Decoding climate change : Modeling resilience of sugarcane Co86032 in Padegaon (Maharashtra), India with DSSAT and Random forest

Abstract

Climate change presents significant challenges to agricultural productivity, especially in tropical regions where crops like sugarcane are crucial for the economy. This study investigates the impact of climatic factors on the Co86032 sugarcane cultivar under the RCP 4.5 scenario. The integration of DSSAT and Random Forest models allows for a detailed exploration of non-linear relationships between temperature, rainfall, and crop outcomes. We used the DSSAT model and data mining to analyze the effects of past climate data (1986-2021) and future projections (2024-2098) of temperature and rainfall on key crop factors such as yield, sucrose content, green leaf area index, and harvest index. Results show that high temperatures (Tx) have a significant impact on yield and sucrose content, emphasizing the need for temperature management strategies, such as optimized planting schedules and heat-tolerant crop varieties.

The results indicate that high temperatures (Tx), a crucial factor in the RCP4.5 scenario, notably affect sugarcane yield and sucrose content, highlighting more focus on the management of maximum temperature fluctuation. This can be done with heat-tolerant breeding programs and optimizing planting strategies. In contrast, rainfall (Rf) has a weaker correlation with crop productivity, highlighting the importance of irrigation infrastructure in managing water stress. It also emphasizes the importance of stress management, crop diversification, and climate-smart farming techniques for improved resilience and resource use. Advanced irrigation systems aligned with temperature trends are recommended to stabilize crop yields.  Adaptive and real-time decision-making supported by predictive models (DSSAT) gives optimal crop management practices and the Random Forest model enhances yield predictions under varying climate scenarios. This combined modeling offers practical solutions for farmers and policymakers. Thus, precision agriculture tools like weather-based advisories, irrigation planning, and crop diversification are crucial for mitigating climate impacts and improving crop performance in changing conditions.

This study highlights the importance of understanding how climate influences sugarcane growth to assist industries in making informed decisions and adaptive precision farming practices to tackle the effects of climate change.