Fatty Acids-Based Quality Index to Differentiate Worldwide Commercial Pistachio Cultivars

Abstract

The fatty-acid profiles of five main commercial pistachio cultivars, including Ahmad-Aghaei, Akbari, Chrok, Kalle-Ghouchi and Ohadi, were determined by gas chromatography: palmitic (C16:0), palmitoleic (C16:1), stearic (C18:0), oleic (C18:1), linoleic (C18:2), linolenic (C18:3) arachidic (C20:0) and gondoic (C20:1) acid. Based on the oleic to linoleic acid (O/L) ratio, a quality index was determined for these five cultivars: Ohadi (2.40) < Ahmad-Aghaei (2.60) < Kale-Ghouchi (2.94) < Chrok (3.05) < Akbari (3.66). Principal component analysis (PCA) of the fatty-acid data yielded three significant PCs, which together account for 80.0% of the total variance in the data set. A linear discriminant analysis (LDA) model evaluated with cross validation correctly classified almost all samples: the average percent accuracy for the prediction set was 98.0%. The high predictive power for the prediction set shows the ability to indicate the cultivar of an unknown sample based on its fatty-acid chromatographic fingerprint.

Edible Plant Oil: Global Status, Health Issues, and Perspectives

“…A fatty acid is an organic substance consisting of a long aliphatic hydrocarbon chain that contains one carboxyl group at one end. Fatty acids are divided into saturated fatty acids (SFAs) and UFAs ( Esteki et al, 2018 ). The human body can synthesize the required SFAs and UFAs with only one double bond.…”

“…Overall, the global production of major EPO is increasing annually ( Table 3 ). Palm oil is mainly produced in southeastern Asia, including Malaysia and Indonesia ( Figure 1A ) ( Esteki et al, 2018 ). In 2016, palm oil from Indonesia and Malaysia was accounted for approximately 85% of global palm oil production, including palm kernel oil.…”

Variation in secondary metabolites in a unique set of tomato accessions collected in Turkey

“…This approach can be used for food quality analysis (Capanoglu et al, 2010;Thissen et al, 2011;Wishart, 2008) and also, food safety aspects such as investigating the presence of pesticide residues, veterinary drugs, natural toxins, environmental contaminants and contaminants arising from food processing (Castro-Puyana, Perez-Miguez, Montero, & Herrero, 2017;Pinu, 2016). Adulteration and fraud in foods have also been revealed through metabolite profiling of materials using similar chromatographic techniques and, metabolites can be used as indicators for the provenance of food materials in terms of their origin (Tolstikov & Fiehn, 2002;Esteki, Ahmadi, Heyden, & Simal-Gandara, 2019;Esteki, Regueiro, & Simal-Gandara, 2019;Esteki, Shahsavari, & Simal-Gandara, 2019a, 2019b and post-harvest history (Thurman et al, 2005) as well as fraudulent deception of consumers regarding their purity and adulteration (Wishart, 2008;Esteki, Farajmand, Kolahderazi, & Simal-Gandara, 2017;Moldes, Mejuto, Rial-Otero, & Simal-Gandara, 2017). In the literature, there are few studies indicating the combined use of spectrophotometric techniques and multivariate analysis in order to identify food classification, authentication and adulteration Astray et al, 2019;Gonzalez-Fernandez et al, 2019).…”