Skip to content

Latest commit

 

History

History
18 lines (11 loc) · 2.9 KB

README.md

File metadata and controls

18 lines (11 loc) · 2.9 KB

DISEASE INFESTED CROP IDENTIFICATION USING DEEP LEARNING AND SUGGESTION OF SOLUTION.

ABSTRACT

India is an agricultural country. A large amount of its population resides in villages and depends on cultivation of crops as its primary source of livelihood. The outcome of crop cultivation and its yield depends on a number of factors such as - quality of soil, use of pesticides, herbicides, crop intensifiers , etc. Farmers face issues when dealing with a disease infested crop due to lack of expertise.The usual way to detect infested crops is using the naked eye or examination by an expert. This process, while being time consuming, further leads to the overuse of pesticides, insecticides and crop intensifiers in greed of a greater yield. The quality of the soil also suffers due to this abuse of pesticide usage. This paper is a reflection of development towards disease infested crop detection. The approach based on disease classification of crops , by the use of deep learning and convolutional neural networks. Computer Vision techniques present an opportunity to enhance and improve disease detection capabilities. A proposed rule based approach finds use in the suggestion model used for pesticides, insecticides.

General Terms

Computer Vision, Deep Learning, Convolutional Neural Networks

Keywords

Computer Vision, Deep Learning, Convolutional Neural Networks, Infested crops, Image Processing

1.INTRODUCTION

Sustainable agriculture greatly depends on the ability of crops to fight pathogens and diseases without the use of chemical pesticides. However, the present approach towards having pest free crops and a greater yield largely depends on the excessive use of pesticides. Timely diagnosis of crop infestation has higher importance due the value it brings to farmer. Early diagnosis helps with financial aid as well as avoids redundant use of pesticides. Visual examination of a crop by a trained professional is the prime technique adopted in practice for plant disease detection. An expert with good knowledge and observation skills is thus needed. This process of disease identification is dependent on the availability of a skilled expert. There is room for error in this process. It is also time consuming. An automated system designed to help identify crop diseases by the crop’s type , its appearance and visual symptoms. Computer Vision techniques present an opportunity to enhance and improve disease detection capabilities. A proposed rule based approach finds use in the suggestion model used for pesticides, insecticides.

2.BACKGROUND AND MOTIVATION

Indian farmers spray a deadly cocktail of pesticides because government lacks staff to guide them.The government’s farm extension system is crumbling. Private companies have stepped into the vacuum but they have commercial interests in overselling pesticides.This degrades the quality of crop produced and affects population health at large.