Volume 13 Issue 5
Sep.  2020
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Chinese Optics  > 2020  >  13(5): 1032-1043.
JIN Wen-ling, CAO Nai-liang, ZHU Ming-dong, CHEN Wei, ZHANG Pei-guang, ZHAO Qing-lei, LIANG Jing-qiu, YU Ying-hong, LV Jin-guang, KAN Rui-feng. Nondestructive grading test of rice seed activity using near infrared super-continuum laser spectrum[J]. Chinese Optics, 2020, 13(5): 1032-1043. doi: 10.37188/CO.2020-0027
Citation: JIN Wen-ling, CAO Nai-liang, ZHU Ming-dong, CHEN Wei, ZHANG Pei-guang, ZHAO Qing-lei, LIANG Jing-qiu, YU Ying-hong, LV Jin-guang, KAN Rui-feng. Nondestructive grading test of rice seed activity using near infrared super-continuum laser spectrum[J]. Chinese Optics, 2020, 13(5): 1032-1043. doi: 10.37188/CO.2020-0027
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Nondestructive grading test of rice seed activity using near infrared super-continuum laser spectrum

  • 1.

    State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China

  • 3.

    Hunan Rice Research Institute, Changsha 410125, China

  • 4.

    Hunan Academy of Agricultural Science, Changsha 410125, China

Funds:  Supported by Hunan Agricultural Science and Technology Innovation Fund Project (No. 2018NK1020); National Natural Science Foundation of China (No. 61627819, No.61805239, No. 61727818); Jilin Province Science and Technology Development Plan (No. 20190303063SF, No. 20180201024GX, No.20150520101JH); Foundation of Youth Innovation Promotion Association of Chinese Academy of Sciences (No. 2018254)
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    Abstract
  • In view of the urgent need for seed selection technology in agriculture and for grading detection of the vigor of three different years of unpeeled rice seeds, we proposed a new method of detecting the vigor of rice seeds based on near-infrared super-continuous laser spectrum to overcome the significant issues in pre-existing universal brown rice detection technology. Firstly, we design a near-infrared absorption spectroscopy system with which we detect seed viability and measure the NIR spectra of three different years of unpeeled rice seeds. The results show that the activity gradient of the rice seeds is correlated with the characteristic absorption peak of their NIR absorption spectrum. Then, the spectrum of seed is optimized with a pretreatment algorithm of normalization, second derivative correction and orthogonal signal correction. Finally, a Principal Component Analysis (PCA) model is established to reduce the dimension of the spectrum and determine the optimal number of principal components. A Partial Least Squares Discriminant Analysis (PLS-DA) model is established. The analysis results show that the transmission absorption spectrum detection system designed in this paper combined with the PLS-DA discrimination model can classify rice seeds of different vigor with an accuracy of 94.44% and 95.92%. After screening, the germination rate of rice seeds can reach 97.17%. The results show that it is feasible to achieve non-destructive classification of rice seed activity using near-infrared spectroscopy with high accuracy.

     

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