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Cotton is a monoculture crop planted on 2.5% of agricultural land. Cotton is drought-resistant and gives farmers in climate-change-prone areas a steady income. These cotton crops are plagued by bacterial, fungal, viral, and parasite illnesses that vary depending on the climate, resulting in poor yield. The leaf is particularly susceptible to diseases, causing plant and agricultural loss. Cotton plant leaf diseases predominate. Traditional disease detection has long been used to identify plant illnesses early for greater productivity. In this Paper author will elaborate for knowing and using numerous image processing and machine learning algorithms helps identify cotton leaf diseases.
Neetu et al. (Fri,) studied this question.
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