Fruit commercialization is adopting the scientific method and detecting, grading,
packaging the fruits on the basis of comprehending the physiology metabolism law,
protecting and improving the quality, and achieving the change from the elementary
raw material to high added-value commodity. Nowadays, reducing the consumption
of post-harvest fruit is the most concerned question for the world agricultural trade. It
was reported that the consumption of post-harvest fruit in developed countries accounted for the 15-20% of the total amount. China is the world’s largest fruits and vegetable production country. The breeding, culturing, and pest control was paid
much attention, however, the post-harvest processing technology was neglected, the
question of detecting, grading, transporting, preservation was not solved, so the lost of
post-harvest fruits and vegetables in circulation was huge, the loss ratio was
30%~40% every year.
With the rapid development of science and technology and computer vision technique
to the development of agricultural field, new methods of non-destructive detection for
fruit quality were provided. The main methods included optical properties, sonic vibration, nuclear magnetic resonance (NMR), machine vision technique, electrical properties detection, computed tomography and electronic noses technique and so on.
In recent years, fruits (of any variety) has become one of the most dependable organic product produced by farmers across the world; this lived much to its expectation as it serves not only for direct consumption, but also as a raw material for other products. Organic products grading and sorting is a vital procedure for producers, which influences the natural products quality assessment and export market. Despite the fact that the grading and sorting can be and has always been done by human, it is slow, tedious and prone to error, hence the need to evolve a smart fruit grading and sorting machine system. Researchers, at various level had come up with various designs with different algorithms for fruit grading by utilizing textural and morphological elements to distinguish the healthy fruits from the defected ones. Subsequently, these features, otherwise known as optical sorting, is the automated process of sorting solid products using sensors. Such sensors utilize product driven knowledge of the picture preparing system, by detecting the colour of fruits, shape and other auxiliary properties. The sensor (sorter) compares fruits based on client’s characterized acknowledgment to distinguish, sort and expel defected fruits and other foreign material from the creation line or to isolate result of various evaluations.