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Novel multiple object tracking method for yellow feather broilers in a flat breeding chamber based on improved YOLOv3 and deep SORT

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International Journal of Agricultural and Biological Engineering 2023年第5期16卷 44-55页

作者： Xiuguo Zou Zhengling Yin Yuhua Li Fei Gong Yungang Bai Zhonghao Zhao Wentian Zhang Yan Qian Maohua Xiao College of Artificial Intelligence Nanjing Agricultural UniversityNanjing 210095China College of Engineering Nanjing Agricultural UniversityNanjing 210095China Faculty of Engineering and Information Technology University of Technology SydneySydneyNSW 2007Australia

Aiming at the difficulties of the health status recognition of yellow feather broilers in large-scale broiler farms and the low recognition rate of current models,a novel method based on machine vision to achieve precise tracking of multiple broilers was proposed in this ***’behavior in the breeding environment can be tracked to analyze their behaviors and health status *** improved YOLOv3(You Only Look Once v3)algorithm was used as the detector of the Deep SORT(Simple Online and Realtime Tracking)algorithm to realize the multiple object tracking of yellow feather broilers in the flat breeding chamber,which replaced the backbone of YOLOv3 with MobileNetV2 to improve the inference speed of the detection *** DRSN(Deep Residual Shrinkage Network)was integrated with MobileNetV2 to enhance the feature extraction capability of the ***,in view of the slight change in the individual size of the yellow feather broiler,the feature fusion network was also redesigned by combining it with the attention mechanism to enable the adaptive learning of the objects’multi-scale *** with traditional YOLOv3,improved YOLOv3 achieves 93.2%mAP(mean Average Precision)and 29 fps(frames per second),representing high-precision real-time detection ***,while the MOTA(Multiple Object Tracking Accuracy)increases from 51%to 54%,the IDSW(Identity Switch)decreases by 62.2%compared with traditional YOLOv3-based objective *** proposed algorithm can provide a technical reference for analyzing the behavioral perception and health status of broilers in the flat breeding environment.

关键词： yellow feather broiler flat breeding chamber multiple object tracking improved YOLOv3 Deep SORT

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Effects of Small Peptide Chelated Copper,Iron,Manganese and Zinc on Growth Performance,Chicken Quality and Antioxidant Capacity of yellow feather broilers

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Animal Husbandry and Feed Science 2020年第5期12卷 7-12页

作者： He Yuanqing Li Yuanfeng Li Min Xiong Zhaolong Wang Yachao He Jian College of Life Science and Engineering Southwest University of Science and TechnologyMianyang 621000China Feng Guangde Laboratory of Sichuan Tie Qi Li Shi Group Mianyang 621000China

[Objective]The paper was to study effects of small peptide chelated trace elements(copper,iron,zinc and manganese)on growth performance,chicken quality and antioxidant capacity of rapid yellow feather broilers.[Method]Three hundred one-day-old yellow feather broilers with similar body weight were selected and randomly divided into three treatments:inorganic trace element group(basal diet+inorganic trace elements),organic trace element group(basal diet+small peptide chelated trace elements)and compound group(basal diet+50%inorganic trace elements+50%small peptide chelated trace elements).There were 10 replicates per treatment and 10 chickens per *** trial lasted for 63 d.[Result]①Compared to inorganic trace element group,average daily gain(ADG)of yellow feather broilers in organic trace element group was significantly increased over the whole period(P0.05).③There was no significant difference in breast muscle pH,chicken color,drip loss,and shear force among the three groups(P>0.05),but cooking loss of chicken breast in inorganic trace element group was 27.46%and 22.53%higher than those in organic trace element group and compound group,respectively(Pbroilers,improves quality of chicken breast,and enhances antioxidant capacity.

关键词： yellow feather broiler Small peptide chelated trace elements Slaughter performance Chicken quality Antioxidant capacity

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