Optimizing Sugarcane Planting Windows Using a Crop Simulation Model at the State Level

Abstract

The planning of planting/harvest operations improves yield and economic returns of sugarcane production systems. This study aims to define homogenous regions and optimum planting dates for sugarcane using simulated water-limited yield in the state of Goias, Brazil. Yw was simulated using crop model and 24 planting dates across the year, including gridded weather data and soil water availability to the crop over the state in a grid cell size of 0.5 × 0.5°. The crop model was evaluated comparing simulated and measured yield tendency across planting dates. Homogeneous regions were obtained based on Yw, using the Ward’s method and Euclidean distance. The crop model was able to replicate yield tendency across planting dates. The clustering divided the state into four homogenous regions, where optimum planting period had different intervals due to the interaction with climate and soil. The optimum planting window had four dates for the region with lower Yw (105 t ha−1). The region with higher Yw (131 t ha−1) had the longer optimum window, with seven dates, but with the higher yield reduction (− 6%) than other regions (− 3%) when planting date was changed from 1st to 2nd better dates. This way, the results and the approach used in this study defines yield level and optimal planting dates, which can be apply to define harvest period and the area required to supply the sugarcane mill demands, leading to better machinery and labor work management, helping to elaborate mills and state-level strategies to increase sugarcane production.