Development and evaluation of a simulation model to estimate the productivity of sweet oranges (Citrus sinensis L.)

• Grant number: 22/06804-3
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: October 01, 2022
• End date: August 01, 2026
• Field of knowledge: Agronomical Sciences - Agricultural Engineering - Soil and Water Engineering
• Principal Investigator: Patricia Angélica Alves Marques
• Grantee: Júlia Boscariol Rasera
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Company: Universidade de São Paulo (USP). Centro de Inovação da USP (INOVA)
• Associated research grant: 19/07665-4 - Center for Artificial Intelligence, AP.eScience.CPE
• Associated scholarship(s): 23/14692-3 - Adaptation, evaluation, and application of the DSSAT CSM-CROPGRO model for sweet orange, BE.EP.DR

Abstract

Brazil is the largest producer of citrus in the world. Climate change has indicated an increase in both global temperature and the concentration of greenhouse gases in the atmosphere and has provoked a new alert in agriculture. In this context, there is a need to carry out studies that seek to assess climate risks and production potential in different regions of Brazil, under current and future conditions. The objectives of this work are: a) to explore the relationship between climate data and productivity of sweet oranges; b) adapt, calibrate and evaluate different predictive models of orange yield; c) develop and apply a model with a new approach for estimating orange yields; d) assess the impact of temporal and spatial climate variability, and climate change on orange yield. Predictive artificial intelligence models will be explored for time series analysis, in sequence, observed orange yield data from different locations and years will be used to calibrate and evaluate the performance of the models by Martini & Ortolani (2006), Ben Mechlia & Carroll (1989), Pereira et al. (2017) and DSSAT-CROPGRO (Morgan et al. 2003). With the analysis of the models, a model will be developed, which will be calibrated and validated, and then, a sensitivity analysis will be carried out, in relation to the variables air temperature, rain, solar radiation and CO2 concentration in the atmosphere. Subsequently, historical series of meteorological data from different producing regions in Brazil will be used to assess the impact of variability and climate change on the productivity of this species. For the evaluation of future scenarios, four General Circulation Climate Models and two greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5) will be considered.

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)

RASERA, JULIA BOSCARIOL; DA SILVA, ROBERTO FRAY; PIEDADE, SONIA; MOURAO FILHO, FRANCISCO DE ASSIS ALVES; DELBEM, ALEXANDRE CLAUDIO BOTAZZO; SARAIVA, ANTONIO MAURO; SENTELHAS, PAULO CESAR; MARQUES, PATRICIA ANGELICA ALVES. Do Gridded Weather Datasets Provide High-Quality Data for Agroclimatic Research in Citrus Production in Brazil?. AGRIENGINEERING, v. 5, n. 2, p. 17-pg., 2023-06-01. (19/07665-4, 22/06804-3)

RASERA, JULIA BOSCARIOL; DA SILVA, ROBERTO FRAY; MOURAO FILHO, FRANCISCO DE ASSIS ALVES; DELBEM, ALEXANDRE CLAUDIO BOTAZZO; SARAIVA, ANTONIO MAURO; SENTELHAS, PAULO CESAR; MARQUES, PATRICIA ANGELICA ALVES. Climate Change and Citriculture: A Bibliometric Analysis. AGRONOMY-BASEL, v. 13, n. 3, p. 22-pg., 2023-03-01. (19/07665-4, 22/06804-3)