Search Results (6)

Genetic selection has achieved little progress in reducing mastitis incidence. Mastitis traits are problematic due to the lack of sensitivity of the data and reliance on clinical diagnosis, often missing subclinical cases, and/or on monthly somatic cell count (SCC) measurements. The current measure for mastitis is the lactation average of the somatic cells score (LSCS). We studied two datasets: (1) 148 heifers divided into non-intramammary infected, sub-clinically infected and clinical mastitis groups; (2) data from 89,601 heifers from Israeli Holsteins through the same period divided into “udder healthy” (UH) and “non-healthy” (UNH) by a threshold of SCC 120,000 cells/mL in all nine monthly milk recordings. In study 1, non-infected heifers had significantly (p < 0.05) more partum, production days and overall lifetime milk production compared to clinical and sub-clinically infected. In study 2, UH heifers (20.3%) had significantly higher (p < 0.01) lifetime milk, production days, and lactations. Subdividing datasets by sires, the same analyses detected differences in percentages of UH daughters between the sire groups. Lifetime milk production correlated (r = +0.83, p < 0.001) with udder health status. SCC threshold of less than 120,000 cells/mL during all first lactation measurements indicated healthy udder, providing a valuable insight that this dichotomous trait is advantageous for calculating lifetime net-merit index (NM$) over LSCS. Full article

In Israel, about 26% of produced milk is used to produce hard cheeses and 29% for soft cheeses. Milk with preferred coagulation properties requires a shorter coagulation time and yields a higher curd firmness than milk with inferior coagulation properties. Studies have shown that milk from cows with the B allele of kappa casein (κ-CN) produces more cheese than milk from those with A and E alleles. There is evidence that milk from AE or EE genotype cows is unsuitable for cheese production. In the early 1990s, the proportion of the B allele in Israeli Holstein cattle was about 17%, similar to its prevalence in the Holstein population worldwide. In recent years, however, its proportion has increased to about 40%. We analyzed milk coagulation properties as a function of the cow’s κ-CN genotype, including time in minutes until the beginning of coagulation and curd firmness after 60 min—measured in volts via an optigraph device and scored on a scale of 0–4 by a laboratory technician. Cow selection was based on their sire’s genotype, so that there would be sufficient genotypes that include the rare E allele. A total of 359 cows were sampled from 15 farms: 64 with genotype AA, 142 with AB, 41 with AE, 65 with BB, and 47 with BE. Data were analyzed via the general linear model procedure of SAS. We found the following: (a) There were significant differences between genotypes for optigraph-measured curd firmness. In a multi-comparison test, the BB genotype gave the highest curd firmness, and AB and BE showed a significant advantage compared to AA and AE (9.4, 8.6, 8.4, 6.9, 6.8 V, respectively). Assuming a frequency of about 55% for the A allele, about 30% of the milk delivered to dairy plants comes from AA cows. (b) There was a significant difference between the genotypes in technician-observed curd firmness, with BB scoring significantly higher than AA and AE. (c) The optigraph-measured curd firmness was significantly higher for milk from primiparous cows as compared to milk from second, third, or fourth lactation cows (8.9, 7.8, 7.9, 7.7 V, respectively). The technician-observed curd firmness was significantly higher for primiparous vs. multiparous cows. There was a clear advantage in curd firmness for genotypes that included the B allele compared to those with AA and AE genotypes. We can increase the proportion of the B allele in the population by insemination of cows using bulls with the genotypes AB and BB. This factor should therefore be included in the selection index. Full article

“Livability” was defined as the inverse of the probability of death. The objectives of this study were to estimate the heritability, genetic and phenotypic trends for the livability of Israeli Holstein cows; estimate the genetic and environmental correlations between livability and the nine traits included in the Israeli breeding index; estimate the effect of the inclusion of livability in the Israeli breeding index on expected genetic gains; and compute a genome-wide association study (GWAS) for livability. Seven data sets were analyzed. All data were derived from the database of the Israeli dairy cattle herd-book. The mean livability for the complete data set of 523,954 cows born from 2000 through 2016 was 89.6%. Pregnancy reduced livability by 15%. Livability generally increased with parity and days in milk within parity. Heritability of livability was 0.0082. Phenotypic and genetic trends over the 14-year period from 2000 through 2013 were −0.42% and −0.22% per year. If livability is included in the Israeli breeding index, accounting for 9% of the index, livability would increase by 1.3% and protein production would decrease by 11 kg over the next decade, as compared to the current index. A marker in proximity to the oxytocin–vasopressin locus had the greatest effect in the GWAS. Oxytocin activity in cattle affects calving-associated pathologies and maternal death. Inclusion of livability in the Israeli breeding index is not recommended. Full article

Phenotypic and genetic changes for female fertility and production traits in the Israeli Holstein population over the last three decades were studied in order to determine if long term selection has resulted in reduced heritability and negative genetic correlations. Annual means for conception status, defined as the inverse of the number of inseminations to conception in percent, decreased from 55.6 for cows born in 1983 to 46.5 for cows born in 2018. Mean estimated breeding values increased by 1.8% for cow born in 1981 to cows born in 2018. Phenotypic records from 1988 to 2016 for the nine Israeli breeding index traits were divided into three time periods for multi-trait REML analysis by the individual animal model. For all traits, heritabilities increased or stayed the same for the later time periods. Heritability for conception status was 0.05. The first parity genetic correlation between conception status and protein yield was −0.38. Heritabilities decreased with the increase in parity for protein but remained the same for conception status. Realized genetic trends were greater than expected for cows born from 2008 through 2016 for somatic cell score, conception status and herd-life, and lower than expected for the production traits. Full article

Yearling weight gain in male and female Israeli Holstein calves, defined as 365 × ((weight − 35)/age at weight) + 35, was analyzed from 814,729 records on 368,255 animals from 740 herds recorded between 1994 and 2021. The variance components were calculated based on valid records from 2008 through 2017 for each sex separately and both sexes jointly by a single-trait individual animal model analysis, which accounted for repeat records on animals. The analysis model also included the square root, linear, and quadratic effects of age at weight. Heritability and repeatability were 0.35 and 0.71 in the analysis of both sexes and similar in the single sex analyses. The regression of yearling weight gain on birth date in the complete data set was −0.96 kg/year. The complete data set was also analyzed by the same model as the variance component analysis, including both sexes and accounting for differing variance components for each sex. The genetic trend for yearling weight gain, including both sexes, was 1.02 kg/year. Genetic evaluations for yearling weight gain was positively correlated with genetic evaluations for milk, fat, protein production, and cow survival but negatively correlated with female fertility. Yearling weight gain was also correlated with the direct effect on dystocia, and increased yearling weight gain resulted in greater frequency of dystocia. Of the 1749 Israeli Holstein bulls genotyped with reliabilities >50%, 1445 had genetic evaluations. As genotyping of these bulls was performed using several single nucleotide polymorhphism (SNP) chip platforms, we included only those markers that were genotyped in >90% of the tested cohort. A total of 40,498 SNPs were retained. More than 400 markers had significant effects after permutation and correction for multiple testing (p_nominal < 1 × 10⁻⁸). Considering all SNPs simultaneously, 0.69 of variance among the sires’ transmitting ability was explained. There were 24 markers with coefficients of determination for yearling weight gain >0.04. One marker, BTA-75458-no-rs on chromosome 5, explained ≈6% of the variance among the estimated breeding values for yearling weight gain. ARS-BFGL-NGS-39379 had the fifth largest coefficient of determination in the current study and was also found to have a significant effect on weight at an age of 13–14 months in a previous study on Holsteins. Significant genomic effects on yearling weight gain were mainly associated with milk production quantitative trait loci, specifically with kappa casein metabolism. Full article

The potent hepatotoxin and carcinogen aflatoxin B1 (AFB1) is a common mycotoxin contaminant of grains used in animal feeds. Aflatoxin M1 (AFM1) is the major metabolite of AFB1 in mammals, being partially excreted into milk, and is a possible human carcinogen. The maximum permitted concentration of AFM1 in cows’ milk is 0.05 μg/kg in Israel and the European Union. Since milk yield and the carry-over of AFB1 in the feed to AFM1 in the milk are highly correlated, it was considered important to determine the AFM1 carry-over in Israeli-Holstein dairy cows, distinguished by world record high milk production. Twelve such cows were used to determine AFM1 carry-over following daily oral administration of feed containing ~86 μg AFB1 for 7 days. The mean carry-over rate at steady-state (Days 3–7) was 5.8% and 2.5% in mid-lactation and late-lactation groups, respectively. The carry-over appears to increase exponentially with milk yield and could be described by the equation: carry-over% = 0.5154 e^{0.0521 × milk yield}, with r² = 0.6224. If these data truly reflect the carry-over in the national Israeli dairy herd, the maximum level of AFB1 in feed should not exceed 1.4 μg/kg, a value 3.6 times lower than the maximum residue level currently applied in Israel. Full article