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<p>This study examines the temperature requirements for conidial germination of <i>Alternaria brassicae</i> (Berk.) Sacc., a major leaf spot pathogen affecting cabbage in Greece. The primary objective was to identify the minimum, optimum and maximum temperatures for conidial germination under constant temperature conditions. Our results showed that the optimum temperature for conidial germination was 23&#xa0;°C, with germination inhibited at both high (35&#xa0;°C) and low (4&#xa0;°C) temperatures. Conidia began germinating after 9&#xa0;h at 23&#xa0;°C. Additionally, we evaluated the accuracy of a forecasting model for predicting <i>Alternaria</i> leaf spot on cabbage by examining the relationship between conidial germination (influenced by temperature and time after wet conditions) and disease progression in the field. We developed and compared the performance of a Linear Mixed-Effects model with non-linear growth models, including logistic, Richards and Gompertz models. The logistic model consistently outperformed the others in most scenarios. The logistic forecast model accurately predicted infection periods and correlated well with disease onset, severity, and symptom progression, particularly in untreated plants. These findings suggest that incorporating temperature thresholds (such as the optimal 23&#xa0;°C and inhibitory points) into the forecast model can effectively predict outbreaks. This predictive approach can assist cabbage growers in Greece and regions with similar climates in optimizing fungicide applications, reducing unnecessary treatments and improving overall crop protection.</p>

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Development and validation of multivariate mixed-effects linear and nonlinear models for forecasting Alternaria black spot of cabbage

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月7日

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  • Ioanna Prodromou,
  • Thomas Thomidis,
  • Petros Damos,
  • Aggelos Patakas

摘要

This study examines the temperature requirements for conidial germination of Alternaria brassicae (Berk.) Sacc., a major leaf spot pathogen affecting cabbage in Greece. The primary objective was to identify the minimum, optimum and maximum temperatures for conidial germination under constant temperature conditions. Our results showed that the optimum temperature for conidial germination was 23 °C, with germination inhibited at both high (35 °C) and low (4 °C) temperatures. Conidia began germinating after 9 h at 23 °C. Additionally, we evaluated the accuracy of a forecasting model for predicting Alternaria leaf spot on cabbage by examining the relationship between conidial germination (influenced by temperature and time after wet conditions) and disease progression in the field. We developed and compared the performance of a Linear Mixed-Effects model with non-linear growth models, including logistic, Richards and Gompertz models. The logistic model consistently outperformed the others in most scenarios. The logistic forecast model accurately predicted infection periods and correlated well with disease onset, severity, and symptom progression, particularly in untreated plants. These findings suggest that incorporating temperature thresholds (such as the optimal 23 °C and inhibitory points) into the forecast model can effectively predict outbreaks. This predictive approach can assist cabbage growers in Greece and regions with similar climates in optimizing fungicide applications, reducing unnecessary treatments and improving overall crop protection.