Rapid identification of rice seed based on inverse Fourier transform of laser-induced breakdown spectroscopy

摘要

The identification of rice seeds is crucial for agriculture production.An inverse Fourier transform(IFT)method based on laser-induced breakdown spectroscopy(LIBS)is proposed to identify five kinds of rice seeds.The LIBS data of the samples were preprocessed by inverse fast Fourier transform(IFFT),and the time-domain signals of rice seeds were obtained.The back propagation(BP)neural network was used to establish full spectrum,segmented spectrum,time-domain full spectrum and time-domain segmented spectrum discrimination models.Compared with the original spectrum,the time-domain spectrum can significantly improve the identification accuracy.The time-domain full-spectrum identification accuracy reached 95.28%,and the time-domain segmented spectrum identification accuracy reached 94.36%,whose identification time was only a few seconds.The results demonstrate that LIBS detection technology combined IFFT and BP neural network is fast and accurate,which provides a new idea for batch detection of rice seeds.