Energy cane yield simulated by the DSSAT/CANEGRO model using climate scenarios in Teotônio Vilela, AL, Brazil

Abstract

Energy cane is a sugarcane variety obtained through genetic improvement and it has higher biomass production, essential for energy generation. Mathematical models for crop forecasts are excellent tools to support crops and can assist in the establishment of energy cane in different environments and in climate change scenarios. The objective of this work was to evaluate the impacts of climate change on energy cane yield simulated by the DSSAT/CANEGRO model in Alagoas, Northeast of Brazil. We used meteorological, crop and soil data from a field experiment conducted in Teotônio Vilela/AL in 2016 and 2017. The energy cane variety used was Vertix 2, cultivated in a plant cane cycle, with planting date on February 4, 2016, and harvesting date on January 31, 2017. Climate projections (2017-2060) were used based on RCPs (2.6, 4.5, 6.0 and 8.5). The model showed high precision and accuracy in simulations with values of 0.98 and 0.94 for fresh matter and 0.99 and 0.88 for dry matter, for d and r indices, respectively. In the RCP8.5 scenario, the yield reduction may be up to 15% (fresh matter) and 13.5% (dry matter) by 2060.