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Wheat Leaf Disease Detection Using Machine Learning Method- A Review

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.7, No. 5)

Publication Date:

Authors : ; ;

Page : 124-129

Keywords : Wheat disease detection; Machine learning; SVM (Support Vector Machine); Segmentation; clustering; classification;

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This paper is highlighting the outliers about the wheat leaf disease detection. India is the second larger producer of wheat after china. The wheat diseases are harmful to wheat production, but there are algorithms that can effectively identify common diseases of wheat leaves. The wheat diseases are generally viral, bacterial, fungal, insects, rust etc. There are many types of disease which are presents in wheat leaf. Recently, wheat disease detection through leaf image and data processing techniques are used extensively and in expensive system especially for assisting farmers in monitoring the big plantation area. Machine learning techniques are described for wheat leaf disease detection and its classification also. The key issues and challenges in wheat leaf disease detection are also highlighted. A vast collection of papers, books and standards are listed in the reference list, which gives useful information to the researchers and farmers in agriculture.

Last modified: 2018-06-01 19:33:09