DSSAT modeling of corn under climate change and planting density during the rainy season
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Corn cultivation during the rainy season can be affected by climate variability; therefore, this study evaluated the agronomic performance of corn during the rainy season under climate change and planting densities using a crop simulation model. Field, climate, and soil data were integrated, and three scenarios were run; plant height, number of leaves, leaf area index, above-ground and root biomass, and root growth were analyzed. The simulation was validated by comparing observations and simulations with the coefficient of determination. In the first scenario, the number of leaves observed was 9 and the simulated number was 12, with a coefficient of determination of 0.946; the leaf area index was 0.56 observed and 0.68 simulated. In the third scenario, the simulated root length was 0.51 meters compared to 0.23 meters observed, and the simulated height was 0.16 meters compared to 0.61 meters observed. It is concluded that the model allows for the projection of corn development and supports agronomic decisions in the face of short-term climate variability.
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