952 resultados para apple yield


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The effect of a commercial organic acid (OA) product on BW loss (BWL) during feed withdrawal and transportation, carcass yield, and meat quality was evaluated in broiler chickens. Two experiments were conducted in Brazil. Commercial houses were paired as control groups receiving regular water and treated groups receiving OA in the water. Treated birds had a reduction in BWL of 37 g in experiment 1 and 32.2 g in experiment 2. In experiment 2, no differences were observed in carcass yield between groups. Estimation of the cost benefit suggested a 1: 16 ratio by using the OA. In experiment 3, conducted in Mexico, significant differences on water consumption, BWL, and meat quality characteristics were observed in chickens that were treated with the OA (P < 0.05). These data suggest this OA product may improve animal welfare and economic concerns in the poultry industry by reducing BWL and improving meat quality attributes.

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The knowledge of the meat production from different buffalo breeds and their crossings in different feeding systems becomes necessary for the supply of subsidies to whole productive meat chain. Some quantitative carcass traits of Mediterranean buffaloes bulls, finished in feedlot, with initial age of fourteen months and 330 kg live weight, slaughtered with 450, 480, 510 and 540 kg, were evaluated. The diet contained 13% crude protein, 2.68 Mcal digestible energy/kg DM and a roughage : concentrate ratio of 25:75. Regression equations for prediction weight and yield of primal cuts of carcass as a function of slaughter weight were obtained. Carcass dressing percent increased as the slaughter weight increased (49.2; 49.5; 49.7; and 49.9%). The Pistola Style cut weight although increasing linearly in weight (108.2; 117.6; 124.0 and 130.7 kg) as the slaughter weight increased, declined linearly when expressed in relation to cold carcass weight (49.5; 49.0; 48.6 and 48.2%). In this experimental conditions Mediterranean young bulls slaughtered between 450 to 540 kg of live weight showed increasing yields of cold carcass, forequarter and thin flank.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The use of markers distributed all long the genome may increase the accuracy of the predicted additive genetic value of young animals that are candidates to be selected as reproducers. In commercial herds, due to the cost of genotyping, only some animals are genotyped and procedures, divided in two or three steps, are done in order to include these genomic data in genetic evaluation. However, genomic evaluation may be calculated using one unified step that combines phenotypic data, pedigree and genomics. The aim of the study was to compare a multiple-trait model using only pedigree information with another using pedigree and genomic data. In this study, 9,318 lactations from 3061 buffaloes were used, 384 buffaloes were genotyped using a Illumina bovine chip (Illumina Infinium (R) bovineHD BeadChip). Seven traits were analyzed milk yield (MY), fat yield (FY), protein yield (PY), lactose yield (LY), fat percentage (F%), protein percentage (P%) and somatic cell score (SCSt). Two analyses were done: one using phenotypic and pedigree information (matrix A) and in the other using a matrix based in pedigree and genomic information (one step, matrix H). The (co) variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year-calving season), number of milking (2 levels), and age of buffalo at calving as (co) variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The heritability estimates using matrix A were 0.25, 0.22, 0.26, 0.17, 0.37, 0.42 and 0.26 and using matrix H were 0.25, 0.24, 0.26, 0.18, 0.38, 0.46 and 0.26 for MY, FY, PY, LY, % F, % P and SCCt, respectively. The estimates of the additive genetic effect for the traits were similar in both analyses, but the accuracy were bigger using matrix H (superior to 15% for traits studied). The heritability estimates were moderated indicating genetic gain under selection. The use of genomic information in the analyses increases the accuracy. It permits a better estimation of the additive genetic value of the animals.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)