Early diagnostics of macronutrient deficiencies in three legume species by color image analysis

By M. Wiwart, G. Fordoński, K. Żuk-Gołaszewska, E. Suchowilska. 2009

118 citations recorded by the source corpus.

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Detection of potato diseases using image segmentation and multiclass support vector machine (2017, background): “in [7] aimed to detect and discriminate among four types of mineral deficiencies (nitrogen, phosphorus, potassium and magnesium).”
A review on the main challenges in automatic plant disease identification based on visible range images (2016, background): “Wiwart et al. (2009) reported significant similarities in the visible characteristics of different nutritional deficiencies, and that those similarities vary according to the plant species.”
Digital image processing techniques for detecting, quantifying and classifying plant diseases (2013, methodology): “The method proposed by Wiwart et al. (2009) aims to detect and discriminate among four types of mineral deficiencies (nitrogen, phosphorus, potassium and magnesium).”
Plants Disease Identification and Classification Through Leaf Images: A Survey (2018, methodology): “HSI (I for intensity), another similar color space is also used [1, 49–52].”