989 resultados para Carcass traits


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The breeding program for beef cattle in Japan has changed dramatically over 4 decades. Visual judging was done initially, but progeny testing in test stations began in 1968. In the 1980s, the genetic evaluation program using field records, so-called on-farm progeny testing, was first adopted in Oita, Hyogo, and Kumamoto prefectures. In this study, genetic trends for carcass traits in these 3 Wagyu populations were estimated, and genetic gains per year were compared among the 3 different beef cattle breeding programs. The field carcass records used were collected between 1988 and 2003. The traits analyzed were carcass weight, LM area, rib thickness, s.c. fat thickness, and beef marbling standard number. The average breeding values of reproducing dams born the same year were used to estimate the genetic trends for the carcass traits. For comparison of the 3 breeding programs, birth years of the dams were divided into 3 periods reflecting each program. Positive genetic trends for beef marbling standard number were clearly shown in all populations. The genetic gains per year for all carcass traits were significantly enhanced by adopting the on-farm progeny testing program. These results indicate that the on-farm progeny testing program with BLUP is a very powerful approach for genetic improvement of carcass traits in Japanese Wagyu beef cattle.

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Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT.

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The objective was to evaluate the effects of genetic group and age on growth, carcass, and meat traits of rabbits. A total of 144 straightbred Botucatu and White German Giant x Botucatu crossbred rabbits were involved. Rabbits were weaned at 35 d and sequentially, slaughtered, four per genetic group x sex combination, at: 42, 49, 56, 63, 70, 77, 84 and 91 d. A 2x2 factorial arrangement was employed in a completely randomized design with repeated measures for growth traits, and a split-plot for carcass and meat traits. Crossbred rabbits were heavier (2032 vs. 1962 g; P < 0.01), consumed more feed (143.5 vs. 131.0 g/d; P < 0.01), and presented higher slaughter weight (2169 vs. 2093 g, P=0.02) and dressing percentage (59.0 vs. 58.2%; P=0.07) than straightbreds throughout the experiment. No difference between genetic groups was detected for feed conversion and empty gastrointestinal weight corrected for slaughter weight (SW). Crossbreds showed higher skin weight (308.2 vs. 299.7 g, P = 0.06) and distal parts of leg weight (75.7 vs. 71.4 g; P < 0.01), both corrected for SW. No genetic group effect was detected on dissectible fat and hind part weights. Chilled commercial carcass (1284 vs. 1229 g: P=0.02), chilled reference carcass (1036 vs. 1000 g, P=0.06), fore part (297.9 vs. 283.3 g; P=0.01) and loin (308.7 vs. 295.5 g; P=0.05) were heavier in crossbreds than in straightbreds, but these differences were attributed to differences in SW. Uncorrected weights of head, kidneys, liver and thoracic viscera were higher in the crossbred group, but only head (116.6 vs. 113.6 g; P=0.06) and thoracic viscera (30.4 vs. 28.6 g; P=0.01) were, in fact, proportionately heavier in crossbreds than in straightbreds. No effect of genetic group was detected on meat to bone ratio, muscle ultimate pH and chemical composition of the Longissimus dorsi muscle. All traits, except for ash and fat contents of the Longissimus muscle, showed age effects (P < 0.01). Crossbreeding may be recommended for the production of whole commercial carcasses, but it is not clearly advantageous for the production of retail cuts. Slaughter should take place between 63 and 70 d of age for both genetic groups.

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Associations between four microsatellite markers on chromosome 11 and five on chromosome 13 with performance, carcass and organs traits were investigated in chickens using a least-squares approach applied to single-marker analysis. Three hundred and twenty seven F 2 chickens from the EMBRAPA broiler×layer experimental population were evaluated for 16 traits: five related to performance, five to carcass and five to organs, plus the hematocrit. Two significance thresholds were considered: p<0.05 and p<0.0056; the last value resulted from the application of a multiple tests analyses correction. On chromosome 11, six associations (p<0.05) between the genotypes of two markers with four growth related and one carcass trait were found. On chromosome 13, six associations (p<0.05) between marker genotypes and three performance traits, eight associations (p<0.05) between marker genotypes and two carcass traits and eight associations (p<0.05) between marker genotypes and four organs traits were detected. These associations were indications of the presence of quantitative trait loci on these chromosomes, especially on chromosome 13. In this chromosome, the strongest evidence was for body weight at 41 days of age and percentage of carcass because the p-values exceeded the multiple test threshold (p<0.0056), but also for breast percentage and heart weight due to the large number of markers (four) on chromosome 13 associated with each one of these traits. These associations should be further investigated by interval mapping analyses to find QTL positions and to allow the estimation of their effects. © Asian Network for Scientific Information, 2009.

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In the past, the focus of broiler breeding programs on yield and carcass traits improvement led to problems related to meat quality. Awareness of public concern for quality resulted in inclusion of meat quality traits in the evaluation process. Nevertheless, few genes associated with meat quality attributes are known. Previous studies mapped quantitative trait loci for weight at 35 and 42 days in a region of GGA4 flanked by the microsatellite markers, MCW0240 and LEI0063. In this region, there are 2 fibroblast growth factor binding protein (FGFBP) genes that play an important role in embryogenesis, cellulardifferentiation, and proliferation in chickens. The objective of this study was to identify and associate single nucleotide polymorphisms (SNPs) in FGFBP1 and FGFBP2 with performance, carcass, and meat quality in experimental and commercial chicken populations. In the commercial population, SNP g.2014G>A in FGFBP1 was associated with decreased carcass weight (P < 0.05), and SNP g.651G>A in FGFBP2 was associated with thawing loss and meat redness content (P < 0.05). Four haplotypes were constructed based on 2 SNPs and were associated with breast weight, thawing loss, and meat redness content. The diplotypes were associated with thawing loss, lightness, and redness content. The SNPs evaluated in the present study may be used as markers in poultry breeding programs to aid in improving growth and meat quality traits. © FUNPEC-RP.

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We evaluated the effect of adding by-products from the processing of oil seeds in the diet of lambs on the carcass and meat traits. Twenty-four non-castrated weaned male Santa Inês lambs with approximately 70 days of age and initial average weight of 19.11 ± 2.12 kg were distributed into a completely randomized design. Treatments consisted of diets containing by-products with 70% of concentrate and 30% of tifton hay (Cynodon spp.) and were termed SM: control with soybean meal; SC: formulated with soybean cake; SUC: formulated with sunflower cake and PC: formulated with peanut cake. Diets had no effects on the carcass traits evaluated. There was no significant effect on the mean values of perirenal, omental and mesenteric fats (0.267, 0.552 and 0.470 kg, respectively) and there was no influence on the percentages of moisture, ether extract, crude protein or ash in the loin between experimental diets. Diets containing by-products from the processing of oil seeds did not change fatty acids found in lamb meat. The use of by-products from oil seeds provided similar carcass and meat traits, thus their use can be recommended as eventual protein and energy sources for feedlot lambs.

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

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pig meat quality is determined by several parameters, such as lipid content, tenderness, water-holding capacity, pH, color and flavor, that affect consumers’ acceptance and technological properties of meat. Carcass quality parameters are important for the production of fresh and dry-cure high-quality products, in particular the fat deposition and the lean cut yield. The identification of genes and markers associated with meat and carcass quality traits is of prime interest, for the possibility of improving the traits by marker-assisted selection (MAS) schemes. Therefore, the aim of this thesis was to investigate seven candidate genes for meat and carcass quality traits in pigs. In particular, we focused on genes belonging to the family of the lipid droplet coat proteins perilipins (PLIN1 and PLIN2) and to the calpain/calpastatin system (CAST, CAPN1, CAPN3, CAPNS1) and on the gene encoding for PPARg-coactivator 1A (PPARGC1A). In general, the candidate genes investigation included the protein localization, the detection of polymorphisms, the association analysis with meat and carcass traits and the analysis of the expression level, in order to assess the involvement of the gene in pork quality. Some of the analyzed genes showed effects on various pork traits that are subject to selection in genetic improvement programs, suggesting a possible involvement of the genes in controlling the traits variability. In particular, significant association results have been obtained for PLIN2, CAST and PPARGC1A genes, that are worthwhile of further validation. The obtained results contribute to a better understanding of biological mechanisms important for pig production as well as for a possible use of pig as animal model for studies regarding obesity in humans.

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A single-generation dataset consisting of 1,730 records from a selection program for high growth rate in giant freshwater prawn (GFP, Macrobrachium rosenbergii) was used to derive prediction equations for meat weight and meat yield. Models were based on body traits [body weight, total length and abdominal width (AW)] and carcass measurements (tail weight and exoskeleton-off weight). Lengths and width were adjusted for the systematic effects of selection line, male morphotypes and female reproductive status, and for the covariables of age at slaughter within sex and body weight. Body and meat weights adjusted for the same effects (except body weight) were used to calculate meat yield (expressed as percentage of tail weight/body weight and exoskeleton-off weight/body weight). The edible meat weight and yield in this GFP population ranged from 12 to 15 g and 37 to 45 %, respectively. The simple (Pearson) correlation coefficients between body traits (body weight, total length and AW) and meat weight were moderate to very high and positive (0.75–0.94), but the correlations between body traits and meat yield were negative (−0.47 to −0.74). There were strong linear positive relationships between measurements of body traits and meat weight, whereas relationships of body traits with meat yield were moderate and negative. Step-wise multiple regression analysis showed that the best model to predict meat weight included all body traits, with a coefficient of determination (R 2) of 0.99 and a correlation between observed and predicted values of meat weight of 0.99. The corresponding figures for meat yield were 0.91 and 0.95, respectively. Body weight or length was the best predictor of meat weight, explaining 91–94 % of observed variance when it was fitted alone in the model. By contrast, tail width explained a lower proportion (69–82 %) of total variance in the single trait models. It is concluded that in practical breeding programs, improvement of meat weight can be easily made through indirect selection for body trait combinations. The improvement of meat yield, albeit being more difficult, is possible by genetic means, with 91 % of the variation in the trait explained by the body and carcass traits examined in this study.

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A restricted maximum likelihood analysis applied to an animal model showed no significant differences (P > 0.05) in pH value of the longissimus dorsi measured at 24 h post-mortem (pH24) between high and low lines of Large White pigs selected over 4 years for post-weaning growth rate on restricted feeding. Genetic and phenotypic correlations between pH24 and production and carcass traits were estimated using all performance testing records combined with the pH24 measurements (5.05-7.02) on slaughtered animals. The estimate of heritability for pH24 was moderate (0.29 ± 0.18). Genetic correlations between pH24 and production or carcass composition traits, except for ultrasonic backfat (UBF), were not significantly different from zero. UBF had a moderate, positive genetic correlation with pH24 (0.24 ± 0.33). These estimates of genetic correlations affirmed that selection for increased growth rate on restricted feeding is likely to result in limited changes in pH24 and pork quality since the selection does not put a high emphasis on reduced fatness.