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Jersey dairy cattle breed is characterized by relatively low milk yield (MY), but high milk solids content. The low productivity and its udder conformation make Jersey a suitable breed for once-a day-milking, resulting in less stress load for animals and higher milk quality. For these reasons Jersey is appreciated by the dairy industry. The present study aimed to assess the phenotypic variation of MY and milk quality traits in Italian Jersey (IJ), and to evaluate the heterogeneity of variance across IJ herds. Sources of variation were investigated through a mixed linear model, including the fixed effects of days in milk, parity, calving season, milking frequency, recording type, the interaction between days in milk and parity, and the random effects of herd-test-day (HTD) and cow. Heterogeneity of variance was assessed across herds classified as low (L), medium (M) or high (H) according to their average MY and milk quality traits. Results highlighted the high contents of milk fat (5.18%), protein (4.08%) and casein (3.16%) of IJ cows. Somatic cell score (SCS) averaged 3.35 units, which is quite high and suggest that SCS should be monitored carefully in IJ herds, especially through an improvement of management practices. Milk yield showed moderate negative correlations with milk composition and SCS. Milk with greater fat content had also greater protein and casein content, whereas SCS resulted moderately and negatively correlated with lactose content. Phenotypic variances of MY and milk quality traits were mainly related to animal effect; on the other hand phenotypic variance of milk urea nitrogen content was mainly affected by HTD effect. Finally, heterogeneity of variance was observed across L, M and H herds, in a way that highly ranked herds showed greater standard deviation. Future research should investigate the impact of accounting or not for heterogeneity of variance in genetic evaluation of IJ breed.

The importance of milk mineral composition for human health is well known and accepted. Because of that, a rapid and cost effective monitoring of milk mineral composition is an important goal to achieve. This study aimed to investigate the potential of mid-infrared spectroscopy to predict calcium, potassium, sodium, magnesium and phosphorus in milk through the use of Uninformative Variables Elimination partial least squares (UVE-PLS) procedure. Individual samples (n=246) of Holstein-Friesian, Brown Swiss, Simmental and Alpine Grey cows from different stages of lactation and parities were collected from single-breed herds. Reference analysis was undertaken with inductively coupled plasma optical emission spectrometry (ICP-OES) in accordance with standardized methods. For each milk sample MIRS analysis in the range of 900 to 5,000 cm-1 was performed. Prediction models were developed using PLS regression after UVE for each considered trait and prediction accuracy was based on leave one out cross validation (246 segments). The coefficient of determination in cross validation was greatest for phosphorus (0.72), followed by potassium (0.70), calcium (0.68) and magnesium (0.67). Sodium prediction was poor, with a very low coefficient of determination (0.46). All the prediction models were unbiased (P

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This study aimed to estimate genetic parameters for 19 linear type traits related to frame, udder, and feet and legs, and for final score of 10,305 first-parity Jersey cows evaluated between 2004 and 2016. Since scoring of locomotion in Jersey breed started in 2009, a subset of 6853 animals was extracted from the original data and used to investigate sources of variation and heritability of locomotion score, and its associations with the other traits. Univariate animal models were used to estimate variance components of type traits and bivariate analyses were implemented to obtain genetic correlations between traits. Fixed effects were herd-year-classifier, season of evaluation, stage of lactation at scoring and age at calving, and the random effects were additive genetic animal and the residual. Herd-year-classifier was the major source of variation affecting the traits. Heritabilities were low with the only exception of a moderate heritability (0.32 ± 0.02) for stature. The lowest heritabilities were estimated for feet and legs traits with values between 0.04 ± 0.02 (rear leg set side view, rear leg set rear view and locomotion) and 0.07 ± 0.02 (foot angle). The final score had heritability of 0.20 ± 0.02. Genetic correlations were generally stronger than their phenotypic counterparts. Overall, frame traits were weakly correlated with feet and legs, and udder traits, except for rump width, which showed moderate correlations with almost all traits, and angularity which showed the greatest correlations with rear udder height (0.61 ± 0.10) and rear udder width (0.62 ± 0.11). Genetic correlations between locomotion and frame traits ranged from 0.08 ± 0.22 (angularity) to 0.32 ± 0.16 (stature). The strongest correlations were estimated between locomotion and other feet and legs traits, but also with front teat placement (0.97 ± 0.19) and with rear teat placement (0.88 ± 0.17). Results of the present study will be used to enhance genetic evaluation of linear type traits in Jersey cattle breed.

Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 testday records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31 ± 0.05 (5 DIM) to 0.67 ± 0.04 (181 DIM) for Ca, from 0.18 ± 0.03 (60 DIM) to 0.24 ± 0.05 (305 DIM) for K, from 0.08 ± 0.03 (15 DIM) to 0.37 ± 0.03 (223 DIM) for Mg, from 0.16 ± 0.03 (30 DIM) to 0.37 ± 0.04 (305 DIM) for Na and from 0.21 ± 0.04 (12 DIM) to 0.57 ± 0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38 ± 0.21 (5 DIM) to 0.79 ± 0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.

This study aimed to investigate factors affecting protein fractions, namely &alpha, casein (&alpha, CN), &beta, casein (&beta, CN), &kappa, casein (&kappa, lactoglobulin (&beta, LG) and &alpha, lactalbumin (&alpha, LA) predicted from milk infrared spectra in milk of dairy and dual-purpose cattle breeds. The dataset comprised 735,328 observations from 49,049 cows in 1782 herds. Results highlighted significant differences of protein fractions in milk of the studied breeds. Significant variations of protein fractions were found also through parities and lactation, with the latter thoroughly influencing protein fractions percentage. Interesting correlations (r) were estimated between &beta, CN, &kappa, CN and &beta, LG, expressed as percentage of crude protein, and milk urea nitrogen (r = 0.31, &minus, 0.20 and &minus, 0.26, respectively) and between &alpha, LA and fat percentage (r = 0.41). The present study paves the way for future studies on the associations between protein fractions and milk technological properties, and for the estimation of genetic parameters of predicted protein composition.

Simple Summary In order to assess sources of variation related to Polverara breed plumage color (black vs. white), we carried out genome-wide analyses to identify the genomic regions involved in this trait. The present work has revealed new candidate genes involved in the phenotypic variability in local chicken populations. These results also contribute insights into the genetic basis for plumage color in poultry, and confirm the great complexity of the mechanisms that control this trait. Abstract Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

si analizza l'iscrizione musiva pavimentale di Euterio, di controversa interpretazione, specialmente riguardo alla presunta aggiunta dell'acclamazione finale.