Abstract:In this paper, three representative varieties of peanut seeds were selected for the experiment based on visible/near-infrared reflectance spectroscopy living in the wavelength rang from 600 to 1 100 nm.Firstly, spectral datas ware collected by the near-infrared fiber optic spectrometer, and the spectral features of the original spectral dates were extracted by the wavelet analysis.Then the principal component analysis (PCA) was used for cluster analysis of spectral features. Finally, the four principal components were applied as the inputs,the varieties category as the output and the Mahalanobis distance as the discriminant function of the recognitionmodel, so a linear discriminant analysis model was established.In the 50 samples of each varieties, 30 samples were randomly selected as the training set, and the remaining 20 samples as the predictor set. The recognitionmodel for three peanut varieties have a recognition rate of 95% on average. As the experimental results show that this method is reliable and effectively, and a new method to distinguish and discriminate the quality of peanut seeds was put forword.
[1] WAN Shu-bo(万书波). Peanut Quality Science(花生品质学). Beijing: China Agricultural Science and Technology Press(北京:中国农业科学技术出版社), 2005. 13. [2] 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. [3] JIANG Ke-sheng, KONG Li-chun, YU Peng, et al(姜科声,孔黎春,余 鹏,等). Chinese Journal of Spectroscopy Laboratory(光谱实验室),2008,25(4): 550. [4] Zhao H, Guo B, Wei Y, et al. Food chemistry, 2013, 138(2): 1902. [5] Balabin R M, Safieva R Z, Lomakina E I. Microchemical Journal, 2011, 98(1): 121. [6] LU Wan-zhen, YUAN Hong-fu, CHU Xiao-li(陆婉珍, 袁洪福, 褚小立). Near-Infrared Spectroscopy Instruments(近红外光谱仪器). Beijing: Chemical Industry Press(北京:化学工业出版社),2010. [7] LIU Ming-cai(刘明才). Wavelet Analysis and Applications(小波分析及其应用). Beijing: Tsinghua University Press(北京: 清华大学出版社), 2005. [8] YAN Yan-lu(严衍禄). Foundation and Application of Near Infrared Spectroscopy(近红外光谱分析基础与应用). Beijing: China Light Industry Press(北京:中国轻工业出版社), 2005. [9] CHEN Gui-ming, QI Hong-yu(陈桂明, 戚红雨). Matlab Mathematical Statistics(Matlab数理统计). Beijing: Science Press(北京:科学出版社), 2002. [10] YANG Shu-ying(杨淑莹). Pattern Recognition and Intelligent Computing(模式识别与智能计算). Beijing: Electronic Industry Press(北京:电子工业出版社), 2011. [11] ZHANG Zheng-xing(张正行). Organic Spectroscopy(有机光谱分析). Beijing: People’s Health Press(北京:人民卫生出版社), 2009.