Quality Evaluation in Guavas using Deep Learning Architectures: An Experimental Review

Determining the quality of fruit can be very challenging without the proper understanding. There are many factors that can result in determining the quality and therefore the actual taste of any given fruit. In this paper we attempt to determine the quality of the guava fruit on what are considered the three most important aspects of flavour by experts, those being, Colour, Shape and texture. All three of these aspects will be determined on a scale of 1–5. In order to produce these results, we are using an exceptional deep learning architecture and a primary dataset curated by a panel of experts who photographed the fruits in six-hour intervals for many days. We have compared the results over multiple deep learning architectures to find the most accurate results. This paper shows the importance of deep learning as a potential future tool for assessing the quality of fruits.