橙汁饮品的荧光光谱特性及模式识别

胡扬俊; 陈国庆; 朱纯; 张咏; 孔凡标; 李润

doi:10.3788/fgxb20133408.1066

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橙汁饮品的荧光光谱特性及模式识别

发光学应用及交叉前沿 | 更新时间：2020-08-12

- 橙汁饮品的荧光光谱特性及模式识别
- Fluorescence Spectra Characteristics and Pattern Recognition of Orange Juice Beverages
- 发光学报 2013年34卷第8期页码：1066-1072
- 作者机构：
  
  江南大学理学院,江苏无锡,中国,214122
- 作者简介：
- 基金信息：
  
  国家自然科学基金(61178032)();江苏省科技支撑计划(社会发展)(BE2011828)资助项目()
- DOI：10.3788/fgxb20133408.1066
  中图分类号： O433.4
- 收稿日期：2013-05-01，
  
  修回日期：2013-05-23，
  
  纸质出版日期：2013-08-10
- 稿件说明：
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胡扬俊, 陈国庆, 朱纯, 张咏, 孔凡标, 李润. 橙汁饮品的荧光光谱特性及模式识别[J]. 发光学报, 2013,34(8): 1066-1072

HU Yang-jun, CHEN Guo-qing, ZHU Chun, ZHANG Yong, KONG Fan-biao, LI Run. Fluorescence Spectra Characteristics and Pattern Recognition of Orange Juice Beverages[J]. Chinese Journal of Luminescence, 2013,34(8): 1066-1072
胡扬俊, 陈国庆, 朱纯, 张咏, 孔凡标, 李润. 橙汁饮品的荧光光谱特性及模式识别[J]. 发光学报, 2013,34(8): 1066-1072 DOI： 10.3788/fgxb20133408.1066.

HU Yang-jun, CHEN Guo-qing, ZHU Chun, ZHANG Yong, KONG Fan-biao, LI Run. Fluorescence Spectra Characteristics and Pattern Recognition of Orange Juice Beverages[J]. Chinese Journal of Luminescence, 2013,34(8): 1066-1072 DOI： 10.3788/fgxb20133408.1066.

摘要

应用FLS920型荧光光谱仪测得鲜榨橙汁、市售橙汁饮品(8种品牌)的三维荧光光谱

通过分析鲜榨橙汁与饮品中常见食品添加剂纯物质的荧光机理与特性

得到橙汁饮品中橙汁成分的最佳激发波长为470 nm

荧光峰值波长为526 nm

其荧光特征峰为470/526 nm

其余荧光峰的归属均为食品添加剂。同时

采用三维荧光光谱重心法与基于MCD估计的稳健马氏距离相结合的方法对市售橙汁饮品进行筛选与分类

分类效果良好。结果表明:将荧光光谱技术与光谱模式识别方法相结合

可为饮料类食品的鉴别提供帮助。

Abstract

Three dimensional fluorescence spectra of fresh orange juice and orange juice beverages (8 brands) were obtained by employing FLS920 spectrometer. The fluorescence mechanism and characters of fresh orange juice and different kinds of pure food additives in beverage foods were analyzed. The optimal excitation wavelength and fluorescence peak wavelength of orange juice are 470 nm and 526 nm

respectively. The characteristic peak of orange juice is 470/526 nm

and other peaks belong to food additives. Meanwhile

By extracting the center of gravity of three dimensional fluorescence spectroscopy

and combining the robust Mahalanobis distance based on MCD estimator

the orange juice beverages were classified

and the classification results were ideal. The results indicate that the combination of spectral detection and pattern recognition can contribute to the classification of beverages.

关键词

Keywords

references

GB/T 21731. Orange juice and orange juice beverages [S]. Beijing： AQSIQ, SAC, 2008 (in Chinese).[2] GB/T 16771. Determination of juice content in orange, tangerine juice and their drinks [S]. Beijing： AQSIQ, SAC, 1997 (in Chinese).[3] Liu X M, Xiao G S, Chen W D, et al. Advance in the detection of juice adulteration [J]. Food and Fermentation Industry (食品与发酵工业), 2006, 32(6)：87-91 (in Chinese).[4] Yang X J. Evaluation on Six Characteristic Marks of Commercial Orange Juices and Main Juice Oranges Produced in China [D]. Chongqing： Southwest University, 2009 (in Chinese).[5] Wu J Z, Tang S Z, Sun X, et al. Review on detection techniques about primary fruit juice content in fruit drinks [J].Food and Fermentation Industry (食品与发酵工业), 2006, 32(2)：78-82 (in Chinese).[6] Shui G H, Leong L P. Separation and determination of organic adds and phenolic compounds in fruit juices and drinks by high-performance liquid chromatography [J]. J. Chromat. A, 2002, 977(1)：89-96.[7] Saavedra L, Garcia A, Barbas C. Development and validation of a capillary electrophoresis method for direct measurement of isocitric, citric, tartaric and malic acids as adulteration markers in orange juice [J]. J. Chromat. A, 2000, 881(9)：395-401.[8] Wu J J, Xiao G S, Chen W D, et al. A method to determine the contents of mulberry juice by buffer capability [J]. Food Science (食品科学), 2003, 24(6)：100-102 (in Chinese).[9] Legin A, Rudnitskaya A, Vlasov Y. Tasting of beverages using an electronic tongue [J]. Sensors and Actuators B, Chemical, 1997, 44(1-3)：291-296.[10] Zhu D Z, Ji B P, Qing Z S, et al. The detection of quality deterioration of apple juice by near infrared and fluorescence spectroscopy [J]. Computer Sci., 2011, 346：84-91.[11] Liu J, Saw C L, Olivo M, et al. Study of interaction of hypericin and its pharmaceutical preparation by fluorescence techniques [J]. J. Biomed. Opt., 2009, 14(1)：1-9.[12] Goldman J H, Rounds S A, Needoba J A, et al. Applications of fluorescence spectroscopy for predicting percent wastewater in an urban stream [J]. Envir. Sci. Technol., 2012, 46(8)：4374-4381.[13] Shang L P, Yang R J. Field Fluorescence Spectrum Technology and Its Application [M]. Beijing： Science Press, 2009：130-181 (in Chinese).[14] Li J J, Zhao L H. Pattern Recognition Technology [M]. Beijing： Electronic Industry Press, 2010：81-102 (in Chinese).[15] Hekimoglu S, Erenoglu R C, Kalina J. Outlier detection by means of robust regression estimators for use in engineering science [J]. J. Zhejiang Univ. Sci. A, 2009, 10(6)：909-921.[16] Wu H L, Kang C. Practical Guide to Chemometrics [M]. 2nd edition. Beijing： Science Press, 2012：142-170 (in Chinese).[17] Wang B H, Chen Y F. A robust principal component analysis based on MCD estimator and its empirical study [J]. Application of Statistics and Management (数理统计与管理), 2006, 25(4)：462-468 (in Chinese).[18] Rousseeuw P J, Verboven S. Robust estimation in very small samples [J].Computational Statistics & Data Analysis, 2002, 40(4)：741-758.[19] Zhu X L. Molecular Spectroscopy Analytical Technology Combined with Chemometrics and Its Application [M].Beijing：Chemical Industry Press, 2001：124-137 (in Chinese).[20] Kong F B, Chen G Q, Huang Q F, et al. Detection of carrageenan in the orange juice using fluorescence spectra methods [J]. Spectrosc. Spect. Anal.(光谱学与光谱分析), 2013, 33(1)：126-129 (in Chinese).

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