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Chemometric characterization of fruit juices from Spanish cultivars according to their phenolic compound contents: I. Citrus fruits.
J Agric Food Chem. 2012 Apr 11; 60(14):3635-44.JA

Abstract

The data set composed by phenolic compound profiles of 83 Citrus juices (determined by HPLC-DAD-MS/MS) was evaluated by chemometrics to differentiate them according to Citrus species (sweet orange, tangerine, lemon, and grapefruit). Cluster analysis (CA) and principal component analysis (PCA) showed natural sample grouping among Citrus species and even the Citrus subclass. Most of the information contained in the full data set can be captured if only 15 phenolic compounds (concentration ≥10 mg/L), which can be quantified with fast and accurate methods in real samples, are introduced in the models; a good classification which allows the confirmation of the authenticity of juices is achieved by linear discriminant analysis. Using this reduced data set, fast and routine methods have been developed for predicting the percentage of grapefruit in adulterated sweet orange juices using principal component regression (PCR) and partial least-squares regression (PLS). The PLS model has provided suitable estimation errors.

Authors+Show Affiliations

Departamento de Química Analítica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Bilbao, Spain.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

22423971

Citation

Abad-García, Beatriz, et al. "Chemometric Characterization of Fruit Juices From Spanish Cultivars According to Their Phenolic Compound Contents: I. Citrus Fruits." Journal of Agricultural and Food Chemistry, vol. 60, no. 14, 2012, pp. 3635-44.
Abad-García B, Berrueta LA, Garmón-Lobato S, et al. Chemometric characterization of fruit juices from Spanish cultivars according to their phenolic compound contents: I. Citrus fruits. J Agric Food Chem. 2012;60(14):3635-44.
Abad-García, B., Berrueta, L. A., Garmón-Lobato, S., Urkaregi, A., Gallo, B., & Vicente, F. (2012). Chemometric characterization of fruit juices from Spanish cultivars according to their phenolic compound contents: I. Citrus fruits. Journal of Agricultural and Food Chemistry, 60(14), 3635-44. https://doi.org/10.1021/jf300022u
Abad-García B, et al. Chemometric Characterization of Fruit Juices From Spanish Cultivars According to Their Phenolic Compound Contents: I. Citrus Fruits. J Agric Food Chem. 2012 Apr 11;60(14):3635-44. PubMed PMID: 22423971.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Chemometric characterization of fruit juices from Spanish cultivars according to their phenolic compound contents: I. Citrus fruits. AU - Abad-García,Beatriz, AU - Berrueta,Luis A, AU - Garmón-Lobato,Sergio, AU - Urkaregi,Arantza, AU - Gallo,Blanca, AU - Vicente,Francisca, Y1 - 2012/03/29/ PY - 2012/3/20/entrez PY - 2012/3/20/pubmed PY - 2012/8/8/medline SP - 3635 EP - 44 JF - Journal of agricultural and food chemistry JO - J Agric Food Chem VL - 60 IS - 14 N2 - The data set composed by phenolic compound profiles of 83 Citrus juices (determined by HPLC-DAD-MS/MS) was evaluated by chemometrics to differentiate them according to Citrus species (sweet orange, tangerine, lemon, and grapefruit). Cluster analysis (CA) and principal component analysis (PCA) showed natural sample grouping among Citrus species and even the Citrus subclass. Most of the information contained in the full data set can be captured if only 15 phenolic compounds (concentration ≥10 mg/L), which can be quantified with fast and accurate methods in real samples, are introduced in the models; a good classification which allows the confirmation of the authenticity of juices is achieved by linear discriminant analysis. Using this reduced data set, fast and routine methods have been developed for predicting the percentage of grapefruit in adulterated sweet orange juices using principal component regression (PCR) and partial least-squares regression (PLS). The PLS model has provided suitable estimation errors. SN - 1520-5118 UR - https://www.unboundmedicine.com/medline/citation/22423971/Chemometric_characterization_of_fruit_juices_from_Spanish_cultivars_according_to_their_phenolic_compound_contents:_I__Citrus_fruits_ L2 - https://doi.org/10.1021/jf300022u DB - PRIME DP - Unbound Medicine ER -