Between January and July 1992, 8403 monthly test day records were obtained from 3202 ewes from 22 Churra dairy flocks in the Castilla-León region of Spain. Variables measured were milk yield, SCC, and fat and protein percentages; means were 912 ml, 1501 x 10(3) cells/ml, 6.76%, and 6.28%. Analysis of variance showed significant effects of flock, stage of lactation, parity, and type of birth on milk yield, SCC, and composition. Variability in SCC among flocks was high and ranged from 420 to 2719 x 10(3) cells/ml. During lactation, SCC and fat and protein percentages showed increases of 31.2, 37.6, and 20.3%. Twin birth ewes had higher SCC (8.6%) and yield (4.4%) than single birth ewes. However, fat and protein fell 1.7 and .8% in twin birth ewes. The parity effect was highly significant for yield, SCC, and fat; first lactation was always lower. A statistical model similar to that for dairy cattle was used to predict milk yield on the basis of flock, ewes within the flock, lactation stage, parity number, type of birth, and SCC. The model predicted 73% of the variation in milk yield.

Records from monthly test days for milk yield, natural log-transformed SCC, and protein percentage of 10,171 records of 3832 Spanish Churra ewes in 24 herds were analyzed to estimate genetic parameters. Heritabilities and genetic and phenotypic correlations for test day records were estimated using multivariate REML with an animal model, accounting for the effects of litter size, test day within herd group, age at lambing, and month in milk. Heritabilities for test day records of milk, log SCC, and protein percentage were .34, .04, and .13, respectively. Genetic correlations of test day measures of SCC with milk yield and protein percentage were -.37 and .37, respectively; phenotypic correlations were -.05 and .19. Considered as a random effect, test day within herd accounted for 28 and 17% of the total variance of test day milk yield and test day SCC, respectively. The correlation between milk yield and SCC because of the test day within herd, the covariation factor, was estimated to be -.16. Results indicate a moderately high heritability for milk yield, a low heritability for SCC, and moderate, negative genetic relationships between measures of SCC in milk and milk yield.

An animal model was used to estimate the repeatabilities and genetic parameters of linear udder traits of Churra ewes (5265 records from 2015 ewes). In addition, the phenotypic correlations were examined between log SCC and udder traits.Heritabilities of udder depth (0.16), udder attachment (0.17), teat placement (0.24), teat size (0.18), and udder shape (0.24) were similar to those for dairy cattle, making it feasible to use data from the proposed linear system in a breeding program to improve the machine milkability of ewes.Genetic correlations among udder traits were generally favorable, implying that selection for improvement of one trait would result in improvement of others. A notable exception was the genetic correlation between teat placement and teat size of 0.62. Vertical placement of teats was associated with larger teats. Also, genetic correlations between udder and yield traits (milk and protein yields) were small, except for udder depth and teat placement. These exceptions predict worsening udder morphology from selection based solely on milk yield.Phenotypic correlations between udder traits and log SCC indicate that present handling routines led to a greater likelihood of infections for deep udders with large teats. (

The availability of SNP chips for massive genotyping has proven to be useful to genetically characterize populations of domestic cattle and to assess their degree of divergence. In this study, the Illumina BovineHD BeadChip genotyping array was used to describe the genetic variability and divergence among 7 important autochthonous Spanish beef cattle breeds. The within-breed genetic diversity, measured as the marker expected heterozygosity, was around 0.30, similar to other European cattle breeds. The analysis of molecular variance revealed that 94.22% of the total variance was explained by differences within individuals whereas only 4.46% was the result of differences among populations. The degree of genetic differentiation was small to moderate as the pairwise fixation index of genetic differentiation among breeds (F) estimates ranged from 0.026 to 0.068 and the Nei's D genetic distances ranged from 0.009 to 0.016. A neighbor joining (N-J) phylogenetic tree showed 2 main groups of breeds: Pirenaica, Bruna dels Pirineus, and Rubia Gallega on the one hand and Avileña-Negra Ibérica, Morucha, and Retinta on the other. In turn, Asturiana de los Valles occupied an independent and intermediate position. A principal component analysis (PCA) applied to a distance matrix based on marker identity by state, in which the first 2 axes explained up to 17.3% of the variance, showed a grouping of animals that was similar to the one observed in the N-J tree. Finally, a cluster analysis for ancestries allowed assigning all the individuals to the breed they belong to, although it revealed some degree of admixture among breeds. Our results indicate large within-breed diversity and a low degree of divergence among the autochthonous Spanish beef cattle breeds studied. Both N-J and PCA groupings fit quite well to the ancestral trunks from which the Spanish beef cattle breeds were supposed to derive.

The Fossomatic method for SCC was compared with the direct microscopic method in 85 half-udder samples of sheep milk. The correlation coefficient was .986. The repeatability of the Fossomatic method showed average variation coefficients less than 5%. The carry-over effect between samples was less than 5%. The effect of the storage method (fresh milk, refrigerated at 4 degrees C and frozen at -19 degrees C) and the sample age were studied in 48 samples of foremilk and strippings. The storage method had a significant effect on the SCC variation. The average fresh, refrigerated, and frozen sample counts were 125,000, 110,000, and 82,000 cells/ml for foremilk and 201,000, 192,000, and 145,000 cells/ml for strippings, respectively. The effect of age on the refrigerated samples was also significant; counts were reduced by about 14% from d 1 to 7 in both types of milk. The effect of age on the frozen sample varied. These results suggest standardization of age and storage conditions of the milk samples to reduce variation of SCC. The milk must not be frozen.