光谱学与光谱分析 |
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Quality Analysis of Olive Oil and Quantification Detection of Adulteration in Olive Oil by Near-Infrared Spectrometry and Chemometrics |
ZHUANG Xiao-li1,XIANG Yu-hong1,QIANG Hong1,ZHANG Zhuo-yong1*,ZOU Ming-qiang2, ZHANG Xiao-fang2 |
1. Department of Chemistry,Capital Normal University,Beijing 100048,China 2. Chinese Academy of Inspection and Quarantine,Beijing 100025, China |
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Abstract Discriminant analysis was used to classify 20 olive oil samples based on their near-infrared (NIR) spectra. The samples were successfully classified into two categories which are consistent with extra virgin olive oil and ordinary olive oil defined in the products. The NIR spectra of olive-oil mixtures containing colza oil, corn oil, peanut oil, camellia oil, sunflower oil, and poppy seed oil were collected, respectively. The volume percent of adulterants ranged from 0 to 100%. The best spectrum bands for analysis were selected before developing partial least-squares (PLS) calibration models. The relative errors of prediction ranged from -5.67% to 5.61%. Results showed that the method combined with chemometrics methods and near-infrared spectrometry is simple, fast and credible for qualitative and quantitative analyses of olive oil samples.
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Received: 2009-04-12
Accepted: 2009-07-16
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Corresponding Authors:
ZHANG Zhuo-yong
E-mail: gusto2008@vip.sina.com
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[1] ZHAO Dan,XIAO Ping,REN Yan(赵 丹,肖 平,任 雁). South China Agriculture(南方农业),2007,1(2):49. [2] XU Li,WANG Ruo-lan,GAO Xue-qin(徐 莉,王若兰,高雪琴). Food and Nutrition in China(中国食物与营养),2006,(10):46. [3] LIU Ya,ZHAO Guo-hua,CHEN Zong-dao, et al(刘 娅,赵国华,陈宗道, 等). Guangzhou Food Science and Technology(广州食品工业科技),2002,18(4):44. [4] Armenta S,Garrigues S,Guardia M. de la. Analytica Chimica Acta,2007,596:330. [5] Christy A A, Kasemsumran S, Du Y P, et al. Analytical Sciences,2004,20(6):935.
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