Estimation of genetic gain in milk yield by selection in a closed herd of dairy cattle

The aim of the present study was to estimate genetic parameters for calcium (Ca), phosphorus (P) and titratable acidity (TA) in bovine milk predicted by mid-IR spectroscopy (MIRS). Data consisted of 2458 Italian Holstein − Friesian cows sampled once in 220 farms. Information per sample on protein and fat percentage, pH and somatic cell count, as well as test-day milk yield, was also available. (Co)variance components were estimated using univariate and bivariate animal linear mixed models. Fixed effects considered in the analyses were herd of sampling, parity, lactation stage and a two-way interaction between parity and lactation stage; an additive genetic and residual term were included in the models as random effects. Estimates of heritability for Ca, P and TA were 0.10, 0.12 and 0.26, respectively. Positive moderate to strong phenotypic correlations (0.33 to 0.82) existed between Ca, P and TA, whereas phenotypic weak to moderate correlations (0.00 to 0.45) existed between these traits with both milk quality and yield. Moderate to strong genetic correlations (0.28 to 0.92) existed between Ca, P and TA, and between these predicted traits with both fat and protein percentage (0.35 to 0.91). The existence of heritable genetic variation for Ca, P and TA, coupled with the potential to predict these components for routine cow milk testing, imply that genetic gain in these traits is indeed possible.

Section: Heritabilitiesmentioning

confidence: 99%

Genetic parameters for milk mineral content and acidity predicted by mid-infrared spectroscopy in Holstein–Friesian cows

Toffanin

Penasa

McParland

et al. 2015

“…It was assumed that all four traits in the breeding objective were measured simultaneously (that is, in each female, in each lactation). The genetic progresses in the population were calculated adding up the progress in each group, following the Rendel and Robertson (1950) formula to take into account the differences in the generation interval. The different proportions of use of natural service rams (64%), testing AI rams (17%) and proven AI rams (19%) were included in the formula.…”

Section: Estimation Of Genetic Gainsmentioning

confidence: 99%

Economic weights of fertility, prolificacy, milk yield and longevity in dairy sheep

Legarra

Ramón

Ugarte

et al. 2007

Economic weights have been estimated in two breeds (Latxa and Manchega) using economic and technical data collected in 41 Latxa and 12 Manchega dairy sheep flocks. The traits considered were fertility (lambing per year), prolificacy (number of lambs), milk yield (litres) and longevity (as productive life, in years). A linear function was used, relating these traits to the different costs in the flock. The variable costs involved in the profit function were feed and labour. From this function, economic weights were obtained. Labour is considered in the Latxa breed to be a constraint. Moreover, farm profits are unusually high, which probably means that some costs were not included according to the economic theory. For that reason, a rescaling procedure was applied constraining total labour time at the farm. Genetic gains were estimated with the resulting economic weights to test if they give any practical difference. Milk yield only as selection criterion was also considered. The medians of the estimated economic weights for fertility, prolificacy, milk yield and longevity were 138.60 e per lambing, 40.00 e per lamb, 1.18 e per l, 1.66 e per year, and 137.66 e per lambing, 34.17 e per lamb, 0.73 e per l, 2.16 e per year under the linear approach in the Latxa and Manchega breeds respectively. Most differences between breeds can be related to differences in production systems. As for the genetic gains, they were very similar for all economic weights, except when only milk yield was considered, where a correlated decrease in fertility led to a strong decrease in profit. It is concluded that the estimates are robust for practical purposes and that breeding programmes should consider inclusion of fertility. More research is needed to include other traits such as somatic cell score, milk composition and udder traits.

“…The forgotten 'omics' Genetic gain is known to be a function of selection intensity, accuracy of selection, genetic variation present among selection candidates, and generation interval (Rendel and Robertson, 1950). However, what is missing from this simple definition is how the phenotype under investigation reflects the true trait of interest over and above that reflected in the heritability.…”

Section: Challenges and Future Researchmentioning

confidence: 99%

The integration of ‘omic’ disciplines and systems biology in cattle breeding

Berry

Meade

Mullen

et al. 2011

Enormous progress has been made in the selection of animals, including cattle, for specific traits using traditional quantitative genetics approaches. Nevertheless, considerable variation in phenotypes remains unexplained, and therefore represents potential additional gain for animal production. In addition, the paradigm shift in new disciplines now being applied to animal breeding represents a powerful opportunity to prise open the 'black box' underlying the response to selection and fully understand the genetic architecture controlling the traits of interest. A move away from traditional approaches of animal breeding toward systems approaches using integrative analysis of data from the 'omic' disciplines represents a multitude of exciting opportunities for animal breeding going forward as well as providing alternatives for overcoming some of the limitations of traditional approaches such as the expressed phenotype being an imperfect predictor of the individual's true genetic merit, or the phenotype being only expressed in one gender or late in the lifetime of an animal. This review aims to discuss these opportunities from the perspective of their potential application and contribution to cattle breeding. Harnessing the potential of this paradigm shift also poses some new challenges for animal scientists -and they will also be discussed.