Potato tuber yield were simulated at Jorhat, Assam under various Representative Concentration Pathways (RCPs) scenarios for 2020, 2050 and 2080 using DSSAT SUBSTOR-Potato model. The model was calibrated and validated for three potato cultivars, viz., Kufri Jyoti, Kufri Pokhraj and Kufri Himalini with the experimental data collected during 2014-15 and 2015-16. Results revealed that if planting is delayed beyond November, all these cultivars are likely to record drastic reduction in tuber yield. Cultivar Kufri Himalini may incur tuber yield loss of 64 per cent in 2020 to 75 per cent in 2080, followed by Kufri Jyoti (57.6% in 2020 to 71.5% in 2080) and Kufri Pokhraj (45.2% in 2020 to 56.2% in 2080). Among the cultivars, Kufri Pokhraj may remain a viable cultivar up to 2050, but Kufri Himalini may lose its sustainability by 2020 itself. Hence, adjustment of planting time and development of improved adaptive potato cultivarsonly will ascertai n future potato production in this region.
Impact of climate change on rice yield variabilities under various Representative Concentration Pathways (RCPs) has been estimated for Jorhat district, under Upper Brahmaputra Valley Agroclimatic Zone of Assam. CERES-Rice module of DSSAT 4.5 was calibrated and validated for rice cultivar ‘Mahsuri’ under three different dates of transplanting between May and July. Increase in both maximum and minimum temperatures at Jorhat, under all the RCPs for 2020, 2050 and 2080, suggests increasing level of heat stress during crop growth period. The deviations in projected grain yield over observed mean yield of 2009-2013 was found ranging from -12.7 to -43.4 per cent under all the scenario and dates of transplanting. Among all the climate scenarios, the reduction in grain yield was highest (-43.4%) under RCP 8.5 and lowest (-12.7%) under RCP 2.6.The mean yield reduction, considering all scenarios together, was highest in second transplanting date(-38.5%), followed by third(-28.8%) and first one (-23.3%).
Crop growth simulation models, properly validated against experimental data have the potential for facilitating strategic decision making in agriculture. Such validated models can also make use of the information generated for site specific experiments and trials to other sites and for different time durations. For proper calibration and evaluation of crop simulation models, there is a need for collection of a comprehensive minimum set of data on soil, weather and crop management in all agronomic experiments. Keeping this in view, data from seven field experiments conducted at Jorhat (26° 47' N, 94°12' E; 87 m amsl) during 1998-2005 for long duration rice cultivar Ranjit grown under rainfed conditions were collected. Genetic coefficients required for running the CERES-Rice v4.5 model were derived and the performance of the model under the climate of upper Brahmaputra valley was evaluated. These results indicate that the CERES Rice v4.5 model is capable of estimating growth stages and grain yield of rice cultivar Ranjit in the climatic conditions of upper Brahmaputra valley with reasonable accuracy. Hence, the model have the potential for its use as a tool in making various strategic and tactical decisions related to agricultural planning in the state.
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