Identification of Maize Seed Purity Based on Spectral Images of A Small Amount of Near Infrared Bands
RAN Hang1，CUI Yong-jin1，JIN Zhao-xi1，YAN Yan-lu1，AN Dong1,2*
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2. Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
Abstract：The method of identifying maize seed purity by analysising seeds spectral images of a small amount of near infrared bands was developed to satisfy the needs of rapid inspection and automatic sorting of maize hybrid seeds. The spectral images of hybrid and female parent of 5 maize varieties at 4 short wave near infrared bands in transmission mode and 4 medium wave near infrared bands in reflection mode were collected. Black-white calibration, median filtering, otsu method were applied to remove the noise and extract the seeds from background. Texture features were extracted by histogram statistics(HS) and gray level co-occurrence Matrix(GLCM). Splicing the feature data at each wavelength, principal component analysis(PCA) and orthogonal linear discriminant analysis(OLDA) were applied to reduce dimensions and obtain the best separability of subspace. The transmission and reflection spectral image purity identification model was built by support vector machine (SVM). The average correct identification rate of 5 maize varieties was above 85% both in transmission and reflection models. This research show that it is feasible to use spectral images of a small amount of near infrared bands to identify the purity of maize hybrid seeds.
冉 航，崔永进，靳召晰，严衍禄，安 冬. 利用少量波段近红外光谱图像鉴定玉米种子纯度[J]. 光谱学与光谱分析, 2017, 37(09): 2743-2750.
RAN Hang，CUI Yong-jin，JIN Zhao-xi，YAN Yan-lu，AN Dong. Identification of Maize Seed Purity Based on Spectral Images of A Small Amount of Near Infrared Bands. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(09): 2743-2750.
[1] BAI Ou, HUANG Rui-dong(白 鸥, 黄瑞冬). Journal of Maize Sciences(玉米科学)，2007, 15(3): 59，70.
[2] QUAN Long-zhe, ZHU Rong-xin, LEI Pu, et al(权龙哲, 祝荣欣, 雷 溥, 等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报)，2010, 41(4): 168.
[3] CHENG Hong, SHI Zhi-xing, YIN Hui-juan, et al(程 洪, 史智兴, 尹辉娟, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报)，2013, 29(19): 145.
[4] LIU Shuang-xi, WANG Pan, ZHANG Chun-qing, et al(刘双喜, 王 盼, 张春庆, 等). Transactions of the Chinese Society of Agricultural Machinery(农业机械学报)，2012, 43(4): 188.
[5] XU Shu-tu, WANG Wen-bin, GAO Jie, et al(徐淑兔，王文斌，高 杰，等). Journal of Maize Sciences(玉米科学)，2015，23(3)： 15.
[6] TANG Jin-ya, HUANG Min, ZHU Qi-bing(唐金亚，黄 敏，朱启兵). Laser & Optoelectronics(激光与光电子学进展)，2015，52(4)： 95.
[7] JIA Shi-qiang, LIU Zhe, LI Shao-ming, et al(贾仕强, 刘 哲, 李绍明, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2013, 33(10): 2847.
[8] ZHU Qi-bing, FENG Chao-li, HUANG Min, et al(朱启兵, 冯朝丽, 黄 敏, 等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报)，2012, 28(23): 271.
[9] Osborne B G. Near Infrared Spectroscopy in Food Analysis. Australia: Wiely Interscience, 1986. 1.
[10] HU Dou-ming, ZHAO Hai-sheng, LI Yun-chuan, et al(胡窦明, 赵海生, 李云川, 等). Infrared Technology(红外技术)，2012, 34(4): 224.
[11] QUAN Long-zhe, MA Xiao-yu(权龙哲, 马小愚). Journal of Agricultural Mechanization Research(农机化研究)，2006, (2): 154.
[12] Paschos G, Petrou M. Pattern Recognition Letters, 2003, 24(1): 309.
[13] Bharati M H, Liu J J, Macgregor J F. Chemometrics & Intelligent Laboratory Systems, 2004, 72(1): 57.
[14] Ye J, Xiong T. Journal of Machine Learning Research, 2006, 7(3): 1183.
