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Technological classification of basque cider apple cultivars according to their polyphenolic profiles by pattern recognition analysis.
J Agric Food Chem. 2004 Dec 29; 52(26):8006-16.JA

Abstract

The polyphenolic compositions of 31 Basque cider apple cultivars were determined in pulp, peel, and juice by high-performance liquid chromatography--diode array detection analysis of crude extracts and after thiolysis. Data sets, consisting of individual polyphenol concentrations, total procyanidin content, and the average degree of polymerization of procyanidins, were evaluated by multivariate chemometric techniques, to develop decision rules for classifying apple cultivars technologically into bitter and nonbitter categories. A preliminary study of the data structure was performed by cluster analysis and principal component analysis in each apple material. Bitter apple varieties presented higher contents of flavan-3-ols and/or dihydrochalcones than nonbitter cultivars. Different classification systems for the two categories on the basis of the chemical data were obtained applying several supervised pattern recognition procedures, such as linear discriminant analysis, K-nearest neighbors, soft independent modeling of class analogy, partial least-squares, and multilayer feed forward artificial neural networks. Excellent performance in terms of recognition and prediction abilities for both categories (100% of hits) was achieved in every case (pulp, peel, or juice). Polyphenolic profiles of apple pulp, peel, or juice provide enough information to develop classification criteria for establishing the technological group of apple cultivars (bitter or nonbitter).

Authors+Show Affiliations

Departamento de Química Analítica, Facultad de Ciencias, Universidad del País Vasco/Euskal Herriko Unibertsitatea, P.O. Box 644, E-48080 Bilbao, Spain.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

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

Language

eng

PubMed ID

15612789

Citation

Alonso-Salces, Rosa M., et al. "Technological Classification of Basque Cider Apple Cultivars According to Their Polyphenolic Profiles By Pattern Recognition Analysis." Journal of Agricultural and Food Chemistry, vol. 52, no. 26, 2004, pp. 8006-16.
Alonso-Salces RM, Herrero C, Barranco A, et al. Technological classification of basque cider apple cultivars according to their polyphenolic profiles by pattern recognition analysis. J Agric Food Chem. 2004;52(26):8006-16.
Alonso-Salces, R. M., Herrero, C., Barranco, A., Berrueta, L. A., Gallo, B., & Vicente, F. (2004). Technological classification of basque cider apple cultivars according to their polyphenolic profiles by pattern recognition analysis. Journal of Agricultural and Food Chemistry, 52(26), 8006-16.
Alonso-Salces RM, et al. Technological Classification of Basque Cider Apple Cultivars According to Their Polyphenolic Profiles By Pattern Recognition Analysis. J Agric Food Chem. 2004 Dec 29;52(26):8006-16. PubMed PMID: 15612789.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Technological classification of basque cider apple cultivars according to their polyphenolic profiles by pattern recognition analysis. AU - Alonso-Salces,Rosa M, AU - Herrero,Carlos, AU - Barranco,Alejandro, AU - Berrueta,Luis A, AU - Gallo,Blanca, AU - Vicente,Francisca, PY - 2004/12/23/pubmed PY - 2005/1/27/medline PY - 2004/12/23/entrez SP - 8006 EP - 16 JF - Journal of agricultural and food chemistry JO - J Agric Food Chem VL - 52 IS - 26 N2 - The polyphenolic compositions of 31 Basque cider apple cultivars were determined in pulp, peel, and juice by high-performance liquid chromatography--diode array detection analysis of crude extracts and after thiolysis. Data sets, consisting of individual polyphenol concentrations, total procyanidin content, and the average degree of polymerization of procyanidins, were evaluated by multivariate chemometric techniques, to develop decision rules for classifying apple cultivars technologically into bitter and nonbitter categories. A preliminary study of the data structure was performed by cluster analysis and principal component analysis in each apple material. Bitter apple varieties presented higher contents of flavan-3-ols and/or dihydrochalcones than nonbitter cultivars. Different classification systems for the two categories on the basis of the chemical data were obtained applying several supervised pattern recognition procedures, such as linear discriminant analysis, K-nearest neighbors, soft independent modeling of class analogy, partial least-squares, and multilayer feed forward artificial neural networks. Excellent performance in terms of recognition and prediction abilities for both categories (100% of hits) was achieved in every case (pulp, peel, or juice). Polyphenolic profiles of apple pulp, peel, or juice provide enough information to develop classification criteria for establishing the technological group of apple cultivars (bitter or nonbitter). SN - 0021-8561 UR - https://www.unboundmedicine.com/medline/citation/15612789/Technological_classification_of_basque_cider_apple_cultivars_according_to_their_polyphenolic_profiles_by_pattern_recognition_analysis_ L2 - https://doi.org/10.1021/jf048995i DB - PRIME DP - Unbound Medicine ER -