Abstract:At present, body condition score for dairy cows mainly adopts manual methods, but the reliability of the scoring results is poor due to manual subjectivity, and the assessment process is time-consuming and laborious, which relies heavily on the experience of experts. The development of body condition score for dairy cows has mainly gone through manual scoring stage, traditional machine learning stage and deep learning stage, the latter two can be subdivided into 2D field and 3D field research. Body condition score method for dairy cows based on machine learning mainly suffers from the problem of relying on manual markers and simply improving the method of dimensionality reduction and feature extraction, which can only be improved in specific situations, with limited improvement in results. With the rise of deep learning, researchers have begun to explore methods that do not require manually labeled features. The use of deep learning and 3D technology has further improved the accuracy of automatic body condition scoring, but in actual production, to meet the nutritional management needs of cows at different growth stages, the difference between the body condition score and the ideal score should always be maintained within ±0.25, and the accuracy of existing automatic scoring systems still has a certain gap with the ideal standard of actual farm management. The current research hotspots and theories of body condition score methods were summarized for dairy cows using computer vision by analyzing the literature and potential research directions were proposed. With the development of artificial intelligence, a large number of deep learning algorithms emerged that can be used for target detection and classification. These methods were also applicable to target detection and classification in the field of animal husbandry. In fact, artificial intelligence and deep learning techniques were increasingly being used in the livestock sector as well. Deep learning methods were needed for dairy cattle condition scoring, and as the development of agricultural information technology became more mature, research on automated body condition score methods for dairy cows based on deep learning would also become more advanced.
