Exploring the volatile metabolome of conventional and organic walnut oils by solid-phase microextraction and analysis by GC-MS combined with chemometrics

Kalogiouri, Natasa P.; Manousi, Natalia; Rosenberg, Erwin; Zachariadis, George A.; Paraskevopoulou, Adamantini; Samanidou, Victoria

doi:10.1016/j.foodchem.2021.130331

Cited by 49 publications

(31 citation statements)

References 31 publications

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“…Partial least squares discriminant analysis (PLS-DA) is a supervised pattern recognition technique used to find the appropriate class for each sample ( 20 ). In PLS-DA a mathematical model is built to establish a correlation and classify the samples, knowing the label of each class ( 25 ). A PLS-DA prediction model was developed using the MetaboAnalyst 5.0 platform ( 26 ) to discover patterns in the chromatographic data of the truffles species, establishing the most important volatile markers responsible for their discrimination.…”

Section: Methodsmentioning

confidence: 99%

Headspace Solid-Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry as a Powerful Analytical Tool for the Discrimination of Truffle Species According to Their Volatiles

et al. 2022

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This study provides the first assessment of the volatile metabolome map of Tuber Aestivum and Tuber Borchii originating from Greece using headspace solid-phase micro-extraction (HS-SPME) coupled to gas chromatography-mass spectrometry (GC-MS). For the extraction of the volatile fraction, the SPME protocol was optimized after examining the effects of sample mass, extraction temperature, and extraction time using the one-variable at-a-time approach (OVAT). The optimum parameters involved the extraction of 100 mg of homogenized truffle for 45 min at 50°C. Overall, 19 truffle samples were analyzed, and the acquired data were normalized and further processed with chemometrics. Agglomerative hierarchical clustering (HCA) was used to identify the groups of the two species. Partial least squares–discriminant analysis (PLS-DA) was employed to develop a chemometric model that could discriminate the truffles according to the species and reveal characteristic volatile markers for Tuber Aestivum and Tuber Borchii grown in Greece.

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Section: Methodsmentioning

confidence: 99%

Headspace Solid-Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry as a Powerful Analytical Tool for the Discrimination of Truffle Species According to Their Volatiles

et al. 2022

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“…They are also essential indicators of geographical origins. Although VOC metabolites have been studied in various food authenticity studies, such as geographic [ 1 , 4 , 14 ] and botanical origin identification [ 15 , 16 , 17 ], a method for quick identification of the geographic origin of rice from a different region is still lacking. Therefore, in the current study, a non-targeted VOC metabolomics method was applied to study the phenotype of rice from Heilongjiang, Jilin, and Liaoning provinces.…”

Section: Introductionmentioning

confidence: 99%

Fingerprinting of Volatile Organic Compounds for the Geographical Discrimination of Rice Samples from Northeast China

Asimi

Ren

Zhang

et al. 2022

Foods

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Rice’s geographic origin and variety play a vital role in commercial rice trade and consumption. However, a method for rapidly discriminating the geographical origins of rice from a different region is still lacking. Therefore, the current study developed a volatile organic compound (VOC) based geographical discrimination method using headspace gas chromatography-mass spectrometry (HS-GC-MS) to discriminate rice samples from Heilongjiang, Jilin, and Liaoning provinces. The rice VOCs in Heilongjiang, Liaoning, and Jilin were analyzed by agglomerative hierarchical clustering (AHC), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the optimum parameters for headspace solid phase microextraction (HS-SPME) involved the extraction of 3.0 g of rice at 80 °C within 40 min. A total of 35 VOCs were identified from 30 rice varieties from Northeast China. The PLS-DA model exhibited good discrimination (R2 = 0.992, Q2 = 0.983, and Accuracy = 1.0) for rice samples from Heilongjiang, Liaoning, and Jilin. Moreover, K-nearest neighbors showed good specificity (100%) and accuracy (100%) in identifying the origin of samples. In conclusion, the present study established VOC fingerprinting as a highly efficient approach to identifying rice’s geographical origin. Our findings highlight the ability to discriminate rice from Heilongjiang, Liaoning, and Jilin provinces rapidly.

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“…Even though walnuts are high-value agricultural products that provide energy, all the necessary nutrients ingredients and have beneficial health effects, they have not been adequately studied in terms of authenticity compared to other food products [14]. This gap has to be filled with the development of analytical methodologies that enable the determination of walnut constituents that could potentially be used as markers for the guarantee of walnuts genuineness.…”

Section: Introductionmentioning

confidence: 99%

“…The majority of the published articles focus mainly on the development of methodologies for the assessment of the mineral [5,15,16], lipid [6,[17][18][19] or volatile profile [14,20] of walnuts [21,22]. Less is known about the minor phenolic fraction [8,23].…”

Section: Introductionmentioning

confidence: 99%

HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents

Kalogiouri

Samanidou

2021

Foods

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A high-pressure liquid chromatographic method coupled to diode array detector (HPLC-DAD) was developed for the determination of phenolic compounds that could be used as markers in authentication studies of walnuts belonging to the Chandler variety, originating from Bulgaria, Greece, and France. An ultrasound-assisted extraction (UAE) protocol applied in the extraction of phenolic compounds was optimized. The method was validated and the relative standard deviations (RSD%) of the within-day, and between-day assays was lower than 6.3 and 11.1, respectively, showing adequate precision, and good accuracy ranging from 86.4 (sinapic acid) to 98.4% (caffeic acid) for within-day assay, and from 90.1 (gallocatechin gallate) to 100.6% (gallic acid) for between-day assay. Eighteen phenolic compounds were determined belonging to the classes of phenolic acids and flavonoids. The quantification results were further processed with chemometrics, and a robust partial least square–discriminant analysis (PLS-DA) model was developed for the classification of the samples according to their geographical origin, proposing markers that could be used for the control of walnuts authenticity and the detection of fraudulent incidents.

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Exploring the volatile metabolome of conventional and organic walnut oils by solid-phase microextraction and analysis by GC-MS combined with chemometrics

Cited by 49 publications

References 31 publications

Headspace Solid-Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry as a Powerful Analytical Tool for the Discrimination of Truffle Species According to Their Volatiles

Headspace Solid-Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry as a Powerful Analytical Tool for the Discrimination of Truffle Species According to Their Volatiles

Fingerprinting of Volatile Organic Compounds for the Geographical Discrimination of Rice Samples from Northeast China

HPLC Fingerprints for the Characterization of Walnuts and the Detection of Fraudulent Incidents

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