Simulating upland rice yield at diverse temperatures using DSSAT4.7-CERES-Rice crop model under changing climatic conditions in southern Thailand

Abstract

Declaration of climate emergency reminds that the main source of variations in worldwide food production sourced from developing countries and is of utmost concern. Process-based models use simplified functions to express the interactions between upland rice growth and the major environmental factors (i.e., climate, soils, and management) that affect crops yield. This research was conducted to investigate the DSSAT-CERES-Rice model for simulating the impact of different temperature (28ËšC, 30ËšC and 32ËšC) on upland grain yield (Dawk Pa-yawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm). The results showed that the temperature significantly affected the grain yield, flowering, and maturity date. The highest grain yield bearing genotype was Bow leb Nahng (6235.80 kgha^-1) with the highest variation between the genotypes. At maximum temperature 32ËšC simulated grain yield varied from (3194-6669) kgha^-1, at high temperature 30ËšC it varied from 3252-6667 kgha^-1 while at moderate temperature 28ËšC 3189-6711 kgha^-1 was the observed range. However, results indicated that moderate temperature i.e., 28ËšC gave the highest simulated grain yield. Thus, it was demonstrated that the CERES-Rice model was more useful as a tool for simulating grain yield under the changing different temperature conditions.