Body condition has always been an important indicator reflecting the health status of livestock, and new automated and contactless methods for assessing it have also been continuously proposed. In recent years, with the continuous expansion of research on quantitative analysis of three-dimensional shapes in the field of agriculture, amount of studies has shown that quantitative analysis of shapes can promote the development of smart agriculture. This article proposed a method for quantitatively analyzing the local three-dimensional shape of livestock to evaluate their body conditions. This is a universal method that can be applied to various species. It uses the method of point-to-point correspondence in the three-dimensional shape to finely calculate the difference between shapes, and then maps the difference value to the range of the body condition score. The article analyzed the shape of 198 dairy cows, 100 beef cattle, and 201 pigs using body condition scores as test parameters. The accuracy of body condition evaluation within the range of error of 0.5 for dairy cows, 1 for beef cattle, and 0.5 for pigs are 100%, 87.61%, and 92.09%, respectively. Compared to previous methods for assessing body condition, the method proposed in this paper is more accurate and versatile. The dataset used in this study, along with the code implementation have been made publicly available in https://gitee.com/kznd/lshape-analyser/tree/master/MATLAB.
Automatic method for quantitatively analyzing the body condition of livestock from 3D shape
Pezzuolo A.;
2023
Abstract
Body condition has always been an important indicator reflecting the health status of livestock, and new automated and contactless methods for assessing it have also been continuously proposed. In recent years, with the continuous expansion of research on quantitative analysis of three-dimensional shapes in the field of agriculture, amount of studies has shown that quantitative analysis of shapes can promote the development of smart agriculture. This article proposed a method for quantitatively analyzing the local three-dimensional shape of livestock to evaluate their body conditions. This is a universal method that can be applied to various species. It uses the method of point-to-point correspondence in the three-dimensional shape to finely calculate the difference between shapes, and then maps the difference value to the range of the body condition score. The article analyzed the shape of 198 dairy cows, 100 beef cattle, and 201 pigs using body condition scores as test parameters. The accuracy of body condition evaluation within the range of error of 0.5 for dairy cows, 1 for beef cattle, and 0.5 for pigs are 100%, 87.61%, and 92.09%, respectively. Compared to previous methods for assessing body condition, the method proposed in this paper is more accurate and versatile. The dataset used in this study, along with the code implementation have been made publicly available in https://gitee.com/kznd/lshape-analyser/tree/master/MATLAB.
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