Evaluator effect on the ultrasound measurement of subcutaneous fat deposition and loin eye area from weaning to slaughter lambs

Non-invasive methods to quantify the carcass parameters of sheep: Interaction between thermal environment and residual feed intake

The thermal environment is important in unit production because the perception of thermal stress can reduce fertility, and productive performance, therefore its management is necessary. The use of non-invasive methods, such as infrared thermography and real-time ultrasonography, are widely used to evaluate indicators in animal production, without the need to slaughter the animals. Thus, we aimed to assess the effect of the thermal environment on the physiological parameters and carcass characteristics of Dorper sheep with positive and negative residual feed intake (RFI) using infrared thermography and real-time ultrasonography techniques. Twenty uncastrated male Dorper sheep (17.8 ± 2.4 kg) were confined for 40 days for RFI classification. Sheep were separated into positive RFI (n = 10) and negative RFI (n = 10). The experimental design was in randomized blocks, in a 2 × 2 factorial arrangement, with 2 thermal environments (full sun or shade) and two feed efficiency groups (positive RFI or negative RFI), with 5 replications. The sheep remained in confinement for 60 days. The animals were slaughtered at the end of the experiment and the carcasses dissected for tissue separation. Rectal temperature (RT) and respiratory rate (RR) were measured at two times (14:00 h and 18:00 h) for periods of 5 days. The RR was determined by indirect auscultation of heart sounds at the level of the laryngotracheal region. The RT was measured introduced a digital clinical thermometer into the animal's rectum. Surface temperature (ST) was obtained using a thermographic infrared camera, collecting the temperatures of the eyeball and skin surface in the regions of the head, ribs, rump, flank and shin. Sheep confined in full sun showed higher RR (P = 0.0001), ST ribs (P = 0.0020), ST rumb (P = 0.0055), ST flank (P = 0.0001) and heat tolerance coefficient (HTC) (P = 0.0010). For sheep confined in full sun, a strong correlation was observed between the RR and the mean ST (MST; r = 0.6826; P = 0.0236) and between the final loin eye area (LEAf) with the real LEA (LEAr) (r = 0.9263; P = 0.0001) and slaughter body weight (SBW) (r = 0.7532; P = 0.0325). For negative RFI sheep, a positive correlation was observed between the RR and the ST rump (r = 0.7343; P = 0.0025) and ST ribs (r = 0.6560; P = 0.0178) and the MST (r = 0.7435; P = 0.0001), between the MST and the LEAr (r = 0.6837; P = 0.0025) and the final LEA (r = 0.6771; P = 0.0144), and between the final LEA and LEAr (r = 0.9942; P = 0.0001), BW (r = 0.8415; P = 0.0277) and MST (r = 0.6771; P = 0.0045). Positive RFI sheep confined to shade showed a high correlation between final LEA and LEAr (r = 0.9372; P = 0.0001). The use of shading in confined Dorper sheep, regardless of the RFI classification, reduces the effects of heat stress on physiological parameters.

Modelling and predicting fat deposition rates in various South African sheep crosses using ultrasound technology

Producers require an accurate predictive tool that can determine the optimal point of slaughter based on fat depth. The modelling of fat deposition with a simple mathematical model could supply in this need. Dohne Merino and Merino ewes were crossed with Dorper, Dormer and Ile de France rams or rams of their own breeds to create two purebred (Dohne Merino and Merino) and six crossbred groups (Dohne x Dorper, Dohne x Dormer, Dohne x Ile de France, Merino x Dorper, Merino x Dormer and Merino x Ile de France) of offspring. Fat deposition of four lambs of each sex per genotypic group was monitored from 80 to 360 days using ultrasound, and the data subsequently fitted to various equations and evaluated for goodness of fit. A linear fitting of fat depth to age (R2 > 0.77) and live weight (R2 > 0.56) were deemed to provide the best fit. The slope parameters of the equations indicated that ewes deposited fat faster than rams and that Dorper crosses had the highest fat deposition rate. An attempt was also made to model loin muscle growth, but the model fit was judged to be unsatisfactory. The predictive models developed here are deemed suitable for inclusion in feedlot management systems to aid in the production of optimally classified lamb carcasses.

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.