The study focused on the significance of facial expressions in pigs as a mode of communication for assessing their emotions, physical status, and intentions. To address the challenges of recognizing facial expressions due to the simple facial muscle group structure of pigs, a novel pig facial expression recognition model called CReToNeXt-YOLOv5 was proposed. Several improvements were made to enhance the accuracy and detection ability of the model. Firstly, the CIOU loss function was replaced with the EIOU loss function to optimize the training model and achieve more accurate regression. This change improved the overall performance of the model. Secondly, the model was equipped with the Coordinate Attention mechanism, which improved its sensitivity to expression features, making it more effective in recognizing facial expressions. Lastly, the CReToNeXt module was integrated into the model to enhance its detection capability for subtle expressions. The results demonstrated the effectiveness of the CReToNeXt-YOLOv5 model. It achieved a mean average an mAP of 89.4%, showing a significant improvement of 6.7% compared to the original YOLOv5 model. Overall, the experimental results confirmed the effectiveness of the optimized YOLOv5 model, CReToNeXt-YOLOv5, in accurately recognizing facial expressions in pigs.
Water scarcity is a significant global problem. Considerable water resources are consumed in the production of livestock and poultry products, thus posing a huge challenge to global freshwater resources. Sheep meat has the second highest water footprint among livestock meat products. Furthermore, as the demand for sheep meat increases on a year by year basis, water consumption continues to rise as a result. In order to make better informed decisions around water management, it is necessary to estimate the water footprint of animal husbandry. This study offers a comprehensive overview of the water footprint of sheep in Northern China. It analyzes the water footprint of feed production and virtual water using CROPWAT, based on the water footprint of sheep and goats in Shanxi under different production systems and feed components. The water footprint was calculated to be 6.03 m3/kg for sheep and 5.05 m3/kg for goats, respectively. Therefore, the water footprint of three farming modes, including grazing mixed and industrial in the Shanxi region was slightly higher than what other experts have evaluated for China. These data provide crucial information that can help reduce water resource consumption in animal husbandry and contribute to the development of sustainable strategies.
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