Replacing soybean meal with fermented feed led to a decrease in the abnormal egg rate during the late laying period of Hy-Line Gray laying hens as well as enhancing eggshell strength and thickness. Moreover, this replacement strategy reduced breast muscle drip loss, increased pH levels, and improved meat color. Moreover, it lowered fat and cholesterol content in muscle and facilitated amino acid deposition. Notably, replacing 10 % of soybean meal with fermented feed for 8 weeks demonstrated promising outcomes.

This study was conducted to identify key welfare risks using the AWIN (Animal Welfare Indicators) protocol for extensively managed sheep farms. Each farm was visited once. A total of 702 sheep were individually assessed on the farms as part of the second-level welfare criteria. The main animal welfare risks identified were housing facilities, the provision of adequate and balanced diets to the animals, and the implementation of appropriate animal health plans in accordance with the breed requirements.

The study utilises artificial intelligence to improve buffalo recognition in livestock management. It employs facial images of 11 buffaloes to develop a dataset and utilises four CNN (convolutional neural network) algorithms to identify buffaloes based on muzzle patterns. Results indicate successful performance, with SqueezeNet achieving the highest accuracy of 99.88 %, along with high precision, recall, and F1 score.

Using 900 Hubbard broilers, results showed that enzyme treatment and fermentation improved weight gain and FCRs (feed conversion ratios). Fermentation at 6 % and 12 % was optimal, while 18 % had negative effects. Carcass traits, nutrient digestibility, and bone strength improved, with reduced triglycerides in fermented groups, enhancing broiler productivity.