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- W3084300249 abstract "In the present circumstances, farmers are facing the economic challenges due to chemicalfertilizers, chemical food and pesticides. Plants are affected by the diseases due to poor protection. The study ofplant disease is known as plant pathology. The uncontrollable growth of weeds in the middle of the plants areobstacles 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 theplants 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 agronomyfield. This paper reviews the various machine learning models, which support plant disease detection and weedcontrol systems. The pathogens depends on the disease are identified motivationally.`" @default.
- W3084300249 created "2020-09-14" @default.
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- W3084300249 date "2020-01-01" @default.
- W3084300249 modified "2023-09-23" @default.
- W3084300249 title "PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW" @default.
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