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Exploratory chemometric analysis for the characterisation of Tunisian olive cultivars according to their lipid and sterolic profiles
Author(s) -
Kammoun Naziha G.,
Zarrouk Wissem
Publication year - 2012
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/j.1365-2621.2012.02997.x
Subject(s) - cultivar , principal component analysis , linear discriminant analysis , linoleic acid , olive oil , mathematics , chemometrics , campesterol , fatty acid , biology , food science , horticulture , botany , chemistry , statistics , sterol , chromatography , cholesterol , biochemistry
Summary This study aims to evaluate some Tunisian olive genetic resources using fatty acid, triacyglycerol and sterolic compositions and to classify the cultivars according to their fruit genotype and to their respective geographical origin (North, Centre and South). manova results showed that the studied cultivars presented highly significant differences regarding all the variables ( P < 0.01). The most discriminant variables of fatty acids are C17:1 ( F = 98.468), C16:0 ( F = 92.994), C18:1 ( F = 60.865), C18:1/C18:2 ( F = 44.632) and C18:2 ( F = 40.167); those of triacylglycerols are POP ( F = 123.34), LLL ( F = 122.944), LnLO ( F = 98.363), POO ( F = 93.357) and LOO ( F = 90.42), while sitostanol ( F = 289.171), campestanol ( F = 192.792) and campesterol ( F = 160.724) have the higher discriminant power among sterol compounds. Principal component analysis (PCA) was performed on the data of each chemical parameter to explore their usefulness for the discrimination of eleven monovarietal olive oils. Best differentiations among cultivars were obtained with triacyglycerol and sterolic compositions. The spatial distribution of the different oil samples using all the collected data showed a good discrimination among olive cultivars. A strong resolution between the samples according to the geographical origin was obtained by means of factorial discriminant analysis (FDA) (λ = 0.002). Comparisons of the distances between classes were statistically significant (Fisher tests; P < 0.0001), and 90.91% of cross‐validated grouped cases are correctly classified. The obtained results could become an important tool for sorting out oils to a single cultivar or to a specific geographical area.