Leaf Disease Detection of SoyBean Plant using Machine Learning Algorithms
M.Sowmiya1, C. Thilagavathi2
1Mrs.M.Sowmiya*, Assistant Professor, Department of IT, M. Kumarasamy College of Engineering, Karur.
2Mrs.C.Thilagavathi, Assistant Professor, Department of IT, M. Kumarasamy College of Engineering, Karur.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 1215-1217 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8630019320/2020©BEIESP | DOI: 10.35940/ijitee.C8630.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nature is an important phenomenon of this physical world. This nature includes plants, trees, animal, humans and several other organisms. Amongst them plants are the most important organisms in the world. They are specialist of creating their food by themselves and also they are the notable components in food chain. They also serve the nature and its organisms in a tremendous way. Hence it is necessary to protect our nature in an efficient manner so as to maintain the food chain. Our technology development has given much advancement in the field of agriculture. This paper deals with the analysis of various machine learning algorithms, by applying the algorithms on the plant data set. Sample sizes of collected data set are used to train the algorithm and the results are evaluated accordingly to estimate the better implementation of machine learning algorithm.
Keywords: Machine Learning, Leaf Disease Detection, SVM
Scope of the Article: Machine Learning