A SNP-based PCR–RFLP capillary electrophoresis analysis for the identification of the varietal origin of olive oils

Bazakos, Christos; Dulger, Ayse Ozgur; Uncu, Ali Tevfik; Spaniolas, Stelios; Thodhoraq, Spano; Kalaitzis, Panagiotis

doi:10.1016/j.foodchem.2012.04.031

Cited by 46 publications

(58 citation statements)

References 27 publications

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“…40,41 Among the six SNPs used in the identification key, three were reported in previous work. SNP2, identified in the Chalcone synthase gene, was reported by Consolandi et al 25 SNP5, identified in the Cycloarthenol synthase gene, was also reported by Consolandi et al, 25 and Bazakos et al 21 In addition, we found that the SNP in the Calcium binding protein gene, first described by Reale et al, 24 was also polymorphic in Turkish germplasm and is referred to as SNP6 in this study. These results demonstrate that SNPs in olive coding sequences are conserved across the geography of olive distribution and can be useful for estimating ancestral alleles via phylogenetic analysis.…”

Section: Journal Of Agricultural and Food Chemistrysupporting

confidence: 82%

Cultivar Origin and Admixture Detection in Turkish Olive Oils by SNP-Based CAPS Assays

Uncu

Frary

Doğanlar

2015

J. Agric. Food Chem.

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The aim of this study was to establish a DNA-based identification key to ascertain the cultivar origin of Turkish monovarietal olive oils. To reach this aim, we sequenced short fragments from five olive genes for SNP (single nucleotide polymorphism) identification and developed CAPS (cleaved amplified polymorphic DNA) assays for SNPs that alter restriction enzyme recognition motifs. When applied on the oils of 17 olive cultivars, a maximum of five CAPS assays were necessary to discriminate the varietal origin of the samples. We also tested the efficiency and limit of our approach for detecting olive oil admixtures. As a result of the analysis, we were able to detect admixing down to a limit of 20%. The SNP-based CAPS assays developed in this work can be used for testing and verification of the authenticity of Turkish monovarietal olive oils, for olive tree certification, and in germplasm characterization and preservation studies.

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Section: Journal Of Agricultural and Food Chemistrysupporting

confidence: 82%

Cultivar Origin and Admixture Detection in Turkish Olive Oils by SNP-Based CAPS Assays

Uncu

Frary

Doğanlar

2015

J. Agric. Food Chem.

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“…Regarding monovarietal olive oil classification according to olive cultivar, other approaches have been described in the literature, reporting in some cases slightly less accurate correct classification performances (ranging from 70 to 100 %) depending on the analytical technique used (e.g., NMR, NIR, and MIR spectroscopy; PTR-MS; HS-SPME-GC/MS; SNP-based PCR-RFLP capillary electrophoresis; SNP-based CAPS assays), the number of olive cultivars under study (3,5, or 10 cultivars) and chemometric tool used (e.g., LDA PLS-DA and canonical discriminant analysis) [13,14,22,[50][51][52].…”

Section: Low-level Data Fusion Of Sensory Attributes and E-tongue Sigmentioning

confidence: 99%

“…Moreover, sensory evaluation is mainly used to classify olive oils as LOO, VOO, or EVOO according to their positive and/or negative organoleptic sensations. In the last years, several analytical approaches, ranging from expensive chromatographic [2,6,[9][10][11][12][13]]-, DNA [14]-, or nondestructive spectroscopy [15,16]-based methods to fast and low-cost electrochemical devices [3,13,[17][18][19], have been reported. These methods showed satisfactory predictive performances regarding olive oil quality assessment and classification, including the successful Abstract Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations).…”

Section: Introductionmentioning

confidence: 99%

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Dias

Rodrigues

Veloso

et al. 2015

Eur Food Res Technol

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sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

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“…The economic value of olive oils make this food product very prone to fraud, including mislabeling of olive oil commercial category, geographical or olive cultivar origin [3][4][5][6][7]. So, several gas-, liquid-and mass-spectrometry chromatography, DNA and spectroscopy based methods have been developed to assess olive oil quality and authenticity as well as to detect possible adulterations [3,5,6,[8][9][10][11][12][13][14][15][16]. Electrochemical sensors have also been extensively used, including electronic noses and electronic tongues (E-tongues), individually or in combination, mainly with the aim of identifying possible adulterations or classifying olive oils according to quality level, geographical origin or olive cultivar [16][17][18][19][20][21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Sensory intensity assessment of olive oils using an electronic tongue

Veloso

Dias

Rodrigues

et al. 2016

Talanta

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a b s t r a c tOlive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14 7 2 to 257 6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

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A SNP-based PCR–RFLP capillary electrophoresis analysis for the identification of the varietal origin of olive oils

Cited by 46 publications

References 27 publications

Cultivar Origin and Admixture Detection in Turkish Olive Oils by SNP-Based CAPS Assays

Cultivar Origin and Admixture Detection in Turkish Olive Oils by SNP-Based CAPS Assays

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Sensory intensity assessment of olive oils using an electronic tongue

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