ISSN 2394-5125
 

Review Article 


PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW

Menaga Dhanasekaran, Sudha M.

Abstract
In the present circumstances, farmers are facing the economic challenges due to chemical
fertilizers, chemical food and pesticides. Plants are affected by the diseases due to poor protection. The study of
plant disease is known as plant pathology. The uncontrollable growth of weeds in the middle of the plants are
obstacles to farmers. The effect of plant disease and weeds results uncomfortable to environment. Air pollution,
high temperature and soil acidity are main causal agents to plant diseases. The common disease occurring in the
plants are aster yellows, bacterial wilt, blight, rice bacterial blight, canker, crown gall, rot, basal rot, scab.
Machine learning algorithms play important role to detect the disease and control the weeds such as R-CNN,
deep learning, random forest algorithm etc., some pathogens are virulent and some are non-virulent in nature.
They are transmitted and disseminated to other plants. Plant pathogens are fungal, bacterial and viral.
Researchers discover the way of detecting the disease and control the weeds by the components of agronomy
field. This paper reviews the various machine learning models, which support plant disease detection and weed
control systems. The pathogens depends on the disease are identified motivationally.`

Key words: R-CNN. Pathology. Machine Learning. Agronomy. Non-Virulent. Pathogens. Spectroscopy


 
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Pubmed Style

Menaga Dhanasekaran, Sudha M. PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. JCR. 2020; 7(19): 2178-2194. doi:10.31838/jcr.07.19.262


Web Style

Menaga Dhanasekaran, Sudha M. PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. http://www.jcreview.com/?mno=114857 [Access: July 30, 2020]. doi:10.31838/jcr.07.19.262


AMA (American Medical Association) Style

Menaga Dhanasekaran, Sudha M. PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. JCR. 2020; 7(19): 2178-2194. doi:10.31838/jcr.07.19.262



Vancouver/ICMJE Style

Menaga Dhanasekaran, Sudha M. PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. JCR. (2020), [cited July 30, 2020]; 7(19): 2178-2194. doi:10.31838/jcr.07.19.262



Harvard Style

Menaga Dhanasekaran, Sudha M (2020) PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. JCR, 7 (19), 2178-2194. doi:10.31838/jcr.07.19.262



Turabian Style

Menaga Dhanasekaran, Sudha M. 2020. PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. Journal of Critical Reviews, 7 (19), 2178-2194. doi:10.31838/jcr.07.19.262



Chicago Style

Menaga Dhanasekaran, Sudha M. "PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW." Journal of Critical Reviews 7 (2020), 2178-2194. doi:10.31838/jcr.07.19.262



MLA (The Modern Language Association) Style

Menaga Dhanasekaran, Sudha M. "PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW." Journal of Critical Reviews 7.19 (2020), 2178-2194. Print. doi:10.31838/jcr.07.19.262



APA (American Psychological Association) Style

Menaga Dhanasekaran, Sudha M (2020) PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. Journal of Critical Reviews, 7 (19), 2178-2194. doi:10.31838/jcr.07.19.262





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