The potential of automatic methods of classification to identify leaf diseases from multispectral images

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Current and future applications of statistical machine learning algorithms for agricultural machine vision systems (2019, methodology): “Bauer et al. (2011) differentiated infected (leaf spot pathogen and rust fungus) and healthy leaves of sugar beet by using multispectral (700–950 nm) and colour cameras.”
Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features (2013, background): “Automatic classification of leaf diseases is done based on high resolution multispectral and stereo images (Bauer et al., 2011).”
Plant disease recognition based on plant leaf image. (2015, background): “There are many leaf based plant disease recognition methods (Sabine Bauer et al., 2011; Al-Bashishet al., 2011; Al-Hiaryet al.,2011; Dheebet al., 2010; Arivazhaganet al., 2013).”
A Survey of Deep Convolutional Neural Networks Applied for Prediction of Plant Leaf Diseases (2021, methodology): “Artificial Neural Network (ANN) [4], Support Vector Machine (SVM) [5], Bayes classifier [6], Random Forests [7], K-Nearest Neighbor (KNN) [8], etc.”