Application of Characteristic NIR Variables Selection in Portable Detection of Soluble Solids Content of Apple by Near Infrared Spectroscopy
FAN Shu-xiang1, 2, HUANG Wen-qian2, LI Jiang-bo2，GUO Zhi-ming2, ZHAO Chun-jiang1, 2*
1. College of Mechanical and Electronic Engineering, Northwest A & F University, Yangling 712100, China 2. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Abstract：In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including uninformative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were proposed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS-SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.
樊书祥1, 2，黄文倩2，李江波2，郭志明2，赵春江1, 2* . 特征变量优选在苹果可溶性固形物近红外便携式检测中的应用 [J]. 光谱学与光谱分析, 2014, 34(10): 2707-2712.
FAN Shu-xiang1, 2, HUANG Wen-qian2, LI Jiang-bo2，GUO Zhi-ming2, ZHAO Chun-jiang1, 2* . Application of Characteristic NIR Variables Selection in Portable Detection of Soluble Solids Content of Apple by Near Infrared Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(10): 2707-2712.
[1] Nicola B M, Beullens K, Bobelyn E, et al. Postharvest Biology and Technology, 2007, 46(2): 99. [2] Li J, Huang W, Zhao C, et al. Journal of Food Engineering, 2013, 116(2): 324. [3] Xu H, Qi B, Sun T, et al. Journal of Food Engineering, 2012, 109(1): 142. [4] Ying Y, Liu Y, Tao Y. Applied Optics, 2005, 44(25): 5224. [5] Liew C Y, Lau C Y. International Food Research Journal, 2012, 19(2): 751. [6] Camps C, Christen D. LWT-Food Science and Technology, 2009, 42(6): 1125. [7] ZHAO Jie-wen, ZHANG Hai-dong, LIU Mu-hua(赵杰文, 张海东, 刘木华). Acta Optica Sinica(光学学报), 2006, 26(1): 136. [8] Liu Y, Ying Y, Fu X, et al.. Journal of Food Engineering, 2007, 80(3): 986. [9] Xiaobo Z, Jiewen Z, Xingyi H, et al. Chemometrics and Intelligent Laboratory Systems, 2007, 87(1): 43. [10] Fan G, Zha J, Du R, et al. Journal of Food Engineering, 2009, 93(4): 416. [11] Bobelyn E, Serban A S, Nicu M, et al. Postharvest Biology and Technology, 2010, 55(3): 133. [12] 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(现代近红外光谱分析技术). Beijing, China Petrochemical Press(北京: 中国石化出版社), 2000. [13] Cai W, Li Y, Shao X. Chemometrics and Intelligent Laboratory Systems, 2008, 90(2): 188. [14] CHU Xiao-li, YUAN Hong-fu, WANG Yan-bin, et al(褚小立, 袁洪福, 王艳斌, 等). Chinese Journal of Analytical Chemistry(分析化学), 2001, 29(4): 437. [15] Li H, Liang Y, Xu Q, et al. Analytica Chimica Acta, 2009, 648(1): 77. [16] LIU Yan-de, SHI Yu, CAI Li-jun，et al(刘燕德, 施 宇, 蔡丽君, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2013, 44(9): 138. [17] Nrgaard L, Saudland A, Wagner J. Applied Spectroscopy, 2000, 54(3): 413. [18] Wu D, He Y, Feng S, et al. Journal of Food Engineering, 2008, 84(1): 124.
