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

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

Kinetics of fat and protein secretion in dairy cattle, sheep, goats and buffaloes

The negative correlations of fat and protein concentrations and milk yield, existing in all ruminants dairy species (Oftedal, 1984; Mepham, 1987), reflect a deep mechanism regulating the respective kinetics of secretion of carrier (mainly lactose which is the major responsible for the water drawn to the milk) and of fat and protein. Whereas the correlation coefficients are low (from –0.2 to – 0.4), fat and protein daily yield and milk production are positively and strongly linked (r = 0.8÷0.9). It means that more productive animals have higher fat and protein yield, but their milk has lower concentration of these components. The aim of this work is to investigate the relationships between milk, fat and protein yield in all main ruminant dairy species by using a simple mathematical model

I Modelli compartimentali nello studio della dinamica delle popolazioni naturali

Compartmental models are in common use in the study of many biological, agricultural and economic systems. The present paper is an attempt for a review of the great potentialities of the compartmental model originally proposed by Argentesi, De Bernardi and Di Cola (1974 a,b) for the study of the dynamics of single species populations with continuous recruitment. By means of this mathematical model it is possible to derive a simple methodology for an indirect estimation of some dynamic parameters which are not directly evaluable with experiments but which are essential for the biological interpretation of the biotic and abiotic interactions of the populations. The examples which are reported of application of the compartmental model to several experimental situations show that the methodology may be used to evidence the regulatory and perturbatory processes acting on fecundity and mortality rates of populations. In the compartmental framework the population dynamics can also be expressed as biomass in order to evaluate the population production. The parameters of the ordinary differential equations can be estimated via linear programming, which easily permits the introduction of constraints on the parameter value,and the derivative estimation via base function,that avoids the error amplifications of the numerical derivative

Scelta di un modello algebrico semplice per il calcolo degli scambi energetici nelle bovine in lattazione

In order to describe the energetic exchanges in lactating cows, various mathematic models both «mechanicistic» and «empiric» types have been developed in recent years. The former type models make it possible to evaluate the elementary processes, but require both the detailed knowledge of numerous variables and the availability of suitable capacity computers. The latter type models are instead simpler to handle, but they merely reproduce the experimental data, without adding any new information: among these models, a simple algebraic one, originally devised by Wood, makes it possible, on the basis of III definited hypothesis, to foresee the milk yield, the body weight variations and the energetic requirements of lactating cows. This model has been tested on a sample of 50 Hostein Friesian cows, using a minicomputer with elementary Basic; the results show an adeguate estimate of the paramethers, based on the study of easily identified characteristics of the lactation curve

A Multivariate measure of lactation persistency for dairy sheep

The persistency of lactation, i.e. the ability of animals to maintain a rconstant level of production after the lactation peak, represents an interesting trait for animal breeding strategies, allowing for the increase of profitability of animal husbandry via the reduction of production costs. Dairy cattle with flatter curves show a higher reproductive efficiency, a better metabolic status and have their nutritional requirements more constantly spread throughout lactation, allowing for the use of cheaper feeds (Dekkers et al., 1998; Solkner and Fucks, 1987). Also in dairy sheep the persistency could represent an interesting trait for breeding purposes. A main problem for the introduction of this trait in an aggregate genotype is represented by the difficulty in finding an objective measure: several measurements of lactation persistency have been proposed but none of them is widely accepted (Gengler, 1996). Recently a new index of the persistency based on multivariate Factor analysis, has been proposed for dairy cattle (Macciotta et al., 2002). Aim of the present work is to check the suitability of this index to discriminate lactation curves with different persistency and to analyse the effect of some environmental factor on this trait

L'Uso dell'analisi multicaratteriale nella stima dell'ereditabilità della curva di lattazione in bovine da latte

The heritability estimation of the shape of the lactation curve is quite complex. However, it now seems to be resolvable thanks to a combination of two mathematical methods which up to now have been developed indipendently. One method is a multitrait analysis of variance components which enables us to estimate the genetic components of phenotypic variance and the trait correlation. The other method is the mathematical modelling of biological phenomena which, when applicable, provides a mathematical description of the relationship between the fundamental quantities under consideration. Multitrait analysis, when applied to lactation curve parameters, enables us to estimate not only the heritability but also the genetic and phenotipic correlations of the essential elements of the lactation curve

Modelling extended lactation curves for milk production traits in Italian Holsteins

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 050 to 088 and from 053 to 096 for fat and protein yields, respectively, in the different scenarios). Results highlight great flexibility and accuracy of this multivariate technique

Analysis of genetic correlations between multivariate measures of lactation persistency and somatic cell score in Italian Simmental cattle

Genetic relationships between lactation curve traits and Somatic Cell Count are of great interest for dairy cattle breeding. Factor Analysis (MFA) and Principal Component Analysis (PCA) can be used to extract from the correlation matrix of milk test day records new unobservable (latent) variables that can be related to lactation curve shape. Previous researches report that MFA is particularly able to extract two latent variables related with level of production in early lactation (PEL) and lactation persistency (PERS), respectively, whereas PCA yields a leading component related to the average level of production (AVY) for the whole lactation and a second component negatively related with tests of early lactation and positively with tests of the second part of lactation (SLOPE). Aim of this work was to estimate genetic correlations between lactation curve shape traits and Somatic Cell Score (SCS). MFA and PCA were carried out on a data set of 16,020 lactations of Italian Simmental cows, each with six TD records for milk yield recorded with the A4 scheme. Genetic parameters were estimated with a bivariate animal model that included fixed effects of herd-test date, parity*age*lactation stage (only parity*age for lactation curve traits), calving season, and random effects of additive genetic and permanent environment. Heritability estimates were moderate for lactation curve traits (0.15, 0.15, 0.21 and 0.09 for PEL, PERS, AVY and SLOPE, respectively) and low for SCS (0.09). Correlations between lactation curve traits and SCS were favourable, i.e. negative, except for the level of production in early lactation. In particular, the genetic improvement of lactation persistency result in a contemporary reduction of SCS (rg -0.55 and -0.51 with PERS and SLOPE, respectively) whereas the increase of level of production in early lactation can lead to a moderate increase of SCS (rg 0.13). Finally, the two measures of persistency could be used for different selection strategies: the use of PERS may allow for the increase of persistency together with the total lactation yield whereas the use of SLOPE may result in an improvement of the lactation curve shape without modifying total lactation yield

Microarray data analysis of gene expression levels in lactating cows treated with bovine somatotropin

Administration of bovine somatotropin (bST) to lactating cows results in an increase in milk production from 10 to 15%. While physiological mechanisms involved in bST administration are well known, there is limited knowledge about the mechanisms that regulate the bST action at genetic level. For this reason, a microarray experiment was conducted to identify differentially expressed genes when bST is given to milking cows. Sixteen high-density microarrays for cattle, each containing 18,263 gene spots, were used. RNA was extracted from the mammary tissue of four lactating Holstein cows, five and two days before, and one and six days after bST administration. A total of 1,251 and 1,167 differentially expressed genes were detected for mean and median expression intensities, respectively. Only the 115 genes which were identified by both mean and median intensities were taken into account. These genes were grouped into 8 clusters according to changes in expression through time points