The main objective of this study was to compare the performance of different ‘nonlinear quantile regression’ models evaluated at the τth quantile (0·25, 0·50, and 0·75) of milk production traits and somatic cell score (SCS) in Iranian Holstein dairy cows. Data were collected by the Animal Breeding Center of Iran from 1991 to 2011, comprising 101 051 monthly milk production traits and SCS records of 13 977 cows in 183 herds. Incomplete gamma (Wood), exponential (Wilmink), Dijkstra and polynomial (Ali & Schaeffer) functions were implemented in the quantile regression. Residual mean square, Akaike information criterion and log-likelihood from different models and quantiles indicated that in the same quantile, the best models were Wilmink for milk yield, Dijkstra for fat percentage and Ali & Schaeffer for protein percentage. Over all models the best model fit occurred at quantile 0·50 for milk yield, fat and protein percentage, whereas, for SCS the 0·25th quantile was best. The best model to describe SCS was Dijkstra at quantiles 0·25 and 0·50, and Ali & Schaeffer at quantile 0·75. Wood function had the worst performance amongst all traits. Quantile regression is specifically appropriate for SCS which has a mixed multimodal distribution.

Tropical and sub-tropical climates are characterized by high temperature and humidity, during at least part of the year. Consequently, heat stress is common in Holstein cattle and productive and reproductive losses are frequent. Our objectives were as follows: (1) to quantify losses in production and quality of milk due to heat stress; (2) to estimate genetic correlations within and between milk yield (MY) and milk quality traits; and (3) to evaluate the trends of genetic components of tolerance to heat stress in multiple lactations of Brazilian Holstein cows. Thus, nine analyses using two-trait random regression animal models were carried out to estimate variance components and genetic parameters over temperature–humidity index (THI) values for MY and milk quality traits (three lactations: MY×fat percentage (F%), MY×protein percentage (P%) and MY×somatic cell score (SCS)) of Brazilian Holstein cattle. It was demonstrated that the effects of heat stress can be harmful for traits related to milk production and milk quality of Holstein cattle even though most herds were maintained in a modified environment, for example, with fans and sprinklers. For MY, the effect of heat stress was more detrimental in advanced lactations (−0.22 to −0.52 kg/day per increase of 1 THI unit). In general, the mean heritability estimates were higher for lower THI values and longer days in milk for all traits. In contrast, the heritability estimates for SCS increased with increasing THI values in the second and third lactation. For each trait studied, lower genetic correlations (different from unity) were observed between opposite extremes of THI (THI 47 v. THI 80) and in advanced lactations. The genetic correlations between MY and milk quality trait varied across the THI scale and lactations. The genotype×environment interaction due to heat stress was more important for MY and SCS, particularly in advanced lactations, and can affect the genetic relationship between MY and milk quality traits. Selection for higher MY, F% or P% may result in a poor response of the animals to heat stress, as a genetic antagonism was observed between the general production level and specific ability to respond to heat stress for these traits. Genetic trends confirm the adverse responses in the genetic components of heat stress over the years for milk production and quality. Consequently, the selection of Holstein cattle raised in modified environments in both tropical and sub-tropical regions should take into consideration the genetic variation in heat stress.

CD4+ T cells play a key role in the immune response of pathogen-induced mastitis in dairy cattle. Mammary gland factor STAT5b is involved in the regulation of CD4+T cell differentiation during inflammatory response and milk production. Little is known about the genetic variation effects of bovine CD4 and STAT5b genes on somatic cell score (SCS) and milk production traits in dairy cattle. The aim of the study was to investigate the single nucleotide polymorphisms (SNPs) of bovine CD4 and STAT5b in Chinese Holsteins and to analyse their association with estimated breeding values (EBVs) for SCS and milk production traits. In the present study, SNPs of CD4 (NC_007303 g.13598C>T) and STAT5b (NC_007317 g.31562 T>C) were identified and genotyped in Chinese Holstein population. The results showed that both SNPs were significantly associated with the EBVs for milk yield and protein yield in Chinese Holstein cows, and the SNP in CD4 was associated with the EBV for SCS (P<0·01). The additive effect of CD4 SNP on protein yield was significant (P<0·05), and the dominant effect of STAT5b SNP was significant on milk yield and protein yield (P<0·01). Cows with combination genotype C7 (CCTT: CD4 g.13598C>T and STAT5b g.31562 T>C) had the highest SCS EBV but lower milk yield, while cows with C2 (TTTC) produced more milk, fat and protein than the other eight combination genotypes. These results suggested that the SNPs in CD4 and STAT5b may be potential genetic markers for SCS and milk/protein yields selecting and warrant further functional research.

The objective of this study was to develop a method for calculating economic values of clinical mastitis (CM) and somatic cell score (SCS) for inclusion in a dairy cattle breeding goal in the context of a country where farm production and economic data are scarce. In order to calculate the costs and derive economic values for SCS, a new model, ‘milk collection method’, has been developed and was compared with the Meijering model with individual and average SCS distributions. For the population, estimated economic values using the milk collection method were 1.3 and 2.4 times higher than those of Meijering method with average and individual SCS, respectively. The milk collection method needs no assumptions about normality of the distribution of SCS and because of a lack of normality in Iranian data for SCS, the Meijering method resulted in economic values that were biased downwards. Failing to account for the fact that milk price penalties for SCS are applied at milk collection rather than individual cow level resulted in a further large downward bias in the economic value of SCS. When the distribution of data is unknown or difficult to approximate or when a transformation to normality is not straightforward, the milk collection method would be preferable. Inclusion of SCS and CM in the breeding goal for Iranian dairy cattle is justified based on these results. The model to calculate mastitis costs proposed here could be used to estimate economic values for CM in other developing countries where farm production and economic data are generally poor.

The objective was to utilize data from modern US dairy cattle to determine the effect of days dry on fat and protein yield, fat and protein percentages, days open, and somatic cell score in the subsequent lactation. Field data collected through the dairy herd improvement association from January 1997 to December 2003 and extracted from the Animal Improvement Programs Laboratory national database were used for analysis. Actual lactation records calculated from test-day yields using the test-interval method were used in this study. The model for analyses included herd-year of calving, year-state-month of calving, previous lactation record, age at calving, and days dry as a categorical variable. Fat and protein yield was maximized in the subsequent lactation with a 60-d dry period. Dry periods of 20 d or less resulted in substantial losses in fat and protein yield in the subsequent lactation. In contrast to yields, a short dry period was beneficial for fat and protein percentages. Short dry periods also resulted in fewer days open in the subsequent lactation; however, this was entirely due to the lower milk yield associated with shortened dry period. When adjusted for milk yield, short dry periods actually resulted in poorer fertility in the subsequent lactation. Long days dry improved somatic cell score in the subsequent lactation. Herds with mastitis problems should be cautious in shortening days dry because short dry periods led to higher cell scores in the subsequent lactation compared with 60-d dry.