Version 1
: Received: 26 March 2024 / Approved: 27 March 2024 / Online: 27 March 2024 (08:14:06 CET)
How to cite:
Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling of Yield of Irrigated and Rainfed Bean, Based on Essential Climatic Variables, in the Center and South from Sinaloa State, Mexico. Preprints2024, 2024031650. https://doi.org/10.20944/preprints202403.1650.v1
Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling of Yield of Irrigated and Rainfed Bean, Based on Essential Climatic Variables, in the Center and South from Sinaloa State, Mexico. Preprints 2024, 2024031650. https://doi.org/10.20944/preprints202403.1650.v1
Llanes Cárdenas, O.; Estrella Gastélum, R.D.; Parra Galaviz, R.E.; Gutiérrez Ruacho, O.G.; Ávila Díaz, J.A.; Troyo Diéguez, E. Modeling of Yield of Irrigated and Rainfed Bean, Based on Essential Climatic Variables, in the Center and South from Sinaloa State, Mexico. Preprints2024, 2024031650. https://doi.org/10.20944/preprints202403.1650.v1
APA Style
Llanes Cárdenas, O., Estrella Gastélum, R.D., Parra Galaviz, R.E., Gutiérrez Ruacho, O.G., Ávila Díaz, J.A., & Troyo Diéguez, E. (2024). Modeling of Yield of Irrigated and Rainfed Bean, Based on Essential Climatic Variables, in the Center and South from Sinaloa State, Mexico. Preprints. https://doi.org/10.20944/preprints202403.1650.v1
Chicago/Turabian Style
Llanes Cárdenas, O., Jeován A. Ávila Díaz and Enrique Troyo Diéguez. 2024 "Modeling of Yield of Irrigated and Rainfed Bean, Based on Essential Climatic Variables, in the Center and South from Sinaloa State, Mexico" Preprints. https://doi.org/10.20944/preprints202403.1650.v1
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:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
