Spectrum characteristic-based rapid and nondestructive detection method of watermelon maturity

A non-destructive testing and spectral characteristic technology, applied in the direction of color/spectral characteristic measurement, measuring device, genetic model, etc., can solve the problem of difficult to achieve non-destructive testing, and achieve the effect of reducing missed picking, meeting requirements, and improving the income of melon farmers.

Inactive Publication Date: 2019-11-19
FUJIAN AGRI & FORESTRY UNIV
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  • Claims
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Problems solved by technology

Traditional watermelon maturity detection methods are difficult to meet the requirements of non-destructive testing

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  • Spectrum characteristic-based rapid and nondestructive detection method of watermelon maturity
  • Spectrum characteristic-based rapid and nondestructive detection method of watermelon maturity
  • Spectrum characteristic-based rapid and nondestructive detection method of watermelon maturity

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Embodiment Construction

[0028] In order to make the features and advantages of this patent more obvious and easy to understand, the following specific examples are given together with the accompanying drawings and described in detail as follows:

[0029] Such as figure 1 As shown, the overall process of this embodiment includes the following steps: Step S1: Obtain the visible / near-infrared spectrum of the watermelon; in this step, polyurethane embedded optical fibers are placed in close contact with the watermelon, and 12 tungsten halogens are arranged around the equator of the watermelon lamp, and the visible / near-infrared spectrum is acquired by a spectrometer. In this embodiment, the integration time is 250 milliseconds. Since the different ripening stages of watermelon will affect the acquisition of the transmission spectrum, and each spectrum has 1044 data points, in order to eliminate noise or irrelevant information in the diffuse transmission spectrum, only using The spectrum between 680 and ...

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Abstract

The invention proposes a spectrum characteristic-based rapid and nondestructive detection method of watermelon maturity. The spectrum characteristic-based rapid and nondestructive detection method comprises the following steps of S1, acquiring visible/near infrared spectrum of watermelon; S2, extracting peak1 and peak2 from the obtained spectrum; S3, calculating a RPP value and/or an NDIP value, wherein RPP=peak1/peak2, and NDIP=(peak1+peak2)/(peak1-peak2); and S4, executing steps S1-S3 on a plurality of watermelon samples, training a data set of the RPP value and/or the NDIP value acquired bycalculation, and acquiring a RPP and/or NPID boundary correction factor CRPP and/or CNDIP by a genetic algorithm. By the method, the mature watermelon can be effectively identified, the ripe of the unmantured watermelon is reduced, and maximum of economic benefit is achieved.

Description

technical field [0001] The invention relates to the field of watermelon non-destructive detection, in particular to a method for rapid non-destructive detection of watermelon maturity based on spectral characteristics. Background technique [0002] The market value of watermelon will be affected by the quality of the watermelon and is closely related to the economic interests of growers and fruit merchants. Therefore, judging whether the watermelon is suitable for picking and screening out immature watermelons will help improve the quality of the commodity. However, the ripeness of watermelon is an internal quality that cannot be observed from the outside, and usually can only be judged by cutting the watermelon. Because watermelons are often harvested on a large scale by recording the elapsed time after the watermelon blooms and judging the experience of the fruit grower, but the watermelon is in the same melon field, the watermelon will be affected by many different factor...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/31G01N21/359G06N3/12
CPCG01N21/314G01N21/359G01N2021/3155G06N3/126
Inventor 介邓飞吴爽魏萱叶大鹏
Owner FUJIAN AGRI & FORESTRY UNIV
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