Author(s):
Moreto, Victor Brunini [UNESP] ; Rolim, Glauco de Souza [UNESP] ; Zacarin, Bruno Gustavo ; Vanin, Ana Paula ; de Souza, Leone Maia ; Latado, Rodrigo Rocha
Date: 2018
Persistent ID: http://hdl.handle.net/11449/173458
Origin: Oasisbr
Subject(s): Agrometeorology; Citrus sinensis L. Osbeck; Crop model; Early prevision; Prediction; Agrometeorology; Agrometeorology; Citrus sinensis L. Osbeck; Citrus sinensis L. Osbeck; Crop model; Crop model; Early prevision; Early prevision; Prediction; Prediction
Description
Made available in DSpace on 2018-12-11T17:05:35Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-11-01
Forecasting is the act of predicting unknown future events using available data. Estimating, in contrast, uses data to simulate an actual condition. Brazil is the world’s largest producer of oranges, and the state of São Paulo is the largest producer in Brazil. The “Valência” orange is among the most common cultivars in the state. We analyzed the influence of monthly meteorological variables during the growth cycle of Valência oranges grafted onto “Rangpur” lime rootstocks (VACR) for São Paulo, and developed monthly agrometeorological models for forecasting the qualitative attributes of VACR in mature orchard. For fruits per box for all months, the best accuracy was of 0.84 % and the minimum forecast range of 4 months. For the relation between °brix and juice acidity (RATIO) the best accuracy was of 0.69 % and the minimum forecast range of 5 months. Minimum, mean and maximum air temperatures, and relative evapotranspiration were the most important variables in the models.
Department of Exact Science Faculdade de Ciências Agrárias e Veterinárias University of São Paulo State (UNESP)
Fisher Group S. A
Citrus Center ‘Sylvio Moreira
Department of Exact Science Faculdade de Ciências Agrárias e Veterinárias University of São Paulo State (UNESP)
