Near Infrared Spectroscopy Analysis Method of Maize Hybrid Seed Purity Discrimination
HUANG Hua-jun1, YAN Yan-lu1, SHEN Bing-hui1, LIU Zhe1, GU Jian-cheng2, LI Shao-ming1, ZHU De-hai1, ZHANG Xiao-dong1, MA Qin1, LI Lin1, AN Dong1*
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China 2. Beijing Kings Nower Seed S&T Co., Ltd., Beijing 100080, China
Abstract:Near infrared spectroscopy analysis method of discrimination of maize hybrid seed purity was studied with the sample of Nong Hua 101 (NH101) from different origins and years. Spectral acquisition time lasted for 10 months. Using Fourier transform (FT) near infrared spectroscopy instruments, including 23 days in different seasons (divided into five time periods), a total of 920 near infrared diffuse reflectance spectra of single corn grain of those samples were collected. Moving window average, first derivative and vector normalization were used to pretreat all original spectra, principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to reduce data dimensionality, and the discrimination model was established based on biomimetic pattern recognition (BPR) method. Spectral distortion was calibrated by spectra pretreatment, which makes characteristics spatial distribution range of sample spectra set contract. The relative distance between hybrid and female parent increased by nearly 70-fold, and the discrimination model achieved the identification of hybrid and female parent seeds. Through the choice of representative samples, the model’s response capacity to the changes in spectral acquisition time, place and environment, etc. was improved. Besides, the model’s response capacity to the changes in time and site of seed production was also improved, and the robustness of the model was enhanced. The average correct acceptance rate (CAR) of the test set reached more than 95% while the average correct rejection rate (CRR) of the test set also reached 85%.
[1] WU Li-li, WANG Qing-sheng(吴丽丽,王庆胜). Heilongjiang Agricultural Sciences(黑龙江农业科学),2009,(3):170. [2] YAN Mi-ge, PIAN Yue-bin, LI Su-ling, et al(闫米格,骈跃斌,李素玲,等). Journal of Jilin Agricultural Sciences(吉林农业科学), 2011,36(3):9. [3] YAN Yan-lu, CHEN Bin, ZHU Da-zhou, et al(严衍禄,陈 斌,朱大洲, 等). Near Infrared Spectroscopy—Principles, Technologies and Applications(近红外光谱分析的原理、 技术与应用). Beijing: China Light Industry Press(北京:中国轻工业出版社),2013. [4] LU Wan-zhen, YUAN Hong-fu, XU Guang-tong, et al(陆婉珍,袁洪福,徐广通,等). Modern Near Infrared Spectroscopy Analytical Technology(Second Edition)(现代近红外光谱分析技术,第2版). Beijing: China Petrochemical Press(北京:中国石化出版社), 2007. [5] WU Jun, BAI Qi-lin, YAN Yan-lu, et al(吴 军,白琪林,严衍禄,等). Chinese Journal of Analytical Chemistry(分析化学) ,2005 (10):1421. [6] GUO Ting-ting, WU Wen-jin, SU Qian, et al(郭婷婷,邬文锦,苏 谦,等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报),2009, 9(40):87. [7] PAN An-long, WANG Jing, LI Dian-ge, et al(潘安龙,王 晶,李典格,等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2011, 7(27):349. [8] LI Nan, XU Yun-hua, SONG Wen-wen, et al(李 楠,许韵华,宋雯雯,等). Journal of Plant Genetic Resources(植物遗传资源学报),2012, 13(6):1037. [9] WANG Qing, XUE Wei-qing, MA Han-xu, et al(王 庆,薛卫青,马晗煦,等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2012, 10(28):259. [10] SHEN Li-feng, JIA Shi-qiang, GUO Ting-ting, et al(沈立峰,贾仕强,郭婷婷,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2012, 32(4): 939.