Literature DB >> 20545134

[Quality analysis of olive oil and quantification detection of adulteration in olive oil by near-infrared spectrometry and chemometrics].

Xiao-Li Zhuang1, Yu-Hong Xiang, Hong Qiang, Zhuo-Yong Zhang, Ming-Qiang Zou, Xiao-Fang Zhang.   

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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Year:  2010        PMID: 20545134

Source DB:  PubMed          Journal:  Guang Pu Xue Yu Guang Pu Fen Xi        ISSN: 1000-0593            Impact factor:   0.589


  1 in total

Review 1.  A Review of Advanced Methods for the Quantitative Analysis of Single Component Oil in Edible Oil Blends.

Authors:  Xihui Bian; Yao Wang; Shuaishuai Wang; Joel B Johnson; Hao Sun; Yugao Guo; Xiaoyao Tan
Journal:  Foods       Date:  2022-08-13
  1 in total

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