| Plant disease identification using explainable 3D deep learning on hyperspectral images K Nagasubramanian, S Jones, AK Singh, S Sarkar, A Singh, ... Plant methods 15, 1-10, 2019 | 284 | 2019 |
| Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems K Nagasubramanian, S Jones, S Sarkar, AK Singh, A Singh, ... Plant methods 14, 1-13, 2018 | 166 | 2018 |
| Challenges and opportunities in machine-augmented plant stress phenotyping A Singh, S Jones, B Ganapathysubramanian, S Sarkar, D Mueller, ... Trends in Plant Science 26 (1), 53-69, 2021 | 135 | 2021 |
| Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps K Nagasubramanian, S Jones, AK Singh, A Singh, ... arXiv preprint arXiv:1804.08831, 2018 | 57 | 2018 |
| Meta-GWAS for quantitative trait loci identification in soybean JM Shook, J Zhang, SE Jones, A Singh, BW Diers, AK Singh G3 11 (7), jkab117, 2021 | 32 | 2021 |
| High-throughput phenotyping in soybean AK Singh, A Singh, S Sarkar, B Ganapathysubramanian, W Schapaugh, ... High-throughput crop phenotyping, 129-163, 2021 | 20 | 2021 |
| Unoccupied aerial systems imagery for phenotyping in cotton, maize, soybean, and wheat breeding AW Herr, A Adak, ME Carroll, D Elango, S Kar, C Li, SE Jones, AH Carter, ... Crop Science 63 (4), 1722-1749, 2023 | 10 | 2023 |
| The inheritance of plant and flower traits in rose SE Jones | 7 | 2013 |
| Identification of spectral disease signatures and resistant QTL for charcoal rot infection in soybean SE Jones Iowa State University, 2017 | 1 | 2017 |
