A Novel Technique to Detect Plant Disease

Authors

  • Diksha Kumar Head, Department of Information Technology, Kharghar, Navi
  • Sagrika Lale Student, Department of Information Technology, Saraswati College of Engineering, Kharghar, Navi Mumbai, Maharashtra, India
  • Nikita Baranwal Student, Department of Information Technology, Saraswati College of Engineering, Kharghar, Navi Mumbai, Maharashtra, India
  • Sanjivani Sathe Student, Department of Information Technology, Saraswati College of Engineering, Kharghar, Navi Mumbai, Maharashtra, India

Abstract

One of the important sectors of Indian Economy is Agriculture. Employment to almost 50% of the countries workforce is provided by Indian agriculture sector. India is known to be the world’s largest producer of pulses, rice, wheat, spices and spice products. Therefore, in field of agriculture, detection of disease in plants plays an instrumental role. Plants are highly prone to diseases that affect the growth of the plant, which in turn affects the ecology of the farmer. In order to detect a plant disease at initial stage, use of automatic disease detection technique is advantageous. The symptoms of plant diseases are conspicuous in different parts of a plant such as leaves, stem, flowers, buds, etc. Manual detection of plant disease using plant components is a tedious job.

Keywords: CNN, Image Processing, Diseased and Healthy leaf, Random forest, Feature extraction, Training, Classification.

Cite this Article: Sagrika Lale, Nikita Baranwal, Sanjivani Sathe, Diksha Kumar. A Novel Technique to Detect Plant Disease. Journal of Artificial Intelligence Research & Advances. 2020; 7(2): 10–16p.

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Published

2020-08-06

Issue

Vol. 7 No. 2 (2020)

Section

Research Articles

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