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.

Evaluation of Infrared Thermography for the Detection of Footrot and White Line Disease Lesions in Dairy Sheep.

The objectives of this study were to investigate temperature distribution at the sheep hoof and evaluate the reliability and diagnostic performance of infrared thermography (IRT) for the detection of footrot and white line disease (WLD) lesions in intensively reared dairy sheep. Hoof lesions were clinically assessed, and IRT was used to measure temperature distribution on hoof superficial tissue in 600 multiparous ewes. Binary regression models were developed and validated, and receiver operating characteristic curves were estimated to assess the predictive value and diagnostic performance of IRT for the detection of hoof lesions. The most sensitive prediction model for the detection of IFR was based on the difference between ambient and hoof heel temperature (sensitivity: 83.3%, specificity: 47.8%, and threshold value: 6.5 °C), whereas the most specific prediction model was based on the difference between ambient and coronary band temperature (sensitivity: 51.9%, specificity: 79.7%, and threshold value: 11.3 °C). In the case of WLD, the diagnostic performance of IRT had limited predictive value. IRT could be a useful tool for hoof health screening in dairy sheep. However, it must be cautiously adapted in cases where environmental, operating, and operator variables are not effectively controlled.