Soybean (Glycine max) Purple Syndrome and its relationship with bioclimatic variables

Authors

  • M. Lavilla Universidad Nacional del Noroeste de la provincia de Buenos Aires, Buenos Aires, Argentina https://orcid.org/0000-0002-7282-4696
  • A. Ivancovich Universidad Nacional del Noroeste de la provincia de Buenos Aires, Buenos Aires, Argentina
  • A. Díaz Paleo Instituto Nacional de Tecnología Agropecuaria, Buenos Aires, Argentina

DOI:

https://doi.org/10.15517/am.2023.53248

Keywords:

phytopatology, diseases, climatology

Abstract

Introduction. Cercospora Leaf Blight (CBL) and Purple Seed Stain (PSS) are two endemic diseases of soybean (Glycine max) in Argentina. Objective. To select the bioclimatic variables (VBs) associated to the severity values equal to or greater than 90 % of the CBL and/or incidences equal to or greater than 50 % for the PSS in Argentina. Materials and methods. In the soybean region of Argentina between 2015 and 2016, 45 VBs available in Worldclim (temperatures, precipitations, and radiation) were used for modeling with the MaxEnt program. From the maps obtained in the modeling, the probabilities of a severity (SEV) of CBL ≥ 90 % and/or an incidence (I) of PSS ≥ 50 % were extracted for each geographical point evaluated in this study, subsequently used in generating multiple linear regressions. Results. Among of the 45 analyzed VBs, precipitation and temperature showed the strongest association with both diseases. Radiation exhibited the least association with both Cercospora Leaf Blight severity (SEV) and Purple Seed Stain incidence. Conclusion. Bioclimatic variables such as temperatures (between 25 °C and 30 °C) and precipitation between the months of December to April exhibited the strongest associations with severity values equal to or greater than 90 % of the CBL and/or incidences equal to or greater than 50 % for PSS in Argentina.

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Published

2023-08-25

How to Cite

Lavilla, M., Ivancovich, A., & Díaz Paleo, A. (2023). Soybean (Glycine max) Purple Syndrome and its relationship with bioclimatic variables. Agronomía Mesoamericana, 34(3), 53248. https://doi.org/10.15517/am.2023.53248

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