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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.

In Japan, the degree of marbling in ribeye (M. longissimus thoracis) is evaluated in the beef meat grading process. However, other muscles (e.g., M. trapezius) are also important in determining the meat quality and carcass market prices. The purpose of this study was to estimate genetic parameters for M. longissimus thoracis (M-LONG) and M. trapezius (M-TRAP) of carcass cross section of Japanese Black steers by computer image analysis. The number of records of Japanese Black steers and the number of pedigree records were 2,925 and 10,889, respectively. Digital images of the carcass cross section were taken between the sixth and seventh ribs by photographing equipment. Muscle area (MA), fat area ratio (FAR), overall coarseness of marbling particles (OCM), and coarseness of maximum marbling particle (MMC) in M-LONG and M-TRAP were calculated by image analysis. Genetic parameters for these traits were estimated using the AIREMLF90 program with an animal model. Fixed effects that were included in the model were dates of arrival at the carcass market and slaughter age (mo), and random effects of fattening farms, additive genetic effects and residuals were included in the model. For M-LONG, heritability estimates (+/-SE) were 0.46 +/- 0.06, 0.59 +/- 0.06, 0.47 +/- 0.06, and 0.20 +/- 0.05 for MA, FAR, OCM, and MMC, respectively. Heritability estimates (+/-SE) in M-TRAP were 0.47 +/- 0.06, 0.57 +/- 0.07, 0.49 +/- 0.07, and 0.13 +/- 0.04 for the same traits. Genetic correlations between subcutaneous fat thickness and FAR for M-LONG and M-TRAP were negative (-0.21 and -0.19, respectively). Those correlations between M-LONG and M-TRAP were moderate to high for MA, FAR, OCM, and MMC (0.38, 0.52, 0.39, and 0.60, respectively). These results indicate that other muscles including M-LONG should be evaluated for more efficient genetic improvement.

This study evaluated the dependence of reliability and prediction bias on the prediction method, the contribution of including animals (bulls or cows), and the genetic relatedness, when including genotyped cows in the progeny-tested bull reference population. We performed genomic evaluation using a Japanese Holstein population, and assessed the accuracy of genomic enhanced breeding value (GEBV) for three production traits and 13 linear conformation traits. A total of 4564 animals for production traits and 4172 animals for conformation traits were genotyped using Illumina BovineSNP50 array. Single-and multi-step methods were compared for predicting GEBV in genotyped bull-only and genotyped bull-cow reference populations. No large differences in realized reliability and regression coefficient were found between the two reference populations; however, a slight difference was found between the two methods for production traits. The accuracy of GEBV determined by single-step method increased slightly when genotyped cows were included in the bull reference population, but decreased slightly by multi-step method. A validation study was used to evaluate the accuracy of GEBV when 800 additional genotyped bulls (POPbull) or cows (POPcow) were included in the base reference population composed of 2000 genotyped bulls. The realized reliabilities of POPbull were higher than those of POPcow for all traits. For the gain of realized reliability over the base reference population, the average ratios of POPbull gain to POPcow gain for production traits and conformation traits were 2.6 and 7.2, respectively, and the ratios depended on heritabilities of the traits. For regression coefficient, no large differences were found between the results for POPbull and POPcow. Another validation study was performed to investigate the effect of genetic relatedness between cows and bulls in the reference and test populations. The effect of genetic relationship among bulls in the reference population was also assessed. The results showed that it is important to account for relatedness among bulls in the reference population. Our studies indicate that the prediction method, the contribution ratio of including animals, and genetic relatedness could affect the prediction accuracy in genomic evaluation of Holstein cattle, when including genotyped cows in the reference population.Keywords: inclusion of cows, dairy cattle, small population, reliability, prediction bias ImplicationsThe size of the reference population strongly influences genomic evaluation. If the size of the progeny-tested bull reference population is small, inclusion of domestic cows must be considered. In order to maximize the prediction accuracy by including genotyped cows in the reference population, we must investigate how the reliability and prediction bias are affected by the inclusion of cows under several conditions. The results of this study indicate that the prediction method, the contribution of included animals, and genetic relatedness should be taken account in designin...

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