Review of Identifying and preventing cotton diseases

This India, with its vast agricultural sector, is a significant player in global crop production, particularly in cotton cultivation. Despite its extensive cultivation area of approximately 350,000 hectares and a production volume of around 5.3 million tons, the sector faces substantial )challenges due to crop diseases and insect pests. Blights, affecting 10-30% of the total crop, are a major concern, necessitating accurate and efficient identification methods to prevent significant yield losses. Cotton, often referred to as “white gold,” is economically vital, with its global trade value projected to rise from 40 billion to 60 billion US dollars by 2030. However, diseases affecting cotton leaves have reduced production by about 25% in India. Insect pests such as Aphis gossypii, Thrips, and Cotton Bollworm further exacerbate the problem, causing significant damage and necessitating effective pest management strategies. This review highlights the importance of developing advanced monitoring and prediction systems to mitigate these challenges and enhance cotton production sustainability.

Keywords—IPPS(Insect pest Predict System), SVM( Support Vectot Machine ), MLP( Multilayer Perceptron ) KNN (K-Nearest neighbor  )Cotton