2019
DOI: 10.1016/j.foodchem.2018.10.105
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Discrimination of geographical origin of oranges (Citrus sinensis L. Osbeck) by mass spectrometry-based electronic nose and characterization of volatile compounds

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Cited by 60 publications
(31 citation statements)
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“…Isotopic ratios of 13 C/ 12 C, 15 N/ 14 N, 18 O/ 16 O, 2 H/ 1 H, and 34 S/ 32 S are usually analyzed by isotope ratio MS (IRMS). For the determination of isotope ratios, the analytes must be converted to the gas phase-H 2 , N 2 , CO, CO 2 , and SO 2 -before ionization.…”
Section: Multiple Isotope Ratiomentioning
confidence: 99%
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“…Isotopic ratios of 13 C/ 12 C, 15 N/ 14 N, 18 O/ 16 O, 2 H/ 1 H, and 34 S/ 32 S are usually analyzed by isotope ratio MS (IRMS). For the determination of isotope ratios, the analytes must be converted to the gas phase-H 2 , N 2 , CO, CO 2 , and SO 2 -before ionization.…”
Section: Multiple Isotope Ratiomentioning
confidence: 99%
“…Some articles, according to the type of product, are referenced below. In the category of 'plant-crops and herbs': potato [14], vegetables: lettuce, pepper, tomato [15], onions [16], rice, flour and cereals [17], oranges [18], herbs [19][20][21]. In the category of 'oils': olive oil [22][23][24].…”
Section: Published Research For Geographical Origin Authentication Frmentioning
confidence: 99%
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“…But the KNN (CP-1NN and CP-3NN) provides the prediction reliability. Centonze et al (2019) in their paper, they used electronic nose to discriminate the different varieties of oranges belongs to three regions Italy, South Africa and Spain. They applied multivariate statistical models to the E-nose response.…”
Section: Discrimination Of Substance Using Electronic Nosementioning
confidence: 99%
“…With the advantages of high resolution, good sensitivity, short cycle and wide scanning range, ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS/MS) is widely used in studying the compositions of TCM [13,14]. Additionally, the analysis methods of chemometric, such as partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), can be adopted to analyze the differences between two groups of multiple variables [15][16].…”
mentioning
confidence: 99%