Agrometeorological models for forecasting the qualitative attributes of “Valência” oranges
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Data
2017-11-01
Autores
Moreto, Victor Brunini [UNESP]
Rolim, Glauco de Souza [UNESP]
Zacarin, Bruno Gustavo
Vanin, Ana Paula
de Souza, Leone Maia
Latado, Rodrigo Rocha
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Resumo
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.
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Palavras-chave
Agrometeorology, Citrus sinensis L. Osbeck, Crop model, Early prevision, Prediction
Como citar
Theoretical and Applied Climatology, v. 130, n. 3-4, p. 847-864, 2017.