1. AAC Connery hard red spring wheat
2. A comprehensive study on soybean yield prediction using soil and hyperspectral reflectance data
3. Agri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction
4. Basic Principles of Plant Breeding
5. Breeding Methods
6. “Canopy fingerprints” for characterizing three-dimensional point cloud data of soybean canopies
7. Common Bean Breeding
8. Cowpea breeding
9. Cyber-agricultural systems for crop breeding and sustainable production
10. Deep learning powered real-time identification of insects using citizen science data
11. Data driven ensemble learning for soybean yield prediction
12. Development of Glycine max Germplasm Highly Resistant to Sclerotinia sclerotiorum
13. Genetic variation and germplasm usage
14. Groundnut Breeding
15. Millet Breeding
16. Models to Estimate Genetic Gain of Soybean Seed Yield from Annual Multi-Environment Field Trials
17. Participatory Plant Breeding and Participatory Variety Selection
18. Pedigree Naming Systems and Symbols
19. Optimized Class-specific Data Augmentation for Plant Stress Classification
20. Out-of-distribution algorithms for robust insect classification
21. Out-of-distribution detection algorithms for robust insect classification
22. Refresher on Population and Quantitative Genetics
23. Rice Breeding
24. Seed systems and certification
25. Seed Systems and Certification
26. Self‐supervised learning improves classification of agriculturally important insect pests in plants
27. Smart Connected Farms and Networked Farmers to Tackle Climate Challenges Impacting Agricultural Production
28. Sorghum Breeding
29. Steps in Cultivar Development
30. UAS imagery for phenotyping in cotton, maize, soybean, and wheat breeding
31. Using machine learning enabled phenotyping to characterize nodulation in three early vegetative stages in soybean