AIMC Topic: Puccinia

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Predicting crop disease severity using real time weather variability through machine learning algorithms.

Scientific reports
Integrating disease severity with real-time meteorological variables and advanced machine learning techniques has provided valuable predictive insights for assessing disease severity in wheat. This study emphasizes the potential of machine learning m...

Prediction of barberry witches' broom rust disease using artificial intelligence models: a case study in South Khorasan, Iran.

Scientific reports
The South Khorasan Province in Iran is the main producer of seedless barberry, accounting for 98% of the country's production. This has led to significant economic growth in the region. However, the cultivation of barberry is threatened by the rust f...

Application of a U-Net Neural Network to the Maize Pathosystem.

Phytopathology
Computer vision approaches to analyze plant disease data can be both faster and more reliable than traditional, manual methods. However, the requirement of manually annotating training data for the majority of machine learning applications can presen...