Influence of Daily Temperature and Relative Humidity Duration on Lesion Development of Black Leaf Mold ( <i>Pseudocercospora fuligena</i> ) in Greenhouse-Grown Tomato

The impact of duration of daily temperature and relative humidity (RH) on symptom development and leaf infection by the black leaf mold pathogen Pseudocercospora fuligena was studied on greenhouse-grown tomato over the 4-year period from 2019 to 2022. The duration was expressed as the number of hours during the daytime, nighttime, or the whole day (i.e., 24-h period) at a temperature or RH that exceeded a given threshold. Temperature thresholds were in 2°C increments between 18 and 34°C, and RH thresholds were in 10% increments between 50 and 90%. Infection severity was estimated by the number of lesions per leaf that developed each day after an incubation period that was assumed to be between 10 and 16 days, based on previous studies. Daytime, nighttime, and whole-day temperatures showed weak to moderate negative correlations with infection severity, and nighttime RH had a weak positive correlation ( P &lt; 0.005). Multiple regression detected no significant interaction between temperature and RH conditions, and the model reliability was insufficient to predict favorable conditions for infection ( R 2 ≤ 0.3106). Two-dimensional scatterplots, however, indicated the duration of conditions that were unfavorable for infection, such as &gt;9.6 h at ≥30°C or &gt;7.4 h at ≥32°C. Thus, a greenhouse environment that incorporates high temperatures discourages infection of tomato plants by P. fuligena, and the whole-day temperature and nighttime RH conditions affect the seasonal variation in disease incidence. The merit of our findings for knowledge-based feature engineering in machine learning to develop models for forecasting black leaf mold disease incidence is discussed. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

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Journal
PhytoFrontiers™
Published
2024-12-19
DOI
https://doi.org/10.1094/phytofr-02-24-0007-r
Citations
1
Primary Topic
Plant Pathogens and Fungal Diseases
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article
Field-Weighted Citation Impact
0.33

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article

Influence of Daily Temperature and Relative Humidity Duration on Lesion Development of Black Leaf Mold ( Pseudocercospora fuligena ) in Greenhouse-Grown Tomato

Sachiko Shimizu, H. Furuya, Hitoshi Kamijima
1 citations
PhytoFrontiers™
Plant Pathogens and Fungal Diseases
0.33
article

Influence of Daily Temperature and Relative Humidity Duration on Lesion Development of Black Leaf Mold ( Pseudocercospora fuligena ) in Greenhouse-Grown Tomato

Sachiko Shimizu, H. Furuya, Hitoshi Kamijima
article en
1 citations

Abstract

The impact of duration of daily temperature and relative humidity (RH) on symptom development and leaf infection by the black leaf mold pathogen Pseudocercospora fuligena was studied on greenhouse-grown tomato over the 4-year period from 2019 to 2022. The duration was expressed as the number of hours during the daytime, nighttime, or the whole day (i.e., 24-h period) at a temperature or RH that exceeded a given threshold. Temperature thresholds were in 2°C increments between 18 and 34°C, and RH thresholds were in 10% increments between 50 and 90%. Infection severity was estimated by the number of lesions per leaf that developed each day after an incubation period that was assumed to be between 10 and 16 days, based on previous studies. Daytime, nighttime, and whole-day temperatures showed weak to moderate negative correlations with infection severity, and nighttime RH had a weak positive correlation ( P &lt; 0.005). Multiple regression detected no significant interaction between temperature and RH conditions, and the model reliability was insufficient to predict favorable conditions for infection ( R 2 ≤ 0.3106). Two-dimensional scatterplots, however, indicated the duration of conditions that were unfavorable for infection, such as &gt;9.6 h at ≥30°C or &gt;7.4 h at ≥32°C. Thus, a greenhouse environment that incorporates high temperatures discourages infection of tomato plants by P. fuligena, and the whole-day temperature and nighttime RH conditions affect the seasonal variation in disease incidence. The merit of our findings for knowledge-based feature engineering in machine learning to develop models for forecasting black leaf mold disease incidence is discussed. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

PhytoFrontiers™Vol. 5(1)
Hiroshima Institute of Technology (JP), Hiroshima Prefectural Rehabilitation Center (JP), Nippon Kayaku (Japan) (JP), Akita Prefectural University (JP)
Bayer CropScience, Bio-oriented Technology Research Advancement Institution
Openalex Percentile: Top 38%
Plant Pathogens and Fungal Diseases
0.33
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