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Multi-model approach to sugarcane yield forecasting and assessment of crop performance under current and future climate conditions

Grant number: 16/11170-2
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): May 01, 2017
Effective date (End): June 30, 2020
Field of knowledge:Agronomical Sciences - Agronomy - Agricultural Meteorology
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal researcher:Paulo Cesar Sentelhas
Grantee:Henrique Boriolo Dias
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated scholarship(s):17/24424-5 - Developing trait parameters in the APSIM-Sugar model for Brazilian sugarcane varieties and their use to optimize the genotype x environment x management interaction for yield and quality, BE.EP.DR


Sugarcane has a great importance to the Brazilian agribusiness. It is grown in about 10 million ha with a wide range of soil and climatic conditions. Due to the great variability of sugarcane yield levels over successive ratoons and between the producing regions, estimates and forecasts of crops are valuable for planning and decision-making processes in the sugarcane industry. Sugarcane cultivation has expanded to regions previously considered marginal by water stress, which requires crop to adapt to these new environments. In addition to adaptations to new production environments, adaptations to potential climate change should be evaluated. Climate change is expected to have significant effects on the sugarcane production and, therefore, reliable predictions about the crop responses to these changes are necessary. Estimates, forecasts and assessment of yield in current and future climate conditions can be made by a multi-model approach (ensemble), which can reduce the uncertainty of simulations, minimizing the error of estimates. Thus, this project aims to: i) develop a sugarcane yield forecasting system with a multi-model approach, employing historical series of meteorological data; ii) evaluate the effect of changes on cultivar traits in two crop simulation models (DSSAT/CANEGRO and APSIM-Sugarcane) in order to adapt sugarcane to environments under water stress conditions and; iii) evaluate sugarcane yield in future climate change scenarios through a multi-model approach, using the default and changed cultivar traits in order to adapt the crop to these scenarios. It is expected that the results can help in planning and decision-making processes in the sugarcane industry through greater precision and accurate information in both current and future climate scenarios. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DIAS, HENRIQUE BORIOLO; SENTELHAS, PAULO CESAR; INMAN-BAMBER, GEOFF; EVERINGHAM, YVETTE. Sugarcane yield future scenarios in Brazil as projected by the APSIM-Sugar model. INDUSTRIAL CROPS AND PRODUCTS, v. 171, NOV 1 2021. Web of Science Citations: 0.
DIAS, HENRIQUE BORIOLO; INMAN-BAMBER, GEOFF; EVERINGHAM, YVETTE; SENTELHAS, PAULO CESAR; BERMEJO, RODRIGO; CHRISTODOULOU, DIOMEDES. Traits for canopy development and light interception by twenty-seven Brazilian sugarcane varieties. FIELD CROPS RESEARCH, v. 249, APR 1 2020. Web of Science Citations: 0.
DIAS, HENRIQUE BORIOLO; INMAN-BAMBER, GEOFF; BERMEJO, RODRIGO; SENTELHAS, PAULO CESAR; CHRISTODOULOU, DIOMEDES. New APSIM-Sugar features and parameters required to account for high sugarcane yields in tropical environments. FIELD CROPS RESEARCH, v. 235, p. 38-53, APR 1 2019. Web of Science Citations: 2.

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