Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System
Gait scoring is a useful measure for evaluating broiler production efficiency, welfare status, bone quality, and physiology. The research objective was to track and characterize spatiotemporal and three-dimensional locomotive behaviors of individual broilers with known gait scores by jointly using d...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/13/4/717 |
| _version_ | 1827759112430026752 |
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| author | Guoming Li Richard S. Gates Meaghan M. Meyer Elizabeth A. Bobeck |
| author_facet | Guoming Li Richard S. Gates Meaghan M. Meyer Elizabeth A. Bobeck |
| author_sort | Guoming Li |
| collection | DOAJ |
| description | Gait scoring is a useful measure for evaluating broiler production efficiency, welfare status, bone quality, and physiology. The research objective was to track and characterize spatiotemporal and three-dimensional locomotive behaviors of individual broilers with known gait scores by jointly using deep-learning algorithms, depth sensing, and image processing. Ross 708 broilers were placed on a platform specifically designed for gait scoring and manually categorized into one of three numerical scores. Normal and depth cameras were installed on the ceiling to capture top-view videos and images. Four birds from each of the three gait-score categories were randomly selected out of 70 total birds scored for video analysis. Bird moving trajectories and 16 locomotive-behavior metrics were extracted and analyzed via the developed deep-learning models. The trained model gained 100% accuracy and 3.62 ± 2.71 mm root-mean-square error for tracking and estimating a key point on the broiler back, indicating precise recognition performance. Broilers with lower gait scores (less difficulty walking) exhibited more obvious lateral body oscillation patterns, moved significantly or numerically faster, and covered more distance in each movement event than those with higher gait scores. In conclusion, the proposed method had acceptable performance for tracking broilers and was found to be a useful tool for characterizing individual broiler gait scores by differentiating between selected spatiotemporal and three-dimensional locomotive behaviors. |
| first_indexed | 2024-03-11T09:16:30Z |
| format | Article |
| id | doaj.art-f06a9f61ff7b4696ae4f2834d2d30c5a |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-11T09:16:30Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-f06a9f61ff7b4696ae4f2834d2d30c5a2023-11-16T18:40:33ZengMDPI AGAnimals2076-26152023-02-0113471710.3390/ani13040717Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring SystemGuoming Li0Richard S. Gates1Meaghan M. Meyer2Elizabeth A. Bobeck3Department of Poultry Science, The University of Georgia, Athens, GA 30602, USADepartment of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USADepartment of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USADepartment of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USAGait scoring is a useful measure for evaluating broiler production efficiency, welfare status, bone quality, and physiology. The research objective was to track and characterize spatiotemporal and three-dimensional locomotive behaviors of individual broilers with known gait scores by jointly using deep-learning algorithms, depth sensing, and image processing. Ross 708 broilers were placed on a platform specifically designed for gait scoring and manually categorized into one of three numerical scores. Normal and depth cameras were installed on the ceiling to capture top-view videos and images. Four birds from each of the three gait-score categories were randomly selected out of 70 total birds scored for video analysis. Bird moving trajectories and 16 locomotive-behavior metrics were extracted and analyzed via the developed deep-learning models. The trained model gained 100% accuracy and 3.62 ± 2.71 mm root-mean-square error for tracking and estimating a key point on the broiler back, indicating precise recognition performance. Broilers with lower gait scores (less difficulty walking) exhibited more obvious lateral body oscillation patterns, moved significantly or numerically faster, and covered more distance in each movement event than those with higher gait scores. In conclusion, the proposed method had acceptable performance for tracking broilers and was found to be a useful tool for characterizing individual broiler gait scores by differentiating between selected spatiotemporal and three-dimensional locomotive behaviors.https://www.mdpi.com/2076-2615/13/4/717broilerwelfare assessmentbehavior recognitiondeep learningtracking |
| spellingShingle | Guoming Li Richard S. Gates Meaghan M. Meyer Elizabeth A. Bobeck Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System Animals broiler welfare assessment behavior recognition deep learning tracking |
| title | Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System |
| title_full | Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System |
| title_fullStr | Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System |
| title_full_unstemmed | Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System |
| title_short | Tracking and Characterizing Spatiotemporal and Three-Dimensional Locomotive Behaviors of Individual Broilers in the Three-Point Gait-Scoring System |
| title_sort | tracking and characterizing spatiotemporal and three dimensional locomotive behaviors of individual broilers in the three point gait scoring system |
| topic | broiler welfare assessment behavior recognition deep learning tracking |
| url | https://www.mdpi.com/2076-2615/13/4/717 |
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