A. Cappio-Borlino

Lactation curves of Sarda breed goats estimated with test day models.

Test day records of milk yield (38,765), fat and protein contents (11,357) of Sarda goats (the most numerous Italian goat breed) were analysed with mixed linear models in order to estimate the effects of test date (month and year of kidding for fat and protein contents) parity, number of kids born, altitude of location of flocks (<200 m asl, 200-500 m asl, >500 m asl), flocks within altitude and lactation stage (eight days-in-milk intervals of 30 d each) on milk production. All factors considered in the models affected milk traits significantly. Milk yield was lower in first parity goats than in higher parities whereas fat and protein contents showed an opposite trend. Goats with two kids at parturition had a higher milk yield than goats with one kid and tended to have lower fat and protein percentages. Repeatability between test days within lactation was 0.34, 0.17 and 0.45 for milk yield, fat content and protein content, respectively. Lactation curves of goats farmed at different altitudes were clearly separated, especially for milk yield. Results of the present study highlight differences in milk production traits among the three subpopulations that have been previously identified within the Sarda breed on the basis of the morphological structure of animals and altitude of location of flocks.

Using eigenvalues as variance priors in the prediction of genomic breeding values by principal component analysis

Genome-wide selection aims to predict genetic merit of individuals by estimating the effect of chromosome segments on phenotypes using dense single nucleotide polymorphism (SNP) marker maps. In the present paper, principal component analysis was used to reduce the number of predictors in the estimation of genomic breeding values for a simulated population. Principal component extraction was carried out either using all markers available or separately for each chromosome. Priors of predictor variance were based on their contribution to the total SNP correlation structure. The principal component approach yielded the same accuracy of predicted genomic breeding values obtained with the regression using SNP genotypes directly, with a reduction in the number of predictors of about 96% and computation time of 99%. Although these accuracies are lower than those currently achieved with Bayesian methods, at least for simulated data, the improved calculation speed together with the possibility of extracting principal components directly on individual chromosomes may represent an interesting option for predicting genomic breeding values in real data with a large number of SNP. The use of phenotypes as dependent variable instead of conventional breeding values resulted in more reliable estimates, thus supporting the current strategies adopted in research programs of genomic selection in livestock.

Somatic variability of Sarda goat breed analysed by multivariate methods

Somatic measurements of 780 Sarda goats were analysed by multivariate statistical methods to investigate the morphostructural variability of this breed. Discriminant analysis highlighted a gradual increase in size passing from flocks located on mountain (M) to hill (H) and coast (C) (Mahalanobis distances 1.159, 1.07 and 3.37 between M–H, H–C and M–C, respectively; P<0.001). Four latent common factors explained different quotas of original somatic (co)variances (70, 90 and 56% in mountain, hill and coast, respectively). Such behaviour can be related to the effect of both different environmental conditions and crosses with other breeds on body development of goats. The same reasons can also explain differences in the relative frequencies of udder conformation types, as in the case of pear-shaped udders between mountain and coast flocks (12 vs. 18%, respectively, P<0.001).

The shape of sarda ewe lactation curve analysed by a compartimental model

Abstract The lactation curve of the dairy Sarda sheep breed is characterised by a notable dimorphism. Empirical mathematical models used to represent the lactation curve of dairy cattle can describe the regular curves but in the case of ‘irregular’ (or decayed) curves, they give parameter estimates which are out of the range of significance. For this reason, a mechanistic mathematical model of the milk secretion process, based on a physiological theory of the mammary gland, was analysed. According to the different evolution of the processes of activation and inactivation of mammary secretory cells, the output of the model is a biexponential function or a monoexponential function. Lactations of sixty-four mature Sardinian ewes were analysed. The biexponential function fitted regular lactation curves ( R 2 = 0.87) and the monoexponential form fitted decayed curves ( R 2 = 0.80). Parameter estimates were submitted to analysis of variance to estimate the influence of production level, type of lambing and udder health. The dimorphism of the lactation curve of the sheep does not seem to be affected by main environmental factors but a genetic influence could be hypothesised.

Enzymes (Isoenzyme System) as homeostatic mechanisms the isoenzyme (ADA2) of adenosine deaminase of human monocytes‐macrophages as a regulator of the 2′deoxyadenosine

Regarding homeostatic mechanisms in the enzyme (isoenzymes) and substrate system we show through a simulation model obtained by STELLA II software that: (i) a pair of isoenzymes (Is1 and Is2) that have different affinity for the substrate (Is2 affinity < ls1 affinity), can constitute an efficient homeostatic mechanism: by varying the relative concentration of the isoenzymes in the system, the levels of the substrate can be controlled; (ii) the isoenzymes ADA1 and ADA2 of adenosine deaminase (ADA) that have different affinity for the substrate 2′deoxyadenosine (ADA2 has very weak affinity for 2′deoxyadenosine) constitute, inside human Monocytes‐Macrophages, a homeostatic mechanism that assures an up‐regulation of 2′deoxyadenosine and a down‐regulation of a second substrate (adenosine) for which the affinity of the two isoenzymes is similar.

Issues and perspectives in dairy sheep breeding

Abstract The present review consists of two parts. In the first part, the authors briefly describe the state of the art of breeding programmes for Italian dairy sheep; then they report new models for genetic evaluation and consider the problem of genotype × environment interaction and the impact of farming systems on the genetic merit of animals. In the second part new breeding goals regarding the evolution of milk quality concept and the increasing importance of functional traits are reported. Regarding milk quality, the authors especially focus on the traits related to cheese-making ability and on the nutraceutical aspects of milk. Among functional traits, resistance to diseases (mastitis and Scrapie) has been highlighted for its great importance in livestock species. Finally, the perspectives of marker-assisted selection have also been reported.

Modelling extended lactation curves for milk production traits in Italian Holsteins

References Test day records of milk production traits (milk yield, fat and protein percentage, and somatic cell score) of 45,132 Italian Holstein cows were analyzed with seven mathematical models in order to assess the main features of lactations of different length. Lactations curves were grouped according to parity (1, 2, and 3) and lactation length (1<350d; 2=from 351 to 450d; 3=from 451 to 650d; 4=651 to 1000d). Models with a larger number of parameters showed better fitting performances for all classes of length for milk yield, whereas poor fitting was observed for fat and protein percentages and SCS in the 651-1000d class. In lactation with length>650d, peak yield was about 31, 37, and 39 kg for first, second, and third parity respectively; peak was predicted at around 60 and 40 days for younger and older animals respectively. The asymptotic level of production was below 10 kg.

Use of a partial least-squares regression model to predict test day of milk, fat and protein yields in dairy goats

A model able to predict missing test day data for milk, fat and protein yields on the basis of few recorded tests was proposed, based on the partial least squares (PLS) regression technique, a multivariate method that is able to solve problems related to high collinearity among predictors. A data set of 1731 lactations of Sarda breed dairy Goats was split into two data sets, one for model estimation and the other for the evaluation of PLS prediction capability. Eight scenarios of simplified recording schemes for fat and protein yields were simulated. Correlations among predicted and observed test day yields were quite high (from 0·50 to 0·88 and from 0·53 to 0·96 for fat and protein yields, respectively, in the different scenarios). Results highlight great flexibility and accuracy of this multivariate technique.

Fit of different functions to the individual deviations in random regression test day models for milk yield in dairy cattle

Abstract The shape of individual deviations of milk yield for dairy cattle from the fixed part of a random regression test day model (RRTDM) was investigated. Data were 53,217 TD records for milk yield of 6,229 first lactation Canadian Holsteins in Ontario. Data were fitted with a model that included the fixed effects of herd-testdate, DIM interval nested within age and season of calving. Residuals of the model were then fitted with the following functions: Ali and Schaeffer 5 parameter model, fourth-order Legendre Polynomials, and cubic spline with three, four or five knots. Result confirm the great variability of shape that can be found when individual lactation are modeled. Cubic splines gave better fitting pe4rformances although together with a marked tendency to yield aberrant estimates at the edge of the lactation trajectory.

Meta-analysis of nutritional effects on conjugated linoleic acid (CLA) in milk fat of dairy cows

Abstract A meta-analysis was carried out on 41 selected studies to obtain more reliable results about the influence of some nutritional factors on conjugated linoleic acid (CLA) in milk fat. Data were analysed with a linear mixed model, including the study as random variable, that highlighted a significant effect on milk CLA content of fat source and the physical form of the lipid supplement used in the diet. The content of fat in the diet and the forage/concentrate ratio seem do not have significant effects.