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Open AccessArticle

Using a Statistical Crop Model to Predict Maize Yield by the End-Of-Century for the Azuero Region in Panama

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Facultad de Ciencias y Tecnología, Universidad Tecnológica de Panamá (UTP), P.O. Box 0819-07289 El Dorado, Panama
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Meteorological Research Institute, Tsukuba 305-0052, Ibaraki, Japan
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Centro de Investigaciones Hidráulicas e Hidrotécnicas, Universidad Tecnológica de Panamá (UTP), P.O. Box 0819-07289 El Dorado, Panama
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Centro de Estudios Multidisciplinarios de Ingeniería Ciencias y Tecnología (CEMCIT-AIP), P.O. Box 0819-07289 El Dorado, Panama
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Faculty of Societal Safety Sciences, Kansai University, Takatsuki-shi 569-1098, Osaka, Japan
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Instituto de Investigación Agropecuaria de Panamá (IDIAP), Estafeta de Los Santos, 0739 Los Santos, Panama
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Facultad de Ingenieria de Sistemas Computacionales, Universidad Tecnológica de Panamá (UTP), P.O. Box 0819-07289 El Dorado, Panama
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(10), 1097; https://doi.org/10.3390/atmos11101097
Received: 10 September 2020 / Revised: 4 October 2020 / Accepted: 8 October 2020 / Published: 14 October 2020
(This article belongs to the Special Issue Climate Change and Agrometeorological Time Series)
In this article, we evaluate the impact of temperature and precipitation at the end of the 21st century (2075–2099) on the yield of maize in the Azuero Region in Panama. Using projected data from an atmospheric climate model, MRI-ACGM 3.2S, the study variables are related to maize yield (t ha1) under four different sea surface Temperature (SST) Ensembles (C0, C1, C2, and C3) and in three different planting dates (21 August, 23 September, and 23 October). In terms climate, results confirm the increase in temperatures and precipitation intensity that has been projected for the region at the end of the century. Moreover, differences are found in the average precipitation patterns of each SST-ensemble, which leads to difference in maize yield. SST-Ensembles C0, C1, and C3 predict a doubling of the yield observed from baseline period (1990–2003), while in C1, the yield is reduced around 5%. Yield doubling is attributed to the increase in rainfall, while yield decrease is related to the selection of a later planting date, which is indistinct to the SST-ensembles used for the calculation. Moreover, lower yields are related to years in which El Niño Southerm Oscilation (ENSO) are projected to occur at the end of century. The results are important as they provide a mitigation strategy for maize producers under rainfed model on the Azuero region, which is responsible for over 95% of the production of the country. View Full-Text
Keywords: Azuero; bias correction; climate prediction; crop yield; GCM; maize; MRI-AGCM; Panama; precipitation; statistical model; temperature Azuero; bias correction; climate prediction; crop yield; GCM; maize; MRI-AGCM; Panama; precipitation; statistical model; temperature
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MDPI and ACS Style

Martínez, M.M.; Nakaegawa, T.; Pinzón, R.; Kusunoki, S.; Gordón, R.; Sanchez-Galan, J.E. Using a Statistical Crop Model to Predict Maize Yield by the End-Of-Century for the Azuero Region in Panama. Atmosphere 2020, 11, 1097. https://doi.org/10.3390/atmos11101097

AMA Style

Martínez MM, Nakaegawa T, Pinzón R, Kusunoki S, Gordón R, Sanchez-Galan JE. Using a Statistical Crop Model to Predict Maize Yield by the End-Of-Century for the Azuero Region in Panama. Atmosphere. 2020; 11(10):1097. https://doi.org/10.3390/atmos11101097

Chicago/Turabian Style

Martínez, Marlemys M.; Nakaegawa, Tosiyuki; Pinzón, Reinhardt; Kusunoki, Shoji; Gordón, Román; Sanchez-Galan, Javier E. 2020. "Using a Statistical Crop Model to Predict Maize Yield by the End-Of-Century for the Azuero Region in Panama" Atmosphere 11, no. 10: 1097. https://doi.org/10.3390/atmos11101097

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