Influence of Growing Region on Fatty Acids and Sterol Composition of Iranian Olive Oils by Unsupervised Clustering Methods

• Published in: Journal of the American Oil Chemists' Society 2012-03, Vol.89 (3), p.371-378
• Main Authors: Piravi-Vanak, Z, Ghasemi, Jahan B, Ghavami, M, Ezzatpanah, H, Zolfonoun, E
• Format: Article
• Language: English
• Subjects: Agriculture; altitude; beta-sitosterol; Biological and medical sciences; Biomaterials; Biotechnology; Chemistry; Chemistry and Materials Science; Chemometrics analysis; climate; Cluster analysis; Fat industries; Fatty acid; Fatty acids; Food industries; Food Science; Fundamental and applied biological sciences. Psychology; Geographical positions; Geography; humidity; Industrial Chemistry/Chemical Engineering; linoleic acid; oleic acid; Olive oil; olives; Original Paper; palmitic acid; principal component analysis; Principal components analysis; rain; Sterol; temperature; Trees
• ISSN: 0003-021X; 1558-9331
• DOI: 10.1007/s11746-011-1922-9

Twenty seven Iranian olive oil samples were collected from different provinces to evaluate fatty acids and sterol compositions. The samples were collected from different geographical locations that varied in altitude, temperature, humidity and rain fall. The sample collected from the northern part of Iran by the Caspian Sea had higher oleic acid [G₂ sample (75.98%)] and lower linoleic acid [Go₅ sample (6.5%)] and palmitic acid [G₂ sample (10.78%)] concentrations than samples from the southern part of the country such as F₁ whose contents of C16:0, C18:1 and C18:2 were 15.27, 62.73 and 16.09%, respectively, in the southern part, the climate is dry and the temperature variation is wider and the elevation is 1,488 m. The results indicated that oleic acid was the predominant fatty acid with 62.7% for F₁ sample in the warmer climate at the south of Iran to 76.0% for G₂ sample in the cooler climate in the north of Iran. According to the results, the highest content of β-sitosterol was 87% related to samples G₉ and Z₃ from the north of Iran and the lowest content was 69.95% related to sample F₁–₂₄ from the south of Iran. Clustering techniques such as principal component analysis and hierarchical cluster analysis were carried out on olive composition data to show similarities and discrimination between samples as a function of the cultivation zone. The two methods applied clearly showed the effect of growing regions on the distribution of the olive oil samples in the high dimensional space created by fatty acid and sterol compositions.