowest Akaike information criterion value was obtained in our model when using THI for 305-day milk yield. This suggests that THI is a more accurate variable for evaluating heat stress than MAX or season.

     

Parameters for the determination and evaluation of heat stress in dairy cattle in South Africa

Not all parameters are trustworthy and practical to use as parameters to determine heat stress in dairy cattle. The temperature-humidity index (THI) is still the best, simplest and most practical index (parameter) for measurement of environmental warmth which cause heat stress in dairy cattle. It is practical, easy to determine and relatively trustworthy to use body temperature and respiratory rate as parameters to determine heat stress in dairy cattle. These physiological parameters must always be used together with THI values to determine and evaluate heat stress in dairy cattle. For practical purposes, plasma cortisol concentration and milk composition cannot be used as parameters to determine heat stress in dairy cattle although good indications of acute or chronic heat stress can be obtained. Vanillic acid is a break-down product of adrenalin found in milk, but before its concentration in milk can be used as an indicator/parameter of heat stress in dairy cows, more about the pharmacodynamics of adrenaline in the milk has to be known. Selection and breeding of dairy cows on the basis of their adaptibility to heat stress using the most practical heat stress parameters will ensure that their offspring will have superior performance in the prevailing environmental conditions.     

Impact of diet composition and temperature–humidity index on water and dry matter intake of high‐yielding dairy cows

The temperature–humidity index (THI) is widely used to characterize heat stress in dairy cattle. Diet composition is known to induce variation in metabolic‐associated heat production. However, the relationships between THI and diet are poorly characterized with regard to performance and intake behaviour. Therefore, the objectives were to evaluate the impact of THI on water intake (WI), dry matter intake (DMI) and the frequency of drinking and feeding bouts in lactating dairy cows offered four dietary treatments: each contained 20% grass silage and additionally (i) 20% maize silage, 60% concentrate (M‐HC); (ii) 60% maize silage, 20% concentrate (M‐LC); (iii) 20% pressed beet pulp silage, 60% concentrate (BPS‐HC); or (iv) 60% pressed beet pulp silage, 20% concentrate (BPS‐LC) (DM basis). Individual WI and DMI were recorded from April to July 2013. Furthermore, dietary effects on milk production and reticular pH were estimated. Milk yield was lowest for M‐LC, while energy‐corrected milk was similar for all diets. Milk fat percentage was higher and milk protein amount lower for cows offered both LC diets. Reticular pH below 6.3, 6.0 and 5.8 lasted longest for BPS‐LC. WI was higher for HC diets. However, the frequency of drinking bouts was not influenced by the ration. Lower DMI occurred for BPS‐LC compared to M‐LC. Frequency of feeding bouts was significantly higher for LC diets. THI was significantly related to WI, DMI as well as drinking and feeding bouts. Per increasing THI, WI increased slightly more for LC diets and DMI decreased more for HC diets. Frequency of drinking bouts increased slightly higher for BPS rations per rising THI, while the decrease in feeding bouts was highest for M‐HC. In conclusion, TMR composition and moderate heat stress impacted WI and DMI of dairy cows, while both dietary energy density and ruminal filling might intensify the THI impact.     

Estimates of heat stress relief needs for Holstein dairy cows

Estimates of environmental heat stress are required for heat stress relief measures in cattle. Heat stress is commonly assessed by the temperature-humidity index (THI), the sum of dry and wet bulb temperatures. The THI does not include an interaction between temperature and humidity, although evaporative heat loss increases with rising air temperature. Coat, air velocity, and radiation effects also are not accounted for in the THI. The Holstein dairy cow is the primary target of heat stress relief, followed by feedlot cattle. Heat stress may be estimated for a variety of conditions by thermal balance models. The models consist of animal-specific data (BW, metabolic heat production, tissue and coat insulation, skin water loss, coat depth, and minimal and maximal tidal volumes) and of general heat exchange equations. A thermal balance simulation model was modified to adapt it for Holstein cows by using Holstein data for the animal characteristics in the model, and was validated by comparing its outputs to experimental data. Model outputs include radiant, convective, skin evaporative, respiratory heat loss and rate of change of body temperature. Effects of milk production (35 and 45 kg/d), hair coat depth (3 and 6 mm), air temperature (20 to 45 degrees C), air velocity (0.2 to 2.0 m/s), air humidity (0.8 to 3.9 kPa), and exposed body surface (100, 75, and 50%) on thermal balance outputs were examined. Environmental conditions at which respiratory heat loss attained approximately 50% of its maximal value were defined as thresholds for intermediate heat stress. Air velocity increased and humidity significantly decreased threshold temperatures, particularly at higher coat depth. The effect of air velocity was amplified at high humidity. Increasing milk production from 35 to 45 kg/d decreased threshold temperature by 5 degrees C. In the lying cow, the lower air velocity in the proximity of body surface and the smaller exposed surface markedly decrease threshold temperature. The large variation in thresholds due to environmental and animal factors justifies the use of thermal balance-based indices for estimating heat stress. Such an approach may make possible estimates of threshold temperatures at which heat stress relief is required for widely different cattle types and environmental situations.     

Genetic and phenotypic parameters for conformation and yield traits in three Swiss dairy cattle breeds

This study presents genetic parameters for conformation traits and their genetic and phenotypic correlations with milk production traits and somatic cell score (SCS) in three Swiss dairy cattle breeds. Data on first lactations from Holstein (67 839), Brown Swiss (173 372) and Red & White breeds (53 784) were available. Analysed conformation traits were stature and heart girth (both in cm), and linear scores of body depth, rump width, dairy character or muscularity, and body condition score (only in Holstein). A sire model, with relationships among sires, was used for all breeds and traits and variance components were estimated using AS‐REML. Heritabilities for stature were high (0.6–0.8), and for the linear type traits ranged from 0.3 to 0.5, for all breeds. Genetic correlations with production traits (milk, fat and protein yield) and SCS differed between the dairy breeds. Most markedly, stronger correlations were found between SCS and some conformation traits in Brown Swiss and Red & White, indicating that a focus on a larger and more ‘dairy’ type in these breeds would lead to increased SCS. Another marked difference was that rump width correlated positively with milk yield traits in Holstein and Red & White, but negative in Brown Swiss. Results indicate that conformation traits generally can be used as predictors for various purposes in dairy cattle breeding, but may require specific adaptation for each breed.     

Evaluation of association between polymorphism within the thyroglobulin gene and milk production traits in dairy cattle

In dairy cattle, many studies have reported quantitative trait loci (QTL) on the centromeric end of chromosome 14 that affect milk production traits. One of the candidate genes in this QTL region – thyroglobulin (TG) – was previously found to be significantly associated with marbling in beef cattle. Thus, based on QTL studies in dairy cattle and because of possible effects of this gene on fat metabolism, we investigated the association of TG with milk yield and composition in Holstein dairy cattle. A total of 1279 bulls from the Cooperative Dairy DNA Repository Holstein population were genotyped for a single nucleotide polymorphism in TG used previously in beef cattle studies. Analysis of 29 sire families showed no significant association between TG variants and milk production traits. Within‐sire family analysis suggests that TG is neither the responsible gene nor a genetic marker in association with milk production traits.     

河北省中国荷斯坦牛产奶和体型性状遗传参数分析

旨在探究河北省中国荷斯坦牛产奶和体型性状的遗传参数,为育种提供参考.本研究收集了2012-2018年河北省133个牛场8 891头中国荷斯坦母牛第一胎次的3个产奶性状记录(产奶量、乳脂率和乳蛋白率)和26个体型性状记录,利用DMU软件,以场年季、产犊月龄、鉴定年季和鉴定员效应为固定效应,以个体的加性遗传效应为随机效应,...     

自然生产条件下热应激周期变化揭示泌乳中期奶牛出现“热应激乳蛋白降低征”

本试验在连续3年时间里测定了上海地区热应激周期变化对泌乳中期奶牛生产性能和牛奶品质的影响。通过实地测定并计算分析,绘制了上海地区热应激周期变化图谱,揭示了整个热应激周期中不同热应激程度的分布状况。研究对比了自然生产环境下无热应激与中度热应激对奶牛生产性能和牛奶品质的影响,发现中度热应激极显著降低了奶牛采食量、产奶量、乳脂校正乳产量、能量校正乳产量、乳脂率、乳蛋白含量、总固体含量(P<0.01),而且显著增加了乳中尿素氮含量(P<0.05)。在热应激周期变化研究中发现,中度热应激显著升高泌乳奶牛的直肠温度和呼吸频率(P<0.05),而且呼吸频率比直肠温度对热应激变化的反应更快、更敏感。热应激周期变化对奶牛干物质采食量、产奶量的影响取决于热应激程度,2012年整个热应激周期的热应激程度比较低,热应激周期变化对奶牛干物质采食量、产奶量无显著影响(P>0.05),但是2013年热应激程度更加严重,热应激周期变化对奶牛干物质采食量、产奶量产生了极显著影响(P<0.01)。在牛奶品质中,受热应激影响最大的是乳蛋白合成量(P<0.01)。2012年和2013年2个热应激周期变化对其他乳成分含量没有显著影响(P>0.05),但是两年的热应激周期变化都导致乳蛋白含量显著下降(P<0.05)和乳中尿素氮含量显著升高(P<0.05)。尤其值得注意的是,2012年热应激周期变化并没有导致奶牛采食量下降(P>0.05),而且产奶量也没有显著性差异(P>0.05),但是仍然出现了乳蛋白含量下降和乳中尿素氮含量升高(P<0.05)。这表明热应激周期变化改变了泌乳中期奶牛氮代谢的途径,发生了氮营养重分配(repartitioning)现象,而且这种现象不依赖于采食量和产奶量,可以称之为“热应激乳蛋白降低征”(heat-stressed milk protein decrease syndrome,HS-MPD)。     

Estimation of genetic parameters for functional longevity in the South African Holstein cattle using a piecewise Weibull proportional hazards model

Non‐genetic factors influencing functional longevity and the heritability of the trait were estimated in South African Holsteins using a piecewise Weibull proportional hazards model. Data consisted of records of 161,222 of daughters of 2,051 sires calving between 1995 and 2013. The reference model included fixed time‐independent age at first calving and time‐dependent interactions involving lactation number, region, season and age of calving, within‐herd class of milk production, fat and protein content, class of annual variation in herd size and the random herd–year effect. Random sire and maternal grandsire effects were added to the model to estimate genetic parameters. The within‐lactation Weibull baseline hazards were assumed to change at 0, 270, 380 days and at drying date. Within‐herd milk production class had the largest contribution to the relative risk of culling. Relative culling risk increased with lower protein and fat per cent production classes and late age at first calving. Cows in large shrinking herds also had high relative risk of culling. The estimate of the sire genetic variance was 0.0472 ± 0.0017 giving a theoretical heritability estimate of 0.11 in the complete absence of censoring. Genetic trends indicated an overall decrease in functional longevity of 0.014 standard deviation from 1995 to 2007. There are opportunities for including the trait in the breeding objective for South African Holstein cattle.     

Random regression models to estimate genetic parameters for test‐day milk yield in Brazilian Murrah buffaloes

The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo’s test‐day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test‐day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from ?0.07 (second with eighth week) to ?0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes.     

Comparison of heritabilities of dairy traits in Australian Holstein‐Friesian cattle from genomic and pedigree data and implications for genomic evaluations

The reliability of genomic evaluations depends on the proportion of genetic variation explained by the DNA markers. In this study, we have estimated the proportion of variance in daughter trait deviations (DTDs) of dairy bulls explained by 45 993 genome wide single‐nucleotide poly‐ morphism (SNP) markers for 29 traits in Australian Holstein‐Friesian dairy cattle. We compare these proportions to the proportion of variance in DTDs explained by the additive relationship matrix derived from the pedigree, as well as the sum of variance explained by both pedigree and marker information when these were fitted simultaneously. The propor‐ tion of genetic variance in DTDs relative to the total genetic variance (the total genetic variance explained by the genomic relationships and pedigree relationships when both were fitted simultaneously) varied from 32% for fertility to approximately 80% for milk yield traits. When fitting genomic and pedigree relationships simultaneously, the variance unexplained (i.e. the residual variance) in DTDs of the total variance for most traits was reduced compared to fitting either individually, suggesting that there is not complete overlap between the effects. The proportion of genetic variance accounted by the genomic relationships can be used to modify the blending equations used to calculate genomic estimated breeding value (GEBV) from direct genomic breeding value (DGV) and parent average. Our results, from a validation population of young dairy bulls with DTD, suggest that this modification can improve the reliability of GEBV by up to 5%.