1. Assessing phenotypic diversity and sensor‐based metrics for drought response in soybean
2. Digital twins for the plant sciences
3. Dissecting seed composition QTL from wild soybean: fine-mapping, candidate gene identification, and evaluation of introgression effects on agronomic performance
4. Genetic dissection of heat stress tolerance in soybean through genome-wide association studies and use of genomic prediction to enhance breeding applications
5. Genetic variability in biomass partitioning and surface residue carbon-nitrogen ratios in soybean
6. Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests
7. Genomic and phenomic prediction for soybean seed yield, protein, and oil
8. Heat Stress and Soil Microbial Disturbance Influence Soybean Root Metabolite, Microbiome Profiles, and Nodulation
9. InsectNet: Real-time identification of insects using an end-to-end machine learning pipeline
10. Leveraging Vision Language Models for Specialized Agricultural Tasks
11. Optimizing Navigation And Chemical Application in Precision Agriculture With Deep Reinforcement Learning And Conditional Action Tree
12. Phenotypic plasticity of bread wheat contributes to yield reliability under heat and drought stress
13. Plant‐based protein crops and their improvement: Current status and future perspectives
14. ReinDSplit: Reinforced Dynamic Split Learning for Pest Recognition in Precision Agriculture
15. Robust soybean seed yield estimation using high-throughput ground robot videos
16. Soybean maturity prediction using two‐dimensional contour plots from drone‐based time series imagery
17. TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models
18. Time series gwas for iron deficiency chlorosis tolerance in soybean using aerial imagery
19. Towards Large Reasoning Models for Agriculture
20. Transcriptional Insights into Soybean Genotypes Under Prolonged Heat Stress: Identification of Key Genes and Soil Influences for Enhanced Tolerance
21. Use of artificial intelligence in soybean breeding and production
22. Using soybean historical field trial data to study genotype by environment variation and identify mega‐environments with the integration of genetic and non‐genetic factors
23. WeedNet: A Foundation Model-Based Global-to-Local AI Approach for Real-Time Weed Species Identification and Classification