A Systematic Review of Citrus Disease Perceptions and Fruit Grading Using Machine Vision

Abstract

Citrus is one of the most commonly farmed and popular fruit crops globally. Citrus fruits are high in vitamins, minerals, and dietary fibre, which are essential for overall health. Oranges are the most widely traded citrus fruit, accounting for more than half of global citrus production. Tangerines, lemons, and mandarins are the next most commonly farmed varieties. Citrus production and export have steadily expanded over the previous three decades, though slower than competing items like mangoes, avocados, and melons. The production of citrus fruit is heavily hampered due to diseases in its growth stages. Again, the diseases not only appear in leaves but also in fruits. So, the quality of fruits is degraded due to the appearance of flaws. The citrus fruits are graded in two ways: first based on their skin tone and second on their size. So, there is a requirement to assess citrus diseases to avoid the degradation of production. Further, there is a need to grade citrus fruit to make easy packaging concerning its quality; so that the proper values of Citrus fruits be generated. This article studied and analysed different methodologies reported for citrus disease prediction and grading of citrus fruit in the postharvest stage based on machine vision between 2010 and 2021. This paper outlines the current achievements, limitations, and suggestions for future research on citrus diseases and their fruit grading.