Assessing the composition of the soft tissue in lamb carcasses with bioimpedance and accessory measures

Prediction of carcass composition and meat and fat quality using sensing technologies: A review

Consumer demand for high-quality healthy food is increasing,  thus meat processors require the means toassess these rapidly, accurately, and inexpensively. Traditional methods forquality assessments are time-consuming, expensive, invasive, and have potentialto negatively impact the environment. Consequently, emphasis has been put onfinding non-destructive, fast, and accurate technologies for productcomposition and quality evaluation. Research in this area is advancing rapidlythrough recent developments in the areas of portability, accuracy, and machinelearning. The present review, therefore, critically evaluates and summarizes developmentsof popular non-invasive technologies (i.e., from imaging to spectroscopicsensing technologies) for estimating beef, pork, and lamb composition andquality, which will hopefully assist in the implementation of thesetechnologies for rapid evaluation/real-timegrading of livestock products in the nearfuture.

Using segmental bioimpedance analysis to estimate soft tissue and chemical composition of retail cuts and carcasses of lambs

This study evaluated the potential of segmental bioimpedance analysis (SBIA) to estimate the composition of retail cuts and their predictability to infer on the carcass composition in lambs. Leg, rib, shoulder, neck, and loin from thirty-one lamb carcasses were evaluated. A single-frequency bioelectrical impedance analyzer at 50 kHz was used to perform measurements. The models for estimating soft tissue showed the highest accuracy in the retail cuts. Lean and fat weight of the lamb cuts or of the carcasses were predicted with R² of calibration ranging from 86.6 to 99.1% and from 67.5 to 95.4%, respectively. Segmental bioimpedance analysis is an accurate technology to assess physical and chemical components in retail cuts of lamb. Despite that, shoulder was the most representative cut; all cuts evaluated through SBIA were valuable to estimate the components of the edible portion of lamb carcasses.

Predicting the chemical composition of the body and the carcass of hair sheep using body parts and carcass measurements

Determination of the chemical composition in the body and carcass of ruminants is important for both nutritional requirement studies and the meat industry. This study aimed to develop equations to predict the body and carcass chemical composition of hair sheep using the chemical composition of body parts, carcass measurements and shrunk BW as predictors. A database containing 107 individual records for castrated male hair sheep ranging from 24 to 43 kg BW was gathered from two body composition studies. The empty body, carcass and body parts were analyzed for water, ash, fat and protein contents (%). The body parts used to estimate body and carcass composition were fore leg, hind leg and 9-11th rib section. The carcass measurements used were leg length, thoracic circumference, hind circumference, hind width, thoracic width, thoracic depth and chest width. Each model performance was evaluated using a leave-one-out cross-validation. Multiple regression analysis considering the study as a random effect revealed that body parts in association with carcass measurements were significant for predicting the chemical composition in the body of castrate male sheep. However, the use of the chemical composition of hind leg produced the best models for predicting the ash and fat contents in the empty body, whereas the water and protein contents in the empty body were better predicted when using the chemical compositions of 9-11th rib section and fore leg, respectively. Multiple regression analysis also revealed that most body parts were suitable for predicting the carcass composition, except for 9-11th rib section whose chemical composition did not produce significant prediction equations for ash and protein carcass contents. The use of the chemical composition of hind leg in association with carcass measurements produced the best models for predicting the water and fat contents in the carcass, while the ash and protein contents in the carcass were better predicted when using the chemical composition of fore leg. In conclusion, precision, accuracy and goodness-of-fit of the equations drove the selection of the chemical composition of hind leg and carcass measurements in a multivariate approach, as the most suitable predictors of the chemical composition of the body and carcass of hair sheep. However, the chemical composition of fore leg may be used as well. The developed equations could improve the accuracy of the empty body and carcass composition estimations in sheep, optimizing the estimation of nutrient requirements, as well as the carcass quality evaluation for this species.

Utilization of Bioelectrical Impedance to Predict Intramuscular Fat and Physicochemical Traits of the Beef Longissimus Thoracis et Lumborum Muscle

The bioelectrical impedance analysis (BIA) is a non-destructive technique that has been successfully used to assess the body and carcass composition of farm species. This study aimed to predict intramuscular fat (IMF) and physicochemical traits in the longissimus thoracis et lumborum muscle (LM) of beef, using BIA. These traits were evaluated in LM samples of 52 crossbred heifer carcasses. The BIA was performed in LM, using a 50 Hz frequency high precision impedance converter system. A correlation analysis of the studied variables was performed. Then a stepwise with a k-folds cross validation procedure was used to modelling the prediction of IMF and physicochemical traits from BIA parameters (24.5% ≤ CV ≤ 47.3%). Wide variation was found for IMF and BIA parameters. In general, correlations of BIA parameters with IMF and physicochemical traits were moderate to high and were similar for all BIA parameters (−0.50 ≤ r ≤ 0.50 only for total pigments, a* and pH48). It was possible to predict IMF and physicochemical traits from BIA. The best fit explained 79.3% of the variation in IMF, while for physicochemical traits the best fits were for sarcomere length and shear force (64.4% and 60.5%, respectively). The results confirmed the potential of BIA for objective measurement of meat quality.