English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/174906
logo share SHARE   Add this article to your Mendeley library MendeleyBASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Data on fatty acid profiles of green Spanish-style Gordal table olives studied by compositional analysis

AuthorsGarrido Fernández, A. ; Cortés Delgado, Amparo ; López-López, Antonio
KeywordsCompositional data analysis
Fat extraction
Green table olive processing
Fatty acid
Issue DateFeb-2018
CitationData in Brief 16: 231-238 (2018)
AbstractThis article contains processed data related to the research published in “Tentative application of compositional data analysis to fatty acid profiles of green Spanish-style Gordal table olives” (Garrido-Fernández et al., 2018) [1]. It provides information on the implementation of compositional data analysis (CoDa) to the fatty acid profiles of Spanish-style Gordal table olives vs the use of conventional statistical analysis (data composition expressed in percentages). Particularly, it includes: i) the matrix of the sequential binary partition used for the balance estimation and the isometric log-ratio transformation (ilr) of the fatty acid profiles, ii) correlation among the diverse fatty acids expressed in percentages and their significances, iii) the ilr transformed values (coordinates in the Euclidean space) obtained following the sequential binary partition previously detailed, iv) the graphical presentation in the Simplex (ternary centred plot) of the treatments as a function of the four fatty acids with the higher log-ratio variances, and v) segregation of treatments based on Cluster Analysis.
Description8 Páginas; 3 Tablas; 2 Figuras
Publisher version (URL)http://dx.doi.org/10.1016/j.dib.2017.11.038
Appears in Collections:(IG) Artículos
Files in This Item:
File Description SizeFormat 
DataBrief_2018_V16_P231.pdfArtículo principal230,56 kBAdobe PDFThumbnail
Show full item record
Review this work

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.