Statistical model based on climatological variables for the prediction of pest and disease incidence in rose (Rosa spp.) crops

Abstract

In Colombia, floriculture is a very important section of the economy since it provides income to the country. Within this sector is the cultivation of roses (Rosa spp.), whose production and quality are affected by the presence of various pests and diseases. Among these pests are thrips Frankliniella occidentalis and mites Tetranychus urticae, and among the diseases are downy mildew Peronospora sparsa, powdery mildew Podosphaera pannosa and botrytis Botrytis cinerea. This problem generates large expenses in the purchase of agrochemical products for their control and management. This study analyzes the incidence of various pests and diseases in rose cultivation as a function of climatological variables (evaporation, temperature, relative humidity, and precipitation) in order to predict a future affectation. The analysis was carried out with R as programming language for the calculation of a multiple linear regression model. The results showed satisfactory prediction for the percentage incidence of each of the pests and diseases, since the difference between the predicted values and the values obtained by monitoring did not exceed 5% for the downy mildew, botrytis, mites, and thrips and 10% for the powdery mildew. The tool presented shows appropriate prediction for the possible behavior of the pests and diseases, and, thus, provides the opportunity to counteract their damage and estimate the investment required for their control. In this study, only the percentage incidence data of each of the pests and/or diseases was considered, as well as the value of the response variables in percentage incidence.