Machine learning for high throughput stress phenotyping in plants
A Singh, B Ganapathysubramanian, A Kumar Singh, S SarkarTrends in plant science 21 (2), 110–124
An explainable deep machine vision framework for plant stress phenotyping
S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ...
Proceedings of the National Academy of Sciences 115 (18), 4613-4618
Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives
Singh, A.K., Ganapathysubramanian, B., Sarkar, S. and Singh, A.
Trends in Plant Science.
A real-time phenotyping framework using machine learning for plant stress severity rating in soybean
HS Naik, J Zhang, A Lofquist, T Assefa, S Sarkar, D Ackerman, A Singh, ...
Plant methods 13 (1), 23
Allelic variation at Psy1-A1 and association with yellow pigment in durum wheat grain
A Singh, S Reimer, CJ Pozniak, FR Clarke, JM Clarke, RE Knox, ...
Theoretical and Applied Genetics 118 (8), 1539-1548
Genome-wide association and epistasis studies unravel the genetic architecture of sudden death syndrome resistance in soybean
Jiaoping Zhang , Arti Singh, Daren Shane Mueller and Asheesh Kumar Singh
The Plant Journal
Ntire 2018 challenge on spectral reconstruction from rgb images
B Arad, O Ben-Shahar, R Timofte, L Van Gool, L Zhang, MH Yang, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …
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), 1-10
Identification and mapping of leaf, stem and stripe rust resistance quantitative trait loci and their interactions in durum wheat
A Singh, MP Pandey, AK Singh, RE Knox, K Ammar, JM Clarke, ...
Molecular breeding 31 (2), 405-418
Computer vision and machine learning for robust phenotyping in genome-wide studies
J Zhang, HS Naik, T Assefa, S Sarkar, RVC Reddy, A Singh, ...
Scientific reports 7, 44048
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), 86
A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting
G Sambuddha, Z Bangyou, CC Scott, PB Andries, JR David, W Xuemin, ...
A deep learning framework to discern and count microscopic nematode eggs
A Akintayo, GL Tylka, AK Singh, B Ganapathysubramanian, A Singh, ...
Scientific Reports 8 (1), 9145
Stripe rust and leaf rust resistance QTL mapping, epistatic interactions, and co-localization with stem rust resistance loci in spring wheat evaluated over three continents
A Singh, RE Knox, RM DePauw, AK Singh, RD Cuthbert, HL Campbell, ...
Theoretical and applied genetics 127 (11), 2465-2477
Main and epistatic loci studies in soybean for Sclerotinia sclerotiorum resistance reveal multiple modes of resistance in multi-environments
TC Moellers, A Singh, J Zhang, J Brungardt, M Kabbage, DS Mueller, ...
Scientific reports 7 (1), 3554
Genetic architecture of Charcoal Rot (Macrophomina phaseolina) Resistance in Soybean revealed using a diverse panel
SM Coser, RV Chowda Reddy, J Zhang, DS Mueller, A Mengistu, ...
Frontiers in plant science 8, 1626
Disease and insect resistance in plants
DP Singh, A Singh
Genetic mapping of common bunt resistance and plant height QTL in wheat
A Singh, RE Knox, RM DePauw, AK Singh, RD Cuthbert, S Kumar, ...
Theoretical and applied genetics 129 (2), 243-256
Genetics of pre-harvest sprouting resistance in a cross of Canadian adapted durum wheat genotypes
AK Singh, RE Knox, JM Clarke, FR Clarke, A Singh, RM DePauw, ...
Molecular breeding 33 (4), 919-929