PREVISÃO DA PRODUTIVIDADE DO CAFÉ COM BASE EM DADOS AGROCLIMÁTICOS E APRENDIZAGEM DE MÁQUINA / FORECASTING COFFEE YIELD BASED ON AGROCLIMATIC DATA AND MACHINE LEARNING
DOI:
https://doi.org/10.48075/ijerrs.v3i1.26255Palavras-chave:
Coffea arábica, Temperatura do ar, Déficit hídrico.Resumo
Objetivou-se prever da produtividade do café com modelos regressivos usando dados meteorológicos em diferentes tipos de solo. O trabalho foi realizado em 15 localidades produtoras de C.arabica do Paraná. Os dados climáticos foram coletados por meio da plataforma NASA/POWER de 1989 e 2020 e os dados de produtividade do Coffea Arabica (sacas/ha) foram obtidos pela CONAB de 2003 a 2018. Para o calcula da evapotranspiração de referência (ETo) foi utilizado o método de Penman e Monteith, e o balanço hídrico climatológico (BH) de Thornthwaite e Mather (1955). Na modelagem dos dados, foi utilizado a regressão linear múltipla, em que a produtividade do C.arabica foi a variável dependente e as variáveis independentes foram temperatura do ar, precipitação, radiação solar, déficit hídrico, excedente hídrico e armazenamento de água no solo. Modelos de regressão linear múltipla são capazes de prever a produtividade do cafeeiro arábica no estado do Paraná com dois a três meses de antecedência a colheita. O elemento meteorológico que mais influencia o cafeeiro é a temperatura máxima do ar, principalmente durante a formação do fruto (março). Temperaturas máximas do ar em março de 31.01°C reduzem a produção do cafeeiro. Os modelos podem ser usados para previsão da produtividade do cafeeiro arábica auxiliando no planejamento dos cafeicultores da região do norte do Paraná.
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