Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling Yield of Irrigated and Rainfed Bean in Central and Southern Sinaloa State, Mexico, Based on Essential Climate Variables. Atmosphere2024, 15, 573.
Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling Yield of Irrigated and Rainfed Bean in Central and Southern Sinaloa State, Mexico, Based on Essential Climate Variables. Atmosphere 2024, 15, 573.
Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling Yield of Irrigated and Rainfed Bean in Central and Southern Sinaloa State, Mexico, Based on Essential Climate Variables. Atmosphere2024, 15, 573.
Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling Yield of Irrigated and Rainfed Bean in Central and Southern Sinaloa State, Mexico, Based on Essential Climate Variables. Atmosphere 2024, 15, 573.
Abstract
The goal was to model the irrigated (IBY) and rainfed (RBY) bean yields, as a function of essential climatic variables (ECVs), in the center (Culiacán) and south (Rosario) from Sinaloa. In Sinaloa, and for the period 1982–2013 (October–March), the following were calculated: a) temperatures. b) average degree days for the bean, c) cumulative potential evapotranspiration and d) cumulative effective precipitation. For ECVs, from the European Space Agency, e) daily soil moisture. f) IBY and RBY, from the Agrifood and Fisheries Information Service. Multiple linear regressions were applied, which modeled IBY–RBY (dependent variables), as a function of ECVs (independent variables). Then, to establish each Pearson correlation (PC) as significantly different from zero, a hypothesis test was applied: PC vs Pearson's critical correlation (CPC). The four models obtained were significantly predictive: IBY–Culiacán (PC = 0.590 > CPC = |0.349|), RBY–Culiacán (PC = 0.734 > CPC = |0.349|), IBY–Rosario (PC = 0.621 > CPC = |0.355|) and RBY–Rosario (PC = 0.532 > CPC = |0.349|). This study is the first in Sinaloa to predict IBY and RBY based on ECVs, contributing to the production of sustainable food.
Keywords
significantly different from zero; multiple linear regressions; sustainable foods; the breadbasket of Mexico
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
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