In today’s consumer lifestyle, food habits have become an important part to dictate health of the individuals. Natural food like fruits and vegetables supplement most of the need for this healthy lifestyle; however the consumer does not often have access to the right quality of fruits and/or vegetables. Apart from increasing the shelf life, identifying the right time to harvest fruits depending on their maturity helps fruit marketability with better taste levels of the fruit. Current methods of grading fruits based on maturity are mostly by visual inspection of physical characteristics like colour, size and shape and using traditional image processing methods for classification. This proposed study is aimed at analysing multiple significant maturity indices like colour, ultra-structural changes in texture of the fruit to measure precisely the shelf life, optimum harvest time and develop a framework based on deep learning techniques for feature extraction and classification of fruits. Low cost standalone farm management solutions can be built using this concept that will help multiple stakeholders in the fruit supply chain in improved quality control, grading and classification of fruits.
Volume 11 | 06-Special Issue
Pages: 1444-1449