Zobrazeno 1 - 4
of 4
pro vyhledávání: '"A. V. M. Subbarao"'
Autor:
Manoranjan Kumar, Yash Agrawal, Sirisha Adamala, Pushpanjali, A. V. M. Subbarao, V. K. Singh, Ankur Srivastava
Publikováno v:
Water, Vol 16, Iss 16, p 2233 (2024)
The potential of generalized deep learning models developed for crop water estimation was examined in the current study. This study was conducted in a semiarid region of India, i.e., Karnataka, with daily climatic data (maximum and minimum air temper
Externí odkaz:
https://doaj.org/article/fcb9431c5bae42cebadfcc264ac6609f
Autor:
Anjan K. Sarmah, Abburi V. M. Subbarao, Santanu K. Bal, Bondita Goswami, Kushal Sarmah, Kuldip Medhi, Nikhil S. Paschapur
Publikováno v:
International Journal of Environment and Climate Change. :16-30
Three years of field trial along with DSSAT v4.6 CERES-Rice model-based simulation experiment was carried out to study the impact of climate change on Sali rice yield under various Representative Concentration Pathways (RCPs) in the agro-climatic con
Autor:
V. Visha Kumari, Rajkumar Dhakar, S. K. Bal, P. Vijaya Kumar, A. V. M. Subbarao, M. A. Sarath Chandran, Shivani Nagar
Publikováno v:
Advances in Crop Environment Interaction ISBN: 9789811318603
Improving water productivity is a major concern globally and more problematic in arid and semiarid regions. Decision support system based on crop simulation models can be a handy tool for improving water use efficiency. In this chapter, we have descr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d22304fcbd6d3c0d7af85fb1f017d5de
https://doi.org/10.1007/978-981-13-1861-0_11
https://doi.org/10.1007/978-981-13-1861-0_11
Autor:
Boote, Ken, Hoogenboom, Gerrit, U Singh, P Singh, K Srinivas, Reddy, Raji, V S Bhatia, Dilwar A Choudury, A V M Subbarao, Hargreaves, John, Poulton, Perry, Nageswara Rao, M Shamin, Kripan Ghosh, Anup Das, N Subash, Tariqul Islam, Jean-Louis Durand, Ripoche, Dominic, Sanctis, Giacomo De, Kumar, Naresh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eacbe21d8b49a5edae996cc30e7af868