Disease Detection and Quality Analysis of Fruits and Vegetables

• Main Authors: Tyagi, S., Uppal, A., Kumar, R., Sharma, S.
• Format: Article
• Published: Springer Science and Business Media Deutschland GmbH 2021
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106423457&doi=10.1007%2f978-981-15-9956-9_58&partnerID=40&md5=8084b2e0e43e13d0db0ae2aa3668aa42; http://eprints.utp.edu.my/29549/

The growing requirement for object recognition techniques which are more �robust and efficient�, is in great demand and highly researched field. Checking the quality of any fruit or vegetable is tedious task and time consuming. The diseases present in the fruits and vegetables decreases the quality and the productivity. There is more involvement of scientists, mall owners and labor to identify the defected part in vegetables and fruits. This whole process consumes a lot of time which in turn damage the rest of production and result cataclysmic for farmers. To reduce the problem, we propose a method for the same as Disease Detection and Quality Analysis of Fruits and Vegetables. Implementing this proposed method can automate quality analysis and disease detection, furthermore consuming less time which in turn can be very beneficial and make it work more efficiently. It has tremendous real-life deployments which includes usage with wide of range processes and systems. This method can be used by the industrial systems or even in the smart home systems, which has even a wider scope. The industries which can use this system are cold storage market and farming industry to analyze fruits and vegetable disease. In addition, the method is entirely powerful against other systems because of the great level of automation of disease detection, which helps the medical research domain. Execution of this application will be a new addition automated and smart procedures. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.