Non-destructive detection method for quickly detecting inner quality of apple

Abstract

The invention discloses a rapid loss-free internal apple quality detecting method, which comprises the following steps: (1) proceeding continual spectrum detecting of each apple through visible-near-infrared spectrometer ranged from 638 to 1295 nm; (2) putting the apple detecting result in the quality discrimination function to judge the apple internal quality; detecting water-core ill and browning ill simultaneously in two discrimination functions through gathering once apple continual spectrum. The invention reduces the waste of sampling apple, which can detect and monitor the stored apple to reduce the storage loss.

Description

technical field [0001] The invention relates to a method for detecting the internal quality of apples, in particular to a method for rapidly and non-destructively detecting the internal quality of apples aimed at water core disease and browning of apples. Background technique [0002] my country is the world's largest producer of fruit, among which apple is the most important variety, but the annual export volume is small, accounting for only 2.1% of the total output. One of the important reasons restricting the export of apples in my country is that the domestic ability of sorting and testing apples is weak, the speed is slow, the test environment is poor, and the level of sorting technology cannot meet the requirements of the international market. Apple water-core disease is an internal physiological disorder that often occurs during the growth period and storage period. It occurs in various apple producing areas in my country. The fruit core of water-core diseased fruit i...

AI Technical Summary

Problems solved by technology

However, this density detection method can only separate apples with qualified quality and serious water-centered fruits (4 grades), but cannot separate apples of adjacent grades.

(2) Light transmission image density method: According to the report of Throop, use a visual computer to detect the light transmittance of apples, and estimate the area and calculate the density according to the apple image to judge the water core of apples, although this method can correctly separate 75% of the water. Heart disease fruit, but not enough to accurately distinguish the severity of water core disease, because the density difference between disease fruit levels is small; and further research by Upchurch and Throop found that the detection effect is related to the camera sensitivity of the computer vision system

(4) Nuclear magnetic resonance method: Clark and Bieleski reported that nuclear magnetic resonance imaging can be used to track the changes of water core in apples during storage, but the cost of this technology is too high and the detection speed is slow, so it cannot be applied to the apple sorting line

(5) Difference method: The classic optical water core detection method is the difference method of 760nm and 810nm, and the detection accuracy is still not ideal

In addition, Bramlage explored the possibility of using optical methods to detect intact apples; while Paola et al. used time-resolved reflection spectroscopy to detect the brown heart of pears without damage, but they could only detect the 2 cm below the peel. Slight browning is difficult to detect

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