Fruit maturity degree evaluation method based on spectrum and color measurement

A technology for color measurement and maturity, applied in the direction of color/spectral characteristic measurement, etc., to achieve accurate prediction, good consistency of results, and accurate fruit maturity

Active Publication Date: 2012-12-12
BEIJING RES CENT OF INTELLIGENT EQUIP FOR AGRI
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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

Method used

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  • Fruit maturity degree evaluation method based on spectrum and color measurement
  • Fruit maturity degree evaluation method based on spectrum and color measurement
  • Fruit maturity degree evaluation method based on spectrum and color measurement

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Embodiment

[0023] Such as figure 1 As shown, first pick apple samples at different maturity stages, and evaluate the apples at different maturity stages corresponding to four maturity levels according to the national testing standard GB10651-2008, namely immature, harvestable maturity, edible maturity, and physiological maturity Four grades; use these apples as standard samples to establish a standard sample set; according to the spectral response characteristics of apples, set the integration time of spectral scanning to 50 milliseconds, the average number of times to 10, the smoothness to 5, and the wavelength range of 400-1100nm. The optical path is 2mm, and the fiber optic probe is equipped with a length-tunable shading rubber sleeve for shading, storing dark spectra and reference spectra, and collecting visible and near-infrared spectra of fruit samples at the equator of the fruit; the visible-near-infrared spectrometer is a miniature optical fiber spectrometer with a built-in CCD ar...

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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 ...

Claims

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Application Information

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IPC IPC(8): G01N21/25
Inventor 陈立平郭志明黄文倩郭建华王秀张驰
Owner BEIJING RES CENT OF INTELLIGENT EQUIP FOR AGRI
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