14 citations as recorded by crossref.

1. Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data K. Reddy et al. https://doi.org/10.5194/gmd-18-763-2025
2. Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia V. Pandey et al. https://doi.org/10.1007/s00704-024-05158-4
3. GHG emissions and carbon footprint in wheat cultivation practices in Bihar state of India R. Pal et al. https://doi.org/10.3389/fsufs.2025.1661999
4. Variability in crop responses as a function of environment affects the NDVI relationship with grain yield in wheat C. Paiboonvorachat et al. https://doi.org/10.1016/j.plaphe.2026.100237
5. The C-FEWS framework: Supporting studies of climate-induced extremes on food, energy, and water systems at the regional scale C. Vörösmarty et al. https://doi.org/10.3389/fenvs.2023.1069613
6. Gender, caste, and heterogeneous farmer preferences for wheat varietal traits in rural India V. Krishna et al. https://doi.org/10.1371/journal.pone.0272126
7. Phenology, fluxes and their drivers in major Indian agroecosystems: A modeling study using the Community Land Model (CLM5) K. Reddy & S. Baidya Roy https://doi.org/10.5194/bg-23-1365-2026
8. Which crop has the highest bioethanol yield in the United States? T. Lin et al. https://doi.org/10.3389/fenrg.2023.1070186
9. Carbon fluxes in spring wheat agroecosystem in India K. Reddy et al. https://doi.org/10.5194/esd-14-915-2023
10. Worldwide Maize and Soybean Yield Response to Environmental and Management Factors Over the 20th and 21st Centuries T. Lin et al. https://doi.org/10.1029/2021JG006304
11. A food crop yield emulator for integration in the compact Earth system model OSCAR (OSCAR-crop v1.0) X. Liu et al. https://doi.org/10.5194/gmd-19-5857-2026
12. The growing factors impact the productivity of new soft winter wheat varieties L. Prysiazhniuk et al. https://doi.org/10.21498/2518-1017.18.4.2022.273989
13. A modeling framework of a territorial socio-ecosystem to study the trajectories of change in agricultural phytosanitary practices A. Bourceret et al. https://doi.org/10.1016/j.ecolmodel.2024.110727
14. IoT-based winter season crop prediction using machine learning on Vyas municipality ward No-13, Nepal P. Deepak https://doi.org/10.17352/2455-815X.000196