Mathematical modeling of the severity of Cercospora leaf spot of chard as a function of meteorological variables
DOI:
https://doi.org/10.24054/cyta.v10i1.3647Keywords:
Epidemiology, Cercospora beticola, multiple linear regressionAbstract
Chard (Beta vulgaris subsp cicla L.), is a plant rich in nutrients such as vitamins, minerals, antioxidants and dietary fibers, however, its cultivation faces challenges due to the lack of technology and, caused by the fungus Cercospora beticola. This research aimed to model the severity of Cercospora leaf spot of chard based on meteorological variables under environmental conditions in the garden of the Escuela Normal Superior de Pamplona (Norte de Santander; Colombia). The assessment of the progress of the disease was developed by evaluating the crop every seven (7) days over time to relate them to the meteorological variables. Seven climatic variables were considered, which were processed for seven days prior to each sample to obtain the maximum, average and minimum temperature, maximum, average and minimum weekly relative humidity, weekly accumulated rainfall and rainy days in those seven days. The Pearson score showed strong and moderate positive linear relationships between disease severity and climatic variables for the two periods of February and March sowing date. From the multiple linear regression model, highly significant relationships were obtained that explain the variability of the severity of Cercospora leaf spot in the crop such as: TM, HRMAX, HRM and TMAX for the February sowing date and TMAX, TM and HRM for the March sowing date, with R2 with reliability above 90% on the February sowing date and 90% on the March date depending on the climatic variables.
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Copyright (c) 2025 Brayham Jhayr Rodríguez Moreno, Leónides Castellanos González, Carmen Omaira Rozo García
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