Single-grain fixed-point recognition technology by aiming at different categories of wheat seeds

Abstract

The invention discloses a single-grain fixed-point recognition technology by aiming at different categories of wheat seeds. The technology comprises the following steps that: obtaining the hyperspectral image data of a wheat seed to be identified, and after a black and white correction method is adopted to correct the hyperspectral image, carrying out principal component transformation; selectinga whole grain of wheat seed as a region of interest to extract the average spectrum as the spectral data of a grain sample; adopting a S-G smoothing method to carry out smoothing processing on the spectral data; using a Kennard-Stone method to divide the sample spectral data into a training set and a prediction set at a ratio of 3:2, and adopting a successive projection algorithm to select an optimal waveband for identifying the wheat seeds of different hybrid varieties; constructing a support vector machine model; and inputting an optimal waveband into the established SVM (Support Vector Machine) model, and showing a prediction result by different colors to finish hybrid seed fixed-point recognition. By use of the technology, the online detection of the wheat grains of different hybrid varieties is realized, and single-grain fixed-point recognition is realized.

Description

technical field [0001] The invention relates to the field of seed identification, in particular to a single-grain fixed-point identification technology for different varieties of wheat seeds. Background technique [0002] The purity of seeds is an important indicator to measure the quality of seeds. The purity of the wheat is defined as the proportion of the intended seed contained in the test seed lot. With the wide application of hybridization technology, wheat seed varieties are increasing, and the similarity between varieties is gradually increasing, and it is difficult to distinguish them subjectively. During storage and transportation, different wheat seeds may be mixed together, reducing the purity of the seeds and affecting the traits of hybrid offspring. And unscrupulous businessmen mix seeds of other varieties or unqualified seeds into qualified seeds, causing crop yield reduction and seriously damaging the interests of growers. Traditional seed purity testing m...

AI Technical Summary

Problems solved by technology

However, machine vision can only capture a single trait of a seed sample

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