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<p>Late blight caused by <i>Phytophthora infestans</i>, poses a significant threat to potato cultivation globally. In A Limia region located in the North-West of Spain, climatic conditions are favorable for late blight development, but disease-forecasting systems are absent, resulting in excessive use of fungicides each growing season. The present study aimed to predict the onset of late blight infections in the&#xa0;potato crop by analyzing weather factors, airborne <i>P. infestans</i>,&#xa0;and the resistance of potato cultivars to late blight over three growing seasons. The study assessed the accuracy of existing weather-based models (Indice Potenziale Infettivo [IPI], Infection Pressure [IP], and hours of risk of sporulation [HOSPO90]) and developed a new model, combining aerobiological and weather data for predicting late blight occurrence. Notably, the&#xa0;2022 growing season displayed lower sporangia concentrations and late blight severity below 5% across all cultivars. Cluster analysis based on different epidemiological parameters highlighted that the growing season significantly influenced the epidemic response. The weather-based models predicted an Aerobiological Risk Period [ARP], which defines the period with significant sporangial levels to initiate infection. Some risk periods according to ARP were identified by the IPI and HOSPO90 models. Furthermore, increased sporangia concentrations were observed before the onset of first symptoms in all potato cultivars. A logarithmic aerobiological-based model was subsequently developed to predict the timing of 5% severity with 92% accuracy. This approach enhances late blight outbreak predictions by integrating aerobiological metrics into disease management strategies, reducing unnecessary fungicide application and fostering more sustainable agricultural practices.</p>

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Innovative Approaches in Potato Late Blight Management: Forecast Models Supported by Meteorological and Aerobiological Data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月11日

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  • Laura Meno,
  • Olga Escuredo,
  • M. Carmen Seijo,
  • Jon Castaño-Serna,
  • Isaac K. Abuley

摘要

Late blight caused by Phytophthora infestans, poses a significant threat to potato cultivation globally. In A Limia region located in the North-West of Spain, climatic conditions are favorable for late blight development, but disease-forecasting systems are absent, resulting in excessive use of fungicides each growing season. The present study aimed to predict the onset of late blight infections in the potato crop by analyzing weather factors, airborne P. infestans, and the resistance of potato cultivars to late blight over three growing seasons. The study assessed the accuracy of existing weather-based models (Indice Potenziale Infettivo [IPI], Infection Pressure [IP], and hours of risk of sporulation [HOSPO90]) and developed a new model, combining aerobiological and weather data for predicting late blight occurrence. Notably, the 2022 growing season displayed lower sporangia concentrations and late blight severity below 5% across all cultivars. Cluster analysis based on different epidemiological parameters highlighted that the growing season significantly influenced the epidemic response. The weather-based models predicted an Aerobiological Risk Period [ARP], which defines the period with significant sporangial levels to initiate infection. Some risk periods according to ARP were identified by the IPI and HOSPO90 models. Furthermore, increased sporangia concentrations were observed before the onset of first symptoms in all potato cultivars. A logarithmic aerobiological-based model was subsequently developed to predict the timing of 5% severity with 92% accuracy. This approach enhances late blight outbreak predictions by integrating aerobiological metrics into disease management strategies, reducing unnecessary fungicide application and fostering more sustainable agricultural practices.