M Battagin

University-Hospital of Padova, Padova, Veneto, Italy

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Publications (3)5.96 Total impact

  • Article: International genetic evaluation of Holstein bulls for overall type traits and body condition score.
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    ABSTRACT: The study documents the procedures used to estimate genetic correlations among countries for overall conformation (OCS), overall udder (OUS), overall feet and legs (OFL), and body condition score (BCS) of Holstein sires. Major differences in traits definition are discussed, in addition to the use of international breeding values (IBV) among countries involved in international genetic evaluations, and similarities among countries through hierarchical clustering. Data were available for populations from 20 countries for OCS and OUS, 18 populations for OFL, and 11 populations for BCS. The IBV for overall traits and BCS were calculated using a multi-trait across-country evaluation model. Distance measures, obtained from genetic correlations, were used as input values in the cluster analysis. Results from surveys sent to countries participating in international genetic evaluation for conformation traits showed that different ways of defining traits are used: the overall traits were either computed from linear or composite traits or defined as general characteristics. For BCS, populations were divided into 2 groups: one scored and evaluated BCS, and one used a best predictor. In general, populations were well connected except for Estonia and French Red Holstein. The average number of common bulls for the overall traits ranged from 19 (OCS and OUS of French Red Holstein) to 514 (OFL of United States), and for BCS from 17 (French Red Holstein) to 413 (the Netherlands). The average genetic correlation (range) across countries was 0.75 (0.35 to 0.95), 0.80 (0.41 to 0.95), and 0.68 (0.12 to 0.89) for OCS, OUS, and OFL, respectively. Genetic correlations among countries that used angularity as best predictor for BCS and countries that scored BCS were negative. The cluster analysis provided a clear picture of the countries distances; differences were due to trait definition, trait composition, and weights in overall traits, genetic ties, and genotype by environment interactions. Harmonization of trait definition and increasing genetic ties could improve genetic correlations across countries and reduce the distances. In each national selection index, all countries, except Estonia and New Zealand, included at least one overall trait, whereas none included BCS. Out of 18 countries, 9 have started genomic evaluation of conformation traits. The first were Canada, France, New Zealand, and United States in 2009, followed by Switzerland, Germany, and the Netherlands in 2010, and Australia and Denmark-Finland-Sweden (joint evaluation) in 2011. Six countries are planning to start soon.
    Journal of Dairy Science 08/2012; 95(8):4721-31. · 2.56 Impact Factor
  • Article: Feasibility of the direct application of near-infrared reflectance spectroscopy on intact chicken breasts to predict meat color and physical traits.
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    ABSTRACT: Physical and color characteristics of chicken meat were investigated on 193 animals by directly applying a fiberoptic probe to the breast muscle and using the visible-near-infrared (NIR) spectral range from 350 to 1,800 nm. Data on pH was recorded 48 h postmortem (pH); lightness (L*), redness (a*), and yellowness (b*) 48 h postmortem; thawing and cooking losses and shear force after freezing. Partial least squares regressions were performed using untreated data, raw absorbance data (log(1/R)), and multiplicative scatter correction plus first or second derivative spectra. Models were validated using full cross-validation, and their predictive ability was determined by root mean square error of cross-validation (RMSE(CV)) and correlation coefficient of cross-validation (r(cv)). Means (±SD) of pH, L*, a*, b*, thawing loss, cooking loss, and shear force were 5.83 ± 0.13, 44.54 ± 2.42, -1.90 ± 0.62, 3.21 ± 3.28, 4.84 ± 2.44%, 19.39 ± 2.95%, and 16.08 ± 3.83 N, respectively. The best prediction models were developed using log(1/R) spectra for b* (r(cv) = 0.93; RMSE(CV) = 1.16) and a* (r(cv) = 0.88; RMSE(CV) = 0.29), while a medium predictive ability of NIR was obtained for pH, L*, and thawing and cooking losses (r(cv) from 0.69 to 0.76; RMSE(CV) from 0.01 to 1.73). Finally, predicted model for shear force (r(cv) = 0.41; RMSE(CV) = 3.18) was unsatisfactory. Results suggest that NIR is a feasible technique for the assessment of several quality traits of intact breast muscle.
    Poultry Science 07/2011; 90(7):1594-9. · 1.73 Impact Factor
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    Article: Bayesian inference of genetic parameters for test-day milk yield, milk quality traits, and somatic cell score in Burlina cows.
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    ABSTRACT: The aim of the study was to infer (co)variance components for daily milk yield, fat and protein contents, and somatic cell score (SCS) in Burlina cattle (a local breed in northeast Italy). Data consisted of 13,576 monthly test-day records of 666 cows (parities 1 to 8) collected in 10 herds between 1999 and 2009. Repeatability animal models were implemented using Bayesian methods. Flat priors were assumed for systematic effects of herd test date, days in milk, and parity, as well as for permanent environmental, genetic, and residual effects. On average, Burlina cows produced 17.0 kg of milk per day, with 3.66 and 3.33 percent of fat and protein, respectively, and 358,000 cells per mL of milk. Marginal posterior medians (highest posterior density of 95%) of heritability were 0.18 (0.09-0.28), 0.28 (0.21-0.36), 0.35 (0.25-0.49), and 0.05 (0.01-0.11) for milk yield, fat content, protein content, and SCS, respectively. Marginal posterior medians of genetic correlations between the traits were low and a 95 percent Bayesian confidence region included zero, with the exception of the genetic correlation between fat and protein contents. Despite the low number of animals in the population, results suggest that genetic variance for production and quality traits exists in Burlina cattle.
    Journal of applied genetics 01/2010; 51(4):489-95. · 1.66 Impact Factor