Shalaldeh, A.; Page, S.; Anthony, P.; Charters, S.; Safa, M.; Logan, C. Body Composition Estimation in Breeding Ewes Using Live Weight and Body Parameters Utilizing Image Analysis. Animals2023, 13, 2391.
Shalaldeh, A.; Page, S.; Anthony, P.; Charters, S.; Safa, M.; Logan, C. Body Composition Estimation in Breeding Ewes Using Live Weight and Body Parameters Utilizing Image Analysis. Animals 2023, 13, 2391.
Shalaldeh, A.; Page, S.; Anthony, P.; Charters, S.; Safa, M.; Logan, C. Body Composition Estimation in Breeding Ewes Using Live Weight and Body Parameters Utilizing Image Analysis. Animals2023, 13, 2391.
Shalaldeh, A.; Page, S.; Anthony, P.; Charters, S.; Safa, M.; Logan, C. Body Composition Estimation in Breeding Ewes Using Live Weight and Body Parameters Utilizing Image Analysis. Animals 2023, 13, 2391.
Abstract
Farmers are continually looking for new reliable, objective and non-invasive methods for evaluation of ewe condition. Live weight (LW) and body condition score (BCS) are used by farmers as a basis to determine the condition of the animal. Body composition is an important aspect of monitoring animal condition. The body composition is the amount of fat, lean and bone; knowing the amount of each is important because the information can be used for better strategic management interventions.
Experiments were conducted to establish the relationship between body composition and body parameters, at key life’s stages (weaning and pre-mating), using measurements automatically determined by an image processing ap-plication at Lincoln University sheep farm for 88 Coopworth ewes. Computerized Tomography technology was used to develop relationship with body parameters and a subset was used to validate the predicted model.
Multivariate linear regression (MLR), artificial neural network (ANNs) and regression tree (RT) statistical analysis methods were evaluated to determine their efficacy to predict body fat, lean and bone.
The results showed a correlation between fat, lean and bone determined by CT and the fat, lean, bone weight estimated by live weight and body parameters calculated using the image processing application with R2 values of 0.90 for fat, 0.72 for lean and 0.50 for bone using ANNs statistical model. From these results, farmers can utilize accurate measures of fat which will enhance nutritional and management practices.
Keywords
body composition; body condition score; body parameters; fat; live weight; ewes condition; im-age analysis
Subject
Biology and Life Sciences, Animal Science, Veterinary Science and Zoology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
