Method for discriminating shelf life of apple through near infrared spectroscopy based on JADE and ELM

A technology of near-infrared spectroscopy and shelf life, applied in the field of infrared non-destructive testing, can solve the problems of large sample base required for modeling, long training time, time-consuming and labor-consuming acquisition of physical and chemical values ​​of samples, etc., to save manpower and material resources, and test quickly , the effect of improving the accuracy of the model

Active Publication Date: 2016-06-08
CHINA JILIANG UNIV
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Problems solved by technology

The current identification method of fruit shelf life based on near-infrared spectroscopy requires a large number of samples for modeling, a

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  • Method for discriminating shelf life of apple through near infrared spectroscopy based on JADE and ELM
  • Method for discriminating shelf life of apple through near infrared spectroscopy based on JADE and ELM

Examples

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[0023] Example

[0024] 1. Sample collection and spectrum collection

[0025] The test apples are Red Fuji apples, which are produced in Shandong Province, suitable for fresh food, but have a short shelf life and are easily damaged during storage and transportation. Choose 80 apples of medium size, similar colors and no pests, diseases and mechanical damage, and transport them to the laboratory for storage at room temperature (25°C, RH50%-60%) on the day of picking. Since the apple needs a balance process from the time of picking to room temperature, the composition changes greatly, and it is stored for two days for the first spectrum collection. After the completion of the spectrum collection, the samples were continued to be stored. Seven days later, the second spectrum collection was performed. As attached figure 2 As shown, the dotted line in the figure is the spectrum collected for the first time for a certain sample, and the solid line is the spectrum collected for the se...

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Abstract

The invention discloses a method for discriminating the shelf life of an apple through near infrared spectroscopy based on JADE and ELM. The method comprises the following steps: 1, collecting a sample, acquiring the spectrum of the sample to obtain sample near infrared diffuse reflection spectrum data, and packing the original near infrared spectrum data by using discrete wavelet transform; 2, decomposing the packed spectrum data by using a characteristic matrix joint approximate diagonalization algorithm to obtain independent component matrixes and a demixing matrix; 3, establishing an extreme learning machine analysis model by using an extreme learning machine technology with the demixing matrix as model input and corresponding shelf life as output; and 4, carrying out quality evaluation on the model, and determining the shelf life of the sample to be identified. The method has the advantages of realization of rapid identification of the shelf life of apples, enrichment of chemometrics methods, and good application prospect.

Description

technical field [0001] The invention relates to the technical field of infrared non-destructive testing, in particular to a method for identifying the shelf life of apples based on near-infrared spectrum analysis of eigenmatrix joint approximate diagonalization (JADE) and extreme learning machine (ELM). Background technique [0002] Apple is the main fruit that is abundant in northern my country. After harvesting, the activity of certain enzymes in the apple becomes stronger, the respiration rate and ethylene release rate of the fruit increase, and the reproduction of putrefactive microorganisms accelerates, resulting in a decline in quality and eventually rot and loss of commercial value. Therefore, strengthening the monitoring of the shelf life of apples during storage, transportation, and sales will help reduce the loss of fresh apples and ensure the eating quality of fresh fruits during the shelf life, improving economic benefits. [0003] Modern near-infrared spectrosco...

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Application Information

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IPC IPC(8): G01N21/359
CPCG01N21/359G01N2021/3595
Inventor 林敏焦亮刘辉军
Owner CHINA JILIANG UNIV
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