Prediction of carcass traits in fattening Chios and Serres lambs using real-time ultrasonography and live body weight measurements pre-slaughter

The objective of this study was to assess the capability of predicting carcass traits and meat cuts weights, in fattening lambs of indigenous Greek dairy sheep breeds, using ultrasound measurements and live body weight measurements pre-slaughter. A total of 187 lambs of Chios and Serres breeds were involved in the study. Body condition score, live body weight (LBW), and ultrasound measurements of Longissimus lumborum muscle depth (LMD) and subcutaneous fat thickness (SFT) at the lumbar region were recorded pre-slaughter. After slaughter, the carcasses were classified using five-degree grading systems for muscle development and fat deposition, while hot (HCW) and cold carcass (CCW) and meat cuts weights were measured. The statistical analyses included descriptive statistics and linear regression models to estimate the fixed effects of sex and the covariances of LBW, BCS, and ultrasound measurements on the studied traits. High R2 values (0.60 ≤ R2 ≤ 0.92) were observed in the models predicting HCW, CCW, forequarter, leg chump on shank off, the short loin, the eye of the short loin, and foreshank weights. Among the models estimated LMD, SFT, and LBW as significant predictors, the ones predicting hot and cold carcass weights, the short loin, the eye of the short loin, and the eye of the rack weights were successfully validated. Other models including BCS, LBW, sex, and either one or none of the ultrasonography measurements as predictors were also validated and presented.

Extruded urea could replace true protein source in supplements for lambs finished in tropical pastures

ABSTRACT The aim of this study was to evaluate the effects of replacing 50% of the true protein from soybean meal with extruded urea on the performance and carcass characteristics of lambs finished on pasture. Twenty lambs with initial weight of 29.9±6.2kg and 5 months of age, distributed in two treatments in blocks at random, were kept in pastures of Urochloa spp. Supplemented with 2% of body weight (BW). The treatments consisted of supplements containing soybean meal as the only true protein source (control), or extruded urea replacing 50% of soybean meal (NPN treatment). There was no effect of treatment on total supplement intake. There were differences in average daily gain (242.1 vs. 264.6g/day), slaughter weight (41.9 vs. 45.0kg) and carcass weight (18.9 vs. 20.1kg). There was no effect of the treatment on the final body condition score, hot carcass yield, carcass length, breast depth, subcutaneous fat thickness or rib eye area. The group of animals that received extruded urea showed superior carcass finishing characteristics (99.0% vs. 66.0%), maturity (22.0% vs. 0.0%), marbling (55.0% vs. 33.0%), meat texture (44.0% vs. 33.0%) and fat (66.0% vs. 22.0%). There were no significant effects on tenderness (7.5kg/f) or flesh color (L* = 33.2; a* = 16.2; b* = 8.3). There were no significant changes in the biochemical profile of the animals' blood during the experiment for both treatments. The replacement of 50% of protein from soybean meal by the extruded urea as NPN source in the supplement for lambs finished in Urochloa spp pastures provides better animal performance and qualitative characteristics of meat, without altering quantitative carcass characteristics.

Predictability of carcass traits in live Tan sheep by real-time ultrasound technology with least-squares support vector machines

This study aimed to investigate the performance of least-squares support vector machines to predict carcass characteristics in Tan sheep using noninvasive in vivo measurements. A total of 80 six-month-old Tan sheep (37 rams and 43 ewes) were examined. Back fat thickness and eye muscle area between the 12th and 13th ribs were measured using real-time ultrasound in live Tan sheep. All carcasses were dissected to hind leg, longissimus dorsi muscle, lean meat, fat, and bone to determine carcass composition. Multiple linear regression (MLR), partial least squares regression (PLSR), and least-squares support vector machines (LSSVM) were applied to correlate the live Tan sheep characteristics with carcass composition. The results showed that the LSSVM model had a better efficacy for estimating carcass weight, longissimus dorsi muscle weight, lean meat weight, fat weight, lean meat, and fat percentage in live lambs (R = 0.94, RMSE = 0.62; R = 0.73, RMSE = 0.02; R = 0.86, RMSE = 0.47; R = 0.78, RMSE = 0.63; R = 0.73, RMSE = 0.02; R = 0.65, RMSE = 0.03, respectively). LSSVM algorithm was a potential alternative to the conventional MLR method. The results demonstrated that LSSVM model might have great potential to be applied to the evaluation of sheep with superior carcass traits by combining with real-time ultrasound technology.

Simultaneously prediction of sheep and goat carcass composition and body fat depots using in vivo ultrasound measurements and live weight

The present study established multiple linear regression models using two ultrasound in vivo measurements (at lumbar and sternal regions, with different real-time ultrasonography machines and probes) and live weight, to predict simultaneously carcass composition and body fat depots of different breeds of sheep and goat. This study is important for the small ruminant industry, considering the feasibility of using the ultrasound methodology in field conditions, as well as an online system of the carcass evaluation. The multiple linear regression models were obtained by selecting the best subset of variables between using the in vivo measurements (raw variables), their second degree and interactions, evaluated in terms of prediction performance using cross-validation "K-folds" and validated by a test group. Overall, high accuracy (adj R²) was obtained from the linear relationship between predicted and experimental values of the group test for each of the nine dependent variables, with values varying between adj R² 0.88 and 0.98.

Advances in Sheep and Goat Meat Products Research

The main goal of this chapter was to review the state of the art in the recent advances in sheep and goat meat products research. Research and innovation have been playing an important role in sheep and goat meat production and meat processing as well as food safety. Special emphasis will be placed on the imaging and spectroscopic methods for predicting body composition, carcass and meat quality. The physicochemical and sensory quality as well as food safety will be referenced to the new sheep and goat meat products. Finally, the future trends in sheep and goat meat products research will be pointed out.