An approach for dynamic stress-free perception of goose body mass. (May 2023) - Zhang, Yanjun; Han, Jiawen; Miao, Hong; Zhang, Shanwen; Gong, Daoqing
Abstract : Growth rate, feed conversion rate, and nutritional status have been considered as important evaluation factors in the process of goose breeding, and these factors mostly depend on timely and effective weight data. Geese are traditionally weighed using electronic platform weighers which requires workers to catch the geese frequently. This results in problems such as intensive labour, transcription errors, biosafety and stress behaviour. In this study, an approach for dynamic stress-free perception of goose weight was proposed. An array piezoresistive film pressure sensor was used to analyse the periodic geese gait characteristics and obtain piezoresistive signals. A gait recognition algorithm was proposed to obtain the stride frequency and stride length of the geese by analyzing the piezoresistive signal variation law of the film pressure sensor. The goose weight perception model was developed to transform the gait characteristics and piezoresistive signals into geese body mass information. The maximum value of average error rate was 7.0%, and the minimum value of average error rate was 5.1%. The experimental results validated the accuracy of the proposed approach. Highlights: A new approach for dynamic stress-free perception of goose body mass. An array piezoresistive film sensor used for analyzing geese gait characteristics. A symmetrical gait period segmentation method. A gait recognition algorithm was proposed for obtaining the gait characteristics of breeding geese. A kinematics analysis algorithm was proposed for calculating body mass of breeding geese.