Avaliação da composição química e física dos cortes da costela para estimar a composição química corporal de novilhos nelore

The objective of this study was to establish equations to estimate the empty body chemical composition of Nellore steers using the following indirect techniques: 1) physical composition of the 9-10-11(th) rib cut;) physical composition of the 10(th) rib cut; and 3) chemical composition of the 10(th) rib cut. Thirty-one Nellore steers with weights ranging from 245 to 489 kg and ages from 20 to 29.7 months at slaughter were utilized. The empty body chemical composition was established through samples collected after grinding all animal tissues. The equations using the percentage of dissectable fat in the 9-10-11(th) rib cut shored a high precision for estimating the percentage of water (r(2) = 0.91; Syx = 1.168) and ether extract (r(2) = 0.94; Syx = 1.298) of the empty body; the same was observed when the percentage of dissectable fat in the 10(th) rib cut was used (r(2) = 0.82 and 0.85; Syx = 1.658 and 1.942, respectively, for water and ether extract). The equations using the percentage of ether extract in the 10(th) rib cut showed a high precision for estimating the percentage of water (r(2) = 0.89; Syx = 1.311) and the ether extract (r(2) = 0.89; Syx = 1.730) of the empty body, but there was no advantage over the physical composition of the 9-10-11(th) and 10(th) rib cut. Multiple regressions using carcass weight and the percentage of bones and kilograms of lean, fat, and bones dissectable in the 10(th) rib cut improved the coefficients of determination for water and ether extract to 0.87 and 0.91. The equations to estimate the percentages of protein and ach showed a low precision, indicating that those techniques are not recommended to estimate these components in the empty body of Nellore steers.

Mapping QTLs on chicken chromosome 1 for performance and carcass traits in a broiler x layer cross

With the objective of mapping quantitative trait loci (QTLs) for performance and carcass traits, an F-2 chicken population was developed by crossing broiler and layer lines. A total of 2063 F-2 chicks in 21 full-sib families were reared as broilers and slaughtered at 42 days of age. Seventeen performance and carcass traits were measured. Parental (F-0) and F-1 individuals were genotyped with 80 microsatellites from chicken chromosome 1 to select informative markers. Thirty-three informative markers were used for selective genotyping of F-2 individuals with extreme phenotypes for body weight at 42 days of age (BW42). Based on the regions identified by selective genotyping, seven full-sib families (649 F-2 chicks) were genotyped with 26 markers. Quantitative trait loci affecting body weight, feed intake, carcass weight, drums and thighs weight and abdominal fat weight were mapped to regions already identified in other populations. Quantitative trait loci for weights of gizzard, liver, lungs, heart and feet, as well as length of intestine, not previously described in the literature were mapped on chromosome 1. This F-2 population can be used to identify novel QTLs and constitutes a new resource for studies of genes related to growth and carcass traits in poultry.

Correlations among carcass traits taken by ultrasound and after slaughter in Mediterranean (Bubalus bubalis) young bulls

The objective of this work was to estimate the correlations among measurements taken in vivo with ultrasound equipment with some carcass traits measured after slaughter. Twenty eight Mediterranean bulls, with average shrunk body weight of 330 kg and 14 months of age, were fed by 120 days with high concentrate diets. The shrunk body weight, the ribeye area (REAU), the back fat thickness (FTU) over the Longissimus dorsi muscle between 12(a) and 13(a) ribs and rump fat (EGP8U), were measured at 28 days intervals. Real-time ultrasound equipment Piemedical Scanner 200 VET, with 18 cm linear array transducer was utilized. After the slaughter, the hot carcass weight (PCQ) and the kidney, pelvic and inguinal fat (GRPI) were weighted and the dressing percentage (DP) calculated. After 24 hours of cooling the ribeye area (REAC), backfat thickness (FTC) and rump fat (EGP8C) were measured. Both the REAC, FTC and EGP8C were underestimated by ultrasound measurements. The Pearson correlation coefficients for ribeye area, backfat thickness and rump fat measured in the carcass and with ultrasound, were 0.96, 0.99 and 0.91, respectively. The coefficient between DP and REAU was 0.47; 0.45 between DP and REAC, 0.56 between DP and FTU and 0.58 between DP and FTC. DP presented a 0.59 correlation coefficient with EGP8U. The Spearman correlation was estimated between REAU and REAC, FTU and FTC, EGP8U and EGP8C, and the values were 0.96, 0.99 and 0.91,respectively. The ultrasound measures could be used to estimate carcass traits in buffaloes with good accuracy.

Breeding of the Scuttle Fly Megaselia scalaris in a fish Carcass and Implications for the use in Forensic Entomology (Diptera: Phoridae).

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

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.