Establishment method for single corn seed protein detection model and application of establishment method

Abstract

The invention relates to detection of the protein content of single crop seeds and particularly discloses an establishment method for a single corn seed protein detection model. The establishment method comprises the specific steps that the diffuse reflection spectra of a sample are collected, effective wavelengths are selected, processing of smoothing (a nine-point window), first-order differentiation and standardization is carried out in sequence, the partial least square method (PLS) is used for dimensionality reduction, the PLS and a support vector machine method (SVR) are used for modeling, near-infrared spectrum data of an unknown sample is obtained under the same conditions and subjected to the same preprocessing and characteristic extraction, and finally the protein content of the sample is detected with the established quantitative analysis model.

Description

technical field [0001] The invention relates to the identification of single-grain seeds of crops, in particular to a method for constructing a protein content detection model of corn single-grain seeds. Background technique [0002] Seeds are the soul of agriculture. my country is a big agricultural country, and seeds are the basic means of production for agricultural production. China is the most populous country in the world. The development of the seed industry is related to the national economy and people's livelihood. . In the field of crop breeding, accurate identification of nutrient components of breeding materials plays an important role in accelerating the breeding process. At present, any component detection and identification of crop breeding materials relies on chemical component analysis, and the identification of hybrid seed purity relies on molecular marker fingerprints. The viability test uses the "tetrazolium" method, and the germination test detects the...

AI Technical Summary

Problems solved by technology

At present, there are very few studies on the use of near-infrared technology to detect the nutrient content of a single corn kernel at home and abroad. This study is dedicated to exploring how to establish a near-infrared quantitative analysis technology suitable for detecting the nutrient content of a single corn kernel.

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