Por favor, use este identificador para citar o enlazar este ítem:
http://cibnor.repositorioinstitucional.mx/jspui/handle/1001/2790| Sensitivity of Four Indices of Meteorological Drought for Rainfed Maize Yield Prediction in the State of Sinaloa, Mexico | |
| OMAR LLANES CARDENAS MARIANO NORZAGARAY CAMPOS ALBERTO GAXIOLA HERNANDEZ ERNESTINA PEREZ GONZALEZ JORGE MONTIEL MONTOYA ENRIQUE TROYO DIEGUEZ | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| DOI: 10.3390/agriculture12040525 URL: https://www.mdpi.com/2077-0472/12/4/525 ISSN: 2077-0472 | |
| "In the state of Sinaloa, rainfall presents considerable irregularities, and the climate is mainly semiarid, which highlights the importance of studying the sensitivity of various indices of meteorological drought. The goal is to evaluate the sensitivity of four indices of meteorological drought from five weather stations in Sinaloa for the prediction of rainfed maize yield. Using DrinC software and data from the period 1982–2013, the following were calculated: the standardized precipitation index (SPI), agricultural standardized precipitation index (aSPI), reconnaissance drought index (RDI) and effective reconnaissance drought index (eRDI). The observed rainfed maize yield (RMYob) was obtained online, through free access from the database of the Agrifood and Fisheries Information Service of the government of Mexico. Sensitivities between the drought indices and RMYob were estimated using Pearson and Spearman correlations. Predictive models of rainfed maíze yield (RMYpr) were calculated using multiple linear and nonlinear regressions. In the models, aSPI and eRDI with reference periods and time steps of one month (January), two months (December–January) and three months (November–January), were the most sensitive. The correlation coefficients between RMYob and RMYpr ranged from 0.423 to 0.706, all being significantly different from zero. This study provides new models for the early calculation of RMYpr. Through appropriate planning of the planting–harvesting cycle of dryland maize, substantial socioeconomic damage can be avoided in one of the most important agricultural regions of Mexico." | |
| Multidisciplinary Digital Publishing Institute | |
| 2022 | |
| Artículo | |
| Agriculture | |
| Español | |
| Omar, L.-C.; Mariano, N.-C.; Alberto, G.; Ernestina, P.-G.; Jorge, M.-M.; Enrique, T.-D. Sensitivity of Four Indices of Meteorological Drought for Rainfed Maize Yield Prediction in the State of Sinaloa, Mexico. Agriculture 2022, 12, 525. https://doi.org/10.3390/agriculture12040525 | |
| HIDROBIOLOGÍA | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Artículos |
Cargar archivos:
| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Sensitivity of Four Indices of Meteorological Drought for Rainfed Maize Yield Prediction in the State of Sinaloa, Mexico.pdf | 81.08 kB | Adobe PDF | Visualizar/Abrir |