Turn off MathJax
Article Contents

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. 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. doi: 10.37188/CO.2020-0027

Nondestructive grading test of rice seed activity using near infrared super-continuum laser spectrum

doi: 10.37188/CO.2020-0027
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)
More Information
  • In view of the urgent need for seed selection technology in agriculture and for grading detection of the vigor of peeled 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 designe a near-infrared absorption spectroscopy system that detects seed viability and measure the NIR spectra of husked rice seeds that are picked over three different years. 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 (PIS-DA) model is established. The analysis showed that the transmission absorption spectrum detection system designed in this paper combined with the PLS-DA discrimination model could classify rice seeds of different vigor with an accuracy of 94.44% and 95.92%. After screening, the germination rate of rice seeds could 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.
  • [1]
    杨振发, 肖航, 张雷, 等. 基于近红外光谱的水泥生料氧化物含量快速测定方法研究[J]. 分析化学,2020,48(2):275-281.

    YANG ZH F, XIAO H, ZHANG L, <italic>et al</italic>. Rapid determination of oxides content in cement raw meal based on near infrared spectroscopy[J]. <italic>Chinese Journal of Analytical Chemistry</italic>, 2020, 48(2): 275-281. (in Chinese)
    [2]
    AMBROSE A, LOHUMI S, LEE W H, <italic>et al</italic>. Comparative nondestructive measurement of corn seed viability using fourier transform near-infrared (FT-NIR) and raman spectroscopy[J]. <italic>Sensors and Actuators B</italic>:<italic>Chemical</italic>, 2015, 224: 500-506.
    [3]
    李茂刚, 闫春华, 薛佳, 等. 近红外光谱结合小波变换—随机森林法快速定量分析甲醇汽油中甲醇含量[J]. 分析化学,2019,47(12):1995-2003.

    LI M G, YAN CH H, XUE J, <italic>et al</italic>. Rapid quantitative analysis of methanol content in methanol gasoline by near infrared spectroscopy coupled with wavelet transform-random forest[J]. <italic>Chinese Journal of Analytical Chemistry</italic>, 2019, 47(12): 1995-2003. (in Chinese)
    [4]
    何龙生. 水稻种子活力测定方法的初步研究[D]. 杭州: 浙江农林大学, 2018: 1-2.

    HE L SH. The preliminary study on methods for determination of rice seed vigor[D]. Hangzhou: Zhejiang A&F University, 2018. (in Chinese)
    [5]
    王岳含. 我国种子质量可追溯系统研究[D]. 北京: 中国农业科学院, 2016.

    WANG Y H. Seed quality tracing system of china research[D]. Beijing: Chinese Academy of Agricultural Sciences, 2016. (in Chinese)
    [6]
    牟致远. 小麦种子活力及其遗传分析[J]. 西南农业大学学报,1987,9(4):421-425.

    MU ZH Y. Seedling vigor and genetic analysis in wheat varieties[J]. <italic>Journal of Southwest Agricultural University</italic>, 1987, 9(4): 421-425. (in Chinese)
    [7]
    王青峰, 宫庆友, 沈凌云, 等. 超甜玉米种子活力研究[J]. 种子,2007,26(6):4-7. doi:  10.3969/j.issn.1001-4705.2007.06.002

    WANG Q F, GONG Q Y, SHEN L Y, <italic>et al</italic>. Study of combining ability of seed vigor in super sweet corn[J]. <italic>Seed</italic>, 2007, 26(6): 4-7. (in Chinese) doi:  10.3969/j.issn.1001-4705.2007.06.002
    [8]
    朱银, 颜伟, 杨欣, 等. 基于近红外光谱的小麦种子发芽率测试[J]. 江苏农业科学,2015,43(12):111-113.

    ZHU Y, YAN W, YANG X, <italic>et al</italic>. Test of germination rate of wheat seeds based on near infrared spectroscopy[J]. <italic>Jiangsu Agricultural Sciences</italic>, 2015, 43(12): 111-113. (in Chinese)
    [9]
    李欢欢, 卢伟, 杜昌文, 等. 基于光声光谱结合LS-SVR的稻种活力快速无损检测方法研究[J]. 中国激光,2015,42(11):1115003. doi:  10.3788/CJL201542.1115003

    LI H H, LU W, DU CH W, <italic>et al</italic>. Study on rapid and non-destructive detection of rice seed vigor based on photoacoustic spectroscopy combined with LS-SVR[J]. <italic>Chinese Journal of Lasers</italic>, 2015, 42(11): 1115003. (in Chinese) doi:  10.3788/CJL201542.1115003
    [10]
    李美凌, 邓飞, 刘颖, 等. 基于高光谱图像的水稻种子活力检测技术研究[J]. 浙江农业学报,2015,27(1):1-6. doi:  10.3969/j.issn.1004-1524.2015.01.01

    LI M L, DENG F, LIU Y, <italic>et al</italic>. Study on detection technology of rice seed vigor based on hyperspectral image[J]. <italic>Acta Agriculturae Zhejiangensis</italic>, 2015, 27(1): 1-6. (in Chinese) doi:  10.3969/j.issn.1004-1524.2015.01.01
    [11]
    宋乐, 王琦, 王纯阳, 等. 基于近红外光谱的单粒水稻种子活力快速无损检测[J]. 粮食储藏,2015,44(1):20-23. doi:  10.3969/j.issn.1000-6958.2015.01.005

    SONG L, WANG Q, WANG CH Y, <italic>et al</italic>. Qualitative analysis of single rice seed vigor using near infrared reflectance spectroscopy[J]. <italic>Grain Storage</italic>, 2015, 44(1): 20-23. (in Chinese) doi:  10.3969/j.issn.1000-6958.2015.01.005
    [12]
    ZHOU X B, ZHAO J W, POVEY M J W, <italic>et al</italic>. Variables selection methods in near-infrared spectroscopy[J]. <italic>Analytica Chimica Acta</italic>, 2010, 667(1-2): 14-32. doi:  10.1016/j.aca.2010.03.048
    [13]
    史永刚, 栗斌, 田高友, 等. 化学计量学方法及MATLAB实现[M]. 北京: 中国石化出版社, 2010.

    SHI Y G, LI B, TIAN G Y, et al.. Chemometrics Method and MATLAB Implementation[M]. Beijing: China Petrochemical Press, 2010. (in Chinese)
    [14]
    郭帅, 苏杭, 黄星灿, 等. 光学无创血糖浓度检测方法的研究进展[J]. 中国光学,2019,12(6):1235-1248. doi:  10.3788/co.20191206.1235

    GUO SH, SU H, HUANG X C, <italic>et al</italic>. Research progress in optical methods for noninvasive blood glucose detection[J]. <italic>Chinese Optics</italic>, 2019, 12(6): 1235-1248. (in Chinese) doi:  10.3788/co.20191206.1235
    [15]
    王纯阳. 基于近红外光谱的单籽粒水稻种子品质检测的方法研究[D]. 合肥: 中国科学技术大学, 2017.

    WANG CH Y. The nondestructive quality analysis of single rice seed using near infrared spectroscopy[D]. Hefei: University of Science and Technology of China. (in Chinese)
    [16]
    高升, 王巧华, 李庆旭, 等. 基于近红外光谱的红提维生素C含量、糖度及总酸含量无损检测方法[J]. 分析化学,2019,47(6):941-949.

    GAO SH, WANG Q H, LI Q X, <italic>et al</italic>. Non-destructive detection of vitamin C, sugar content and total acidity of red globe grape based on near-infrared spectroscopy[J]. <italic>Chinese Journal of Analytical Chemistry</italic>, 2019, 47(6): 941-949. (in Chinese)
    [17]
    付丹丹, 王巧华, 高升, 等. 不同品种鸡蛋贮期S—卵白蛋白含量分析及其可见/近红外光谱无损检测模型研究[J]. 分析化学,2020,48(2):289-297.

    FU D D, WANG Q H, GAO SH, <italic>et al</italic>. Analysis of S-Ovalbumin content of different varieties of eggs during storage and its nondestructive testing model by visible-near infrared spectroscopy[J]. <italic>Chinese Journal of Analytical Chemistry</italic>, 2020, 48(2): 289-297. (in Chinese)
    [18]
    刘宁武, 许林广, 周胜, 等. 量子级联激光光谱在土壤生态系统中的应用[J]. 光学学报,2019,39(11):1130001. doi:  10.3788/AOS201939.1130001

    LIU N W, XU G L, ZHOU SH, <italic>et al</italic>. Application of quantum-cascade laser spectroscopy to soil ecosystems[J]. <italic>Acta Optica Sinica</italic>, 2019, 39(11): 1130001. (in Chinese) doi:  10.3788/AOS201939.1130001
    [19]
    谢臣瑜, 翟文超, 李健军, 等. 超连续激光单色仪系统级光谱响应度定标比对验证[J]. 红外与激光工程,2020,49(2):0205005. doi:  10.3788/IRLA202049.0205005

    XIE CH Y, ZHAI W CH, LI J J, <italic>et al</italic>. System-level spectral responsivity calibration comparison and validation of supercontinuum laser and monochromator[J]. <italic>Infrared and Laser Engineering</italic>, 2020, 49(2): 0205005. (in Chinese) doi:  10.3788/IRLA202049.0205005
    [20]
    曹栋栋, 阮晓丽, 詹艳, 等. 杂交水稻种子不同活力测定方法与其田间成苗率的相关性[J]. 浙江农业学报,2014,26(5):1145-1150. doi:  10.3969/j.issn.1004-1524.2014.05.01

    CAO D D, RUAN X L, ZHAN Y, <italic>et al</italic>. Relativity analysis between seedling percentage in field and different seed vigor testing methods of hybrid rice seeds[J]. <italic>Acta Agriculturae Zhejiangensis</italic>, 2014, 26(5): 1145-1150. (in Chinese) doi:  10.3969/j.issn.1004-1524.2014.05.01
    [21]
    刘燕德, 叶灵玉, 孙旭东, 等. 基于光谱指数的蜜橘成熟度评价模型研究[J]. 中国光学,2018,11(1):83-91. doi:  10.3788/co.20181101.0083

    LIU Y D, YE L Y, SUN X D, <italic>et al</italic>. Maturity evaluation model of tangerine based on spectral index[J]. <italic>Chinese Optics</italic>, 2018, 11(1): 83-91. (in Chinese) doi:  10.3788/co.20181101.0083
    [22]
    董盈红. 油菜籽的傅里叶变换红外光谱鉴别[J]. 保山学院学报,2018,37(2):38-41. doi:  10.3969/j.issn.1674-9340.2018.02.011

    DONG Y H. Identification of rapeseed by fourier transform infrared spectroscopy[J]. <italic>Journal of Baoshan Teachers College</italic>, 2018, 37(2): 38-41. (in Chinese) doi:  10.3969/j.issn.1674-9340.2018.02.011
    [23]
    褚小立. 化学计量学方法与分子光谱分析技术[M]. 北京: 化学工业出版社, 2011.

    CHU X L. Molecular Spectroscopy Analytical Technology Combined with Chemometrics and Its Applications[M]. Beijing: Chemical Industry Press, 2011. (in Chinese)
    [24]
    王昕, 吕世龙, 李岩, 等. 基于基线漂移模型的气体光谱自动基线校正[J]. 光谱学与光谱分析,2018,38(12):3946-3951.

    WANG X, LV SH L, LI Y, <italic>et al</italic>. Automatic baseline correction of gas spectra based on baseline drift model[J]. <italic>Spectroscopy and Spectral Analysis</italic>, 2018, 38(12): 3946-3951. (in Chinese)
    [25]
    王凡, 李永玉, 彭彦昆, 等. 基于可见/近红外透射光谱的番茄红素含量无损检测方法研究[J]. 分析化学,2018,46(9):1424-1431. doi:  10.11895/j.issn.0253-3820.181164

    WANG F, LI Y Y, PENG Y K, <italic>et al</italic>. Nondestructive determination of lycopene content based on visible/near infrared transmission spectrum[J]. <italic>Chinese Journal of Analytical Chemistry</italic>, 2018, 46(9): 1424-1431. (in Chinese) doi:  10.11895/j.issn.0253-3820.181164
    [26]
    高升, 王巧华, 付丹丹, 等. 红提糖度和硬度的高光谱成像无损检测[J]. 光学学报,2019,39(10):355-364.

    GAO SH, WANG Q H, FU D D, <italic>et al</italic>. Nondestructive detection of sugar content and firmness of red globe grape by hyperspectral imaging[J]. <italic>Acta Optica Sinica</italic>, 2019, 39(10): 355-364. (in Chinese)
    [27]
    范雪婷, 朱明东, 杨晨光, 等. 利用近红外吸收光谱对水稻种子活力的判别方法[J]. 杂交水稻,2019,34(4):62-67.

    FAN X T, ZHU M D, YANG CH G, <italic>et al</italic>. Assessment of rice seed vigor using near infrared spectroscopy[J]. <italic>Hybrid Rice</italic>, 2019, 34(4): 62-67. (in Chinese)
    [28]
    SAMPAIO P S, SOARES A, CASTANHO A, <italic>et al</italic>. Optimization of rice amylose determination by NIR-spectroscopy using PLS chemometrics algorithms[J]. <italic>Food Chemistry</italic>, 2018, 242: 196-204. doi:  10.1016/j.foodchem.2017.09.058
    [29]
    LIU D L, WU Y X, GAO Z M, <italic>et al</italic>. Comparative non-destructive classification of partial waxy wheats using near-infrared and raman spectroscopy[J]. <italic>Crop </italic>&<italic>Pasture Science</italic>, 2019, 70(5): 437-441.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(7)  / Tables(4)

Article views(49) PDF downloads(10) Cited by()

Proportional views

Nondestructive grading test of rice seed activity using near infrared super-continuum laser spectrum

doi: 10.37188/CO.2020-0027
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)

Abstract: In view of the urgent need for seed selection technology in agriculture and for grading detection of the vigor of peeled 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 designe a near-infrared absorption spectroscopy system that detects seed viability and measure the NIR spectra of husked rice seeds that are picked over three different years. 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 (PIS-DA) model is established. The analysis showed that the transmission absorption spectrum detection system designed in this paper combined with the PLS-DA discrimination model could classify rice seeds of different vigor with an accuracy of 94.44% and 95.92%. After screening, the germination rate of rice seeds could 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.

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. 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. doi: 10.37188/CO.2020-0027

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return