Quantifying yield gap for rice cropping systems in Lower Gangetic Plains

Modelling the effect of changing transplanting date on consumptive water footprints for paddy under the system of rice intensification

“…1 July to mid-August in kharif and mid-December to mid-February in rabi) was considered here based on the study of Adhikari et al 31 for the West Bengal state of India. The interval of 15 days between two different transplanting dates for scenarios development under both kharif and rabi seasons for this study area was decided based on Rajwade et al 41 and Debnath et al 42 Figure 2 shows the 30 years (1986-2015) of mean solar radiation and the maximum and minimum temperature during grain filling stage with seasonal rainfall for different transplanting dates during both kharif and rabi seasons. At this study area, the early transplanting in kharif exhibited the highest mean minimum temperatures and the delayed transplanting in rabi showed the highest mean solar radiation, as well as maximum and minimum temperatures, throughout the grain-filling period.…”

Identifying most promising agronomic adaptation strategies to close rainfed rice yield gap in future: a model-based assessment

“…baseline condition) for long, medium and short duration cultivars in the study. The DSSAT model simulates Y w and Y a of Shankar and IR36 rice cultivars by using calibrated values from field observations at research plots of the Agricultural and Food Engineering Department (AgFE) during 2015-2017 (Debnath et al 2018), whereas the model simulates for remaining cultivars in the study area by using calibrated genotype coefficient values from published literature (Pathak et al 2003;Kumar & Tripathi 2011;Satapathy et al 2014). The in-built software of DSSAT, Genotype coefficient Calculator (GENCALC), was used to identify genotype coefficients of the cultivars (Hunt et al 1993).…”

“…It could be noted that the major rice-growing states of India consist a large spatial variation of soil properties and climate characteristics which makes the DSSAT model calibration quite difficult for every part of the study area. Moreover, the main aim of this study was not to evaluate the model capability as the model has been successfully used in many places of India where researchers showed its usefulness to simulate rice yield (Pathak et al 2003;Shukla & Matthews 2004;Kumar & Tripathi 2011;Mishra et al 2013;Satapathy et al 2014;Rajwade et al 2018;Debnath et al 2018). Gupta & Mishra (2019) compared average yield simulated from observed and multi-GCM ensemble of historical yield for period 1976-2005 at 20 agroecological zones in India by using calibrated genotype coefficients values from Satapathy et al (2014) to examine the appropriateness of the model.…”

“…By assuming the same field management practices in the future, making climate the only variable, the impact of projected climate change on rice yield and yield gap is assessed by comparing Y w and Y a in the study. The model simulates Y w and Y a by considering the currently recommended crop spacing of 20 cm  20 cm and N-fertilizer level of 120 kg/ha (Mishra et al 2013;Debnath et al 2018;Debnath et al 2020; Rice Knowldege Bank 2021) under timely transplanting date (i.e. 15th June to 15th July) condition (Mishra et al 2013).…”

“…The short duration cultivar has several advantages over a long or medium duration crop as it requires less water availability, less exposure to hazards such as insects, pathogenic organisms, drouths and typhoons and increases the time the land would be available for subsequent plantings of other crops. It can be noted that delayed transplanting experiences more short-term water deficits at some point of time during the growing season (Debnath et al 2018). Therefore, the adverse impact of climate change on rainfed rice cropping systems could be minimized by considering timing of transplanting as 1st June, 15th June and 1st July for long, medium and short duration cultivars, respectively, under the future climate change scenario.…”