Near-infrared spectrum sugar degree detection method and system based on BP artificial neural network

An artificial neural network and near-infrared spectroscopy technology, applied in neural learning methods, biological neural network models, measuring devices, etc., can solve the problems of low detection signal-to-noise ratio and difficult analysis, and achieve filtering noise and reducing input factor personalities Number, eliminate the effect of baseline drift

Inactive Publication Date: 2019-03-29
UNIV OF JINAN
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Problems solved by technology

[0005] The detection process of near-infrared spectroscopy has the characteristics of saving time and simplicity, no need to destroy and waste samples, fast analysis speed, low cost, and good reproducibility of results. It is a fast, convenient and non-destructive detection method; Quantitative analysis, low detection signal-to-noise ratio, etc.

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  • Near-infrared spectrum sugar degree detection method and system based on BP artificial neural network
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  • Near-infrared spectrum sugar degree detection method and system based on BP artificial neural network

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[0042] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0043] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0044] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinati...

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Abstract

The invention provides a near infrared spectrum sugar degree detection method and system based on a BP artificial neural network; certain fruits of the same kind are selected to form a sample set, a modeling sample is selected, and the sample set is randomly divided into a correction set and a prediction set; original near infrared spectrums of all the correction sets and the prediction set samples are collected, equal interval division is carried out on the spectrums, and the absorbance of each interval is summed respectively; the content of the sugar degree in the sample is measured by usinga chemical analysis method; a near-infrared spectrum quantitative analysis model is established; a BP neural network is used for constructing a quantitative correction model between the sugar degreecontent of the correction set sample and the near-infrared characteristic spectrum; the near-infrared quantitative analysis model is used for determining the sugar degree content of the prediction setsample, the near-infrared spectrum information data of the prediction set sample is input into the correction model to obtain the sugar degree content of the prediction set sample.

Description

technical field [0001] The disclosure relates to a near-infrared spectrum sugar content detection method and system based on a BP artificial neural network. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] With the continuous improvement of people's living standards, consumers are not limited to external qualities such as size, color, and appearance for fresh fruits, but pay more attention to related internal qualities such as sugar content. Therefore, under the new situation, it is imperative to enhance the market competitiveness of the fruit industry. While vigorously promoting fine varieties and adopting high-quality, high-yield and high-efficiency cultivation techniques, producers should pay more attention to post-harvest commercialization, establish a sound apple quality control system, and comprehensively improve apple quality, safe...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/359G06N3/08
CPCG01N21/359G06N3/084
Inventor 申涛李晓旭毕淑慧赵钦君韩春艳闫雪华徐元
Owner UNIV OF JINAN
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