Precision Livestock Farming Deep learning prediction of dairy cattle body weight Depth video data-enabled predictions of longitudinal dairy cow body weight using thresholding and Mask R-CNN algorithms Automated depth image acquisition Automated acquisition of top-view dairy cow depth image data using an RGB-D sensor camera. Genetics analysis of digital phenotypes The impact of trait measurement error on quantitative genetic analysis Industry-scale Pig Body Weight Estimation Comparative analysis of semantic segmentation and deep regression models with supervised pre-training for accurate prediction of pig body weight from video data, insights from industry-scale datasets Tracking of multiple pigs under control and stress conditions Video-based cow body condition score estimation Estimate dairy cow body condition score via computer vision systems Pig Body Condition Score Estimation Calf Diarrhea Early Detection Pig Activity Monitoring e.g., distance traveled, frequency of standing, sitting, or lying down, feed and water Intake behavior Calf Body Wegith Estimation Quantitative Genetics Evaluating metabolic and genomic data for predicting rice grain traits Evaluating metabolic and genomic data for predicting grain traits under high night temperature stress in rice. Genomic prediction for metabolites in rice Role of genomics on regulating rice grain metabolic variability under warmer nights, A statistical and image-based deep learning approach Rice phenotypic plasticity analysis Rice phenotypic plasticity analysis using a random regression model Multi-environment genomic analysis in sesame Multi-environment analysis enhances genomic prediction accuracy of agronomic traits in sesame Time series analysis in sesame. Leveraging genomics and temporal high-throughput phenotyping to enhance association mapping and yield prediction in sesame
