Sequence analysis of dssat to select optimum strategy of crop residue and nitrogen for sustainable rice-wheat rotation
Weather variability affects the production of most cropping systems, and rice (Oryza sativa L.)-wheat (Triticum aestivum L.) rotation is not an exception. Integrating weather forecasts with soil fertility management options is one way to combat the production decrease by anticipating weather variability along with sustaining the soil environment. Sequence analysis of DSSAT3.5 was used to select the best combination of crop residue and N application rate for sustainable production of rice-wheat rotation under generated weather. CERES-Rice and CERES-Wheat of DSSAT3.5 were calibrated and validated for rice and wheat crops. Weather generator SIMMETEO was used to generate the weather variables of 30 future years. The variables generated by SIMMETEO, which closely matched with actual weather variables, were used for yield prediction by the sequence analysis program driver. The regression analysis showed a strong relationship between generated rainfall values and predicted yield. The different crop residue levels and N rates were compared for transplanted rice-wheat (T) and direct seeded rice-wheat (D) rotation under 10 yr of generated weather scenario. The sequence analysis of DSSAT predicted the combination of wheat crop residue with 100 kg N ha–1 for rice and rice residue with 80 kg N ha–1 for wheat provided stable yield for both T and D rotation. These combinations of crop residues and N rates were also predicted best for stable rotations under 30 yr of generated weather.