Identification method of rice varieties based on laser-induced breakdown spectroscopy (LIBS)

Abstract

The invention provides an identification method of rice varieties based on laser-induced breakdown spectroscopy (LIBS). The identification method comprises the following steps of S1, measuring a spectrum in a certain range of N standard rice varieties; S2, performing data processing on the spectrum of the N standard rice varieties, S3, performing spectral line identification on data subjected to average processing, so as to acquire wave crest spectral lines of chemical elements of which the contents are at the top; S4, selecting the wave crest spectral lines in S3 to synthesize a characteristic spectrum as an input value of a BP neural network and training to obtain a BP neural network structure; S5, measuring the spectrum in the certain range of one rice variety to be measured by utilizing the LIBS; S6, performing data processing on the spectrum in S5; S7, performing spectral line identification on the spectrum of the rice variety to be measured to obtain the spectral lines of elements which are same with the elements in S3; S8, selecting the wave crest spectral lines in S7 to synthesize the characteristic spectrum as the input value, utilizing the BP neural network in S4 to identify the rice variety to be measured, so as to obtain an identification result; S9, judging whether the identification result is one of the N standard rice varieties or not.

Description

technical field [0001] The invention relates to the technical field of rapid identification of rice varieties, in particular to a method for identifying rice varieties based on laser-induced breakdown spectroscopy. Background technique [0002] Rice is one of the most important food crops in China. At present, the sown area of ​​rice in my country accounts for about 1 / 4 of the total area of ​​food crops, but its output accounts for about 1 / 2 of the country's total food production. [0003] Rice variety identification is an important issue in agricultural production, crop breeding and seed testing. Due to the increasing phenomenon of producing and selling fake and inferior seeds, the economic losses caused every year are huge. At the same time, due to the difficulty in species identification, huge economic losses will be caused every year due to species mistakes and poor purity. Therefore, the identification of rice varieties has been paid more and more attention by seed qu...

AI Technical Summary

Problems solved by technology

However, these spectral analysis techniques also have some shortcomings, such as: the recognition rate needs to be improved, or the data processing is more complicated, it is difficult to identify when there are impurities on the surface of rice grains, such as mold on the surface of rice grains, these spectral techniques cannot be used very well identify

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