Fruit maturity degree evaluation method based on spectrum and color measurement

Abstract

The invention relates to a fruit maturity degree evaluation method based on spectrum and color measurement. The method comprises the following steps that (1) the degrade division is carried out on a certain fruit, and the color measurement parameter, the visible near infrared spectroscopy and the internal quality evaluation index of each grade of fruit are determined; (2) firstly, the visible near infrared spectroscopy and the internal quality evaluation index are combined, a fruit internal quality quantitative analysis model is built by adopting a multivariate calibration method, then, the color measurement parameter is fused, the fruit maturity degree degrade is used as the standard reference, and a fruit maturity degree evaluation model is built by using a machine learning method; and (3) the visible near infrared spectroscopy and the color measurement parameter of fruit samples to be evaluated are determined and are respectively input into the fruit internal quality quantitative analysis model and the fruit maturity degree evaluation model, and a computer carries out intelligent degrade evaluation on the fruit maturity degree. The fruit maturity degree evaluation method is simple, the fruit damage is avoided, and accuracy and high efficiency are realized.

Description

technical field [0001] The invention relates to an intelligent evaluation method of fruit maturity, in particular to an evaluation method of fruit maturity based on spectrum and color measurement. Background technique [0002] Fruit maturity is an important indicator for fruit grading, preservation and storage, and it is also the main basis for consumers to choose and buy. Harvesting maturity has a great influence on the storage effect. If harvesting is too early, the fruit has not yet fully developed, the fruit is small, insufficient sugar accumulation, poor color, and lacks due flavor; if harvesting is too late, the fruit is over-ripe, and the flesh is soft and tender. Hardness is not enough, not resistant to storage. At present, in the fruit harvesting process, the traditional method of determining the ripening period and the best harvesting period of the fruit is based on experience and visual judgment, which can only be judged manually from the appearance. Influenced ...

AI Technical Summary

Problems solved by technology

Domestic and foreign research reports on the method of detecting the internal quality of fruits (sugar content, acidity, hardness and VC content, etc.) by near-infrared spectroscopy, and comprehensively predicting the maturity of various quality indicators has not been reported at home and abroad.

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