Method for establishing peach fruit maturation degree prediction model

Abstract

The invention discloses a method for establishing a peach fruit maturation degree prediction model. The method comprises the following steps: respectively picking peach fruits in a turning-color period and fruits reaching the picking maturation degree, and respectively marking as a maturation degree I and a maturation degree II; measuring the peel absorbance difference IAD of the picked peach fruits, and measuring hardness of the peach fruits; and fitting the hardness of the fruits with the maturation degree I and the maturation degree II with the IAD, and establishing a peach fruit maturation degree prediction equation y=ax2+bx+c. According to the method disclosed by the invention, the peach fruit maturation degree prediction model is established based on the peel absorbance difference IAD which is nondestructively tested by a near infrared technology, and due to regression prediction, the difference between an estimated value and an actual observed value is not obvious. Therefore, the prediction model has high accuracy, the measurement and calculation method is simple, and the peach fruits can be timely picked.

Description

technical field [0001] The invention relates to a method for establishing a peach fruit maturity prediction model. Background technique [0002] In peach market circulation, fruit harvest maturity is always the main factor restricting its commodity value. Accurate judgment of peach fruit maturity is very important for timely harvesting, grading, packaging, transportation, and guarantee of commerciality. As a climacteric fruit, peach has a sharp rise in ethylene release during ripening, accompanied by gene transcription, and these changes are often regulated by hormones. During this process, the firmness of the fruit, the content and proportion of inclusion components, and the background color of the peel will all change accordingly, and the relevant quality indicators of fruits with different maturity levels are significantly different. There have been many studies on the detection of peach fruit maturity based on destructive or non-destructive methods. Zhang Binbin et al...

AI Technical Summary

Problems solved by technology

In the aspect of predicting peach fruit ripeness by near-infrared spectroscopy, Nascimento et al. studied the least squares model of short-term low-temperature peach soluble solids content and fruit firmness, and established prediction models for soluble solids content and fruit firmness respectively, but at the same time It is also pointed out that the model still needs to be optimized

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