Abstract:In order to classify the orange juice beverages effectively,the fluorescence character differences of two kinds of orange juice beverages including 100% orange juice and orange drink were analyzed and compared,principal component analysis combined with Euclidean distance was adopted to classify two kinds of orange juice beverages, and ideal classification results were obtained. Meanwhile, the orange juice content estimation model was established by using fluorescence spectroscopy combined with partial least squares regression method, and the correlation coefficient R, root mean square error of calibration RMSEC and root mean square error of prediction RMSEP were 0.997, 0.87% and 2.05%, respectively. The experimental results indicate that the calibration model offers comparatively accurate content estimation, which reflect the actual orange juice content in the commercial orange juice beverages. The exploration to classify orange juice beverages was carried out from two aspects of qualitative and quantitative analysis by employing fluorescence spectroscopy combined with chemometrics method,which can provide a new idea for the classification and adulteration detection of commercial orange juice beverages, and also can give certain reference basis for the quality control of orange juice raw material.
Key words:Fluorescence spectroscopy;Orange juice beverages;Spectrum detection;Content estimation
[1] CHEN Yu-feng, ZHUANG Zhi-ping(陈玉峰,庄志萍). Journal of Anhui Agricultural Science(安徽农业科学), 2011, 39(1): 236. [2] National Standard of the People’s Republic of China(中华人民共和国国家标准). GB/T 16771, Determination of Juice Content in Orange, Tangerine Juice and Their Drinks(橙、柑、桔汁及其饮料中果汁含量的测定),1997. [3] National Standard of the People’s Republic of China(中华人民共和国国家标准). GB/T 12143. General Analytical Methods for Beverage(饮料通用分析方法), 2008. [4] YANG Xiu-jia, WU Hou-jiu(杨秀佳,吴厚玖). Science and Technology of Food Industry(食品工业科技), 2010, 31(1): 384. [5] HU Meng-kun,CEN Qin,LI Dan(胡梦坤,岑 琴,李 丹). Agricultural Science & Technology and Equipment(农业科技与装备), 2012, 7: 76. [6] Guanghou Shui, LaiPeng Leong. Journal of Chromatography A, 2002, 977(1): 89. [7] Saavedra L, Garcia A, Barbas C. Journal of Chromatography A, 2000, 881(9): 395. [8] WU Ji-jun, XIAO Geng-sheng, CHEN Wei-dong, et al(吴继军,肖更生,陈卫东, 等). Science and Technology of Food Industry(食品工业科技), 2003, 24(8): 96. [9] Pandey Kiran, Pradhan Asima, Agarwal Asha. The Journal of Obstetrics and Gynecology of India, 2012, 62(4): 432. [10] Jami H Goldman, Stewart A Rounds, Joseph A Needoba. Environmental Science & Technology, 2012, 46(8): 4374. [11] SHI Xian-he, WU Yan-wen, HOU Min, et al(施显赫, 武彦文, 侯 敏,等). Modern Instruments(现代仪器), 2012, 18(3): 6. [12] Nadezhda A Stoilova, Andriana R Surleva, Georgi Stoev. Food Analytical Methods, 2013, 6(3): 803. [13] Pu Yang, Wang Wubao, Robert R Alfano. Applied Spectroscopy, 2013, 67(2): 210. [14] CAO Jia-jia(曹佳佳). Identification and Quantitative Analysis in Natural Products by Fluorescence Spectroscopy(荧光光谱法用于天然产物的鉴别和定量分析). Guangzhou: Guangdong University of Technology(广州: 广东工业大学), 2010. [15] HU Yang-jun, CHEN Guo-qing, ZHU Chun, et al(胡扬俊,陈国庆,朱 纯,等). Chinese Journal of Luminescence(发光学报),2013, 34(8): 1066. [16] KONG Fan-biao, CHEN Guo-qing, HUANG Qi-feng, et al(孔凡标,陈国庆,黄奇峰, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2013, 33(1): 126.