Raman hyperspectral grading method for single-grain corn starch content

Abstract

The invention relates to the technical field of grain seed grading and screening, and discloses a single-grain corn starch content Raman hyperspectral classification method, comprising: embryonic surface Raman hyperspectral images and non-embryonic Raman hyperspectral images based on single-grain corn samples , establish the double-surface standard Raman spectral curve of single-grain corn samples; obtain the physicochemical value of starch content of single-grain corn samples based on optical polarimetry; establish the double-surface standard Raman spectral curve of single-grain corn samples and the physicochemical values ​​of starch content of single-grain corn samples, establish Single-grain corn starch content grading model; based on the single-grain corn starch content grading model, non-destructive grading of single-grain corn seed starch content is realized. In the classification method provided by the embodiment of the present invention, a single-grain corn starch content classification model is established through the double-surface standard Raman spectrum curve of a single-grain corn sample combined with the physical and chemical values ​​of starch content, the accuracy of the classification model is improved, and the single-grain corn seed starch content is achieved. Fast non-destructive grading.

Description

technical field [0001] The invention relates to the technical field of grain seed classification and screening, in particular to a single-grain corn starch content Raman hyperspectral classification method. Background technique [0002] A hyperspectral image is a three-dimensional data cube. The data combines the advantages of imaging technology and spectral technology. It combines image information and spectral information into one. During analysis, it can not only perform spectral analysis on a certain area, but also obtain a certain feature. Image information under the band. Raman spectroscopy is a kind of scattering spectrum. Raman signals are generated by molecular vibrations with changing polarizability. Common alkanes, alkenes, alkynes, aromatics, oxygen-containing compounds and nitrogen-containing compounds all have strong Raman bands. . Through the combination of the two technologies, Raman hyperspectral technology can quickly and non-destructively detect samples,...

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Problems solved by technology

[0005] The present invention provides a single-grain corn starch content Raman hyperspectral grading method, which is used to solve the problem that the existing diffuse reflection scanning method often only collects hyperspectral images of one side of corn seeds, and the acquired image information cannot fully reflect the whole grain of corn The real situation of the seeds leads to the unsatisfactory grading effect of the starch content of single-grain corn seeds

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