Assessment of lamb carcass composition from live animal measurement of bioelectrical impedance or ultrasonic tissue depths

Estimation of in vivo body composition of Iberian pigs using bioelectric impedance and ultrasonography techniques

Iberian pigs are renowned for their high-quality products and distinctive characteristics, including high fat accumulation, low protein deposition rate, and a long productive cycle. The study aimed to assess in vivo body composition of purebred Iberian pigs using bioimpedance analysis (BIA) and ultrasonography. Accurate estimation of body composition in live animals is crucial for adopting decisions at the farm level. The experiment involved three groups of pure male Iberian pigs differing in body weight (BW; 60, 80 and 100 kg) with the same nutritional management. Body measurements, BIA and back fat and loin thickness (measured by ultrasonography) were obtained before slaughter. After slaughter pig carcasses were chemically analysed. A strong correlation between BIA measurements, specifically resistance (Rs) values, and body chemical parameters (total protein, lipids, ash, and water contents; p < 0.001 for all) was found. Reactance values (Xc), however, did not exhibit significant correlations. Regression analyses were conducted to predict carcass composition based on BIA measurements, BW, ultrasonography and linear corporal measurements. The prediction models achieved high R2 values for lipids, protein, total ash, water, and lean tissue (0.957, 0.968, 0.936, 0.961 and 0.976, respectively, p < 0.001 for all), indicating strong predictive power. These findings demonstrate the potential of non-invasive techniques such as BIA for estimating body chemical composition and quality of pig carcasses. However, it is important to acknowledge that the prediction models developed may not be applicable to other pig populations, as they were based on a specific sample of pigs.

Investigation of Body Development in Growing Holstein Heifers With Special Emphasis on Body Fat Development Using Bioelectrical Impedance Analysis

This study analyzed skeletal development, body condition, and total body fat development of growing heifers. A total of 144 female primiparous Holstein cattle from four commercial dairy farms with different degrees of stillbirth rates were examined during the rearing period. This included measurements in body condition, fat tissue, metabolic, and endocrine factors. Pelvic measurements and the sacrum height were analyzed to assess skeletal development. The body condition was classified via body condition scoring, bioelectrical impedance analysis (BIA), back fat thickness measurements, and the body mass. For the first time, BIA was used as an appropriate method to evaluate the fat tissue content of cattle throughout the rearing period. This analysis technique can be performed on heifers aged 8–15 months. Throughout that period, the fat content decreased while the skeletal development increased. In addition, high free fatty acid concentrations in serum of the animals with high frame development were found, supporting our hypothesis that stored energy of body fat deposits is used for skeletal growth. Furthermore, we were able to demonstrate complex endocrine relationships between fat metabolism and skeletal growth by using specific markers, such as leptin, insulin growth factor-1 (IGF-1), and estradiol (E2). Food analysis showed high crude protein (CP) levels in the total mixed ration above recommendation for daily protein intake of all farms. However, there was a positive correlation between CP and the body frame measurements in our study. In summary, we established a novel regression formula for BIA analysis (“BIA-Heine”) in heifers to evaluate the body composition throughout different ages and physiological stages in the development of heifers. This special formula allows the evaluation of fat tissue without a whole-body analysis and therefore provides an innovative technique for animal welfare support.

Non-Thermal Methods for Ensuring the Microbiological Quality and Safety of Seafood

A literature search and systematic review were conducted to present and discuss the most recent research studies for the past twenty years on the application of non-thermal methods for ensuring the microbiological safety and quality of fish and seafood. This review presents the principles and reveals the potential benefits of high hydrostatic pressure processing (HHP), ultrasounds (US), non-thermal atmospheric plasma (NTAP), pulsed electric fields (PEF), and electrolyzed water (EW) as alternative methods to conventional heat treatments. Some of these methods have already been adopted by the seafood industry, while others show promising results in inactivating microbial contaminants or spoilage bacteria from solid or liquid seafood products without affecting the biochemical or sensory quality. The main applications and mechanisms of action for each emerging technology are being discussed. Each of these technologies has a specific mode of microbial inactivation and a specific range of use. Thus, their knowledge is important to design a practical application plan focusing on producing safer, qualitative seafood products with added value following today’s consumers’ needs.

The prediction of ham composition by bioelectrical impedance analysis

The objective of this preliminary experiment was to study whether bioelectrical impedance analysis (BIA) can accurately predict the components of fresh pig hams. The trimmed right hams from 20 Iberian barrows were used. Six measures of resistance and reactance were taken by a bioelectrical impedance analyser. Simple and multiple regression equations were calculated for estimating bone, lean, intermuscular fat (IF), subcutaneous fat (SF), total fat (TF) and skin weights and percentages with respect to ham weight (HW). The HW accounted for 22% (P < 0.05) and 35% (P < 0.01) in the variations in lean and skin percentages, respectively. The ham compactness index (HCI), calculated as HW (in g)/(ham length, in cm)2, accounted for 20% (P < 0.05) and 38% (P < 0.01) in the variations in SF and TF percentages, respectively. The HW and BIA variables accounted for 60% (P < 0.001) of the variation in skin percentage; the HCI and BIA measures accounted for 79% (P < 0.0001), 66% (P < 0.001) and 78% (P < 0.0001) of the variation in lean, IF and SF percentages; and BIA variables accounted for 72% (P < 0.0001) of the variation in bone percentage. To determine the accuracy of the calculated regression equations, five additional trimmed fresh hams from Iberian barrows were used. Actual and predicted values were compared. The HW accurately predicted lean weight and skin percentage in linear regression equations, and HCI adequately predicted SF and TF weights in simple linear regression equations, and also SF percentage in inverse function. The additional inclusion of HW, HCI or BIA variables in the regression models did not improve the accuracy of the equations. It is concluded that BIA might be applied to predict the components of fresh hams but more studies are needed to determine whether levels of accuracy and precision are sufficient for this method to be used in practice.

Prediction of lamb carcass composition by impedance spectroscopy

The objective of this study was to compare impedance spectroscopy with resistance measurements at a single frequency (50 kHz) for the prediction of lamb carcass composition. The impedance spectrum is usually recorded by measuring the complex impedance at various frequencies (frequency domain); however, in this study, we also applied the faster and simpler measurement in the time domain (application of a current step and measurement of the voltage response). The study was carried out on 24 male, German Black-headed Mutton lambs with an average BW of 45 kg. Frequency- and time domain-based impedance measurements were collected at 20 min and 24 h postmortem with different electrode placements. Real and imaginary parts at various frequencies were calculated from the locus diagram. Left sides were dissected into lean, fat, and bone, and right sides were ground to determine actual carcass composition. Crude fat, crude protein, and moisture were chemically analyzed on ground samples. Frequency- and time domain-based measurements did not provide the same absolute impedance values; however, the high correlations (P < 0.001) between these methods for the "real parts" showed that they ranked individuals in the same order. Most of the time domain data correlated higher to carcass composition than did the frequency domain data. The real parts of impedance showed correlations between -0.37 (P > 0.05) and -0.74 (P < 0.001) to water, crude fat, lean, and fatty tissue, whereas the relations to CP were much lower (from 0.00 to -0.47, P < 0.05). Electrode placements at different locations did not substantially improve the correlations with carcass composition. The "imaginary parts" of impedance were not suitable for the prediction of carcass composition. The highest accuracy (R2 = 0.66) was reached for the estimation of crude fat percentage by a regression equation with the time domain-based impedance measured at 24 h postmortem. Furthermore, there was not a clear superiority of measurements in a wide frequency range over a single frequency measurement at 50 kHz for the prediction of carcass composition. Even though we calculated the impedance at 50 kHz based on the locus diagram, which allowed for a high precision for predicting this impedance trait, single-frequency impedance devices typically used in practice cannot record the locus diagram and, therefore, exhibit a greater amount of uncertainty.

An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage

An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective means for pricing carcasses in a value-based marketing system.