Practical method for the confirmation of authentic flours of different types of cereals and pseudocereals

Ačanski, Marijana; Vujić, Djura; Psodorov, Djordje

doi:10.1016/j.foodchem.2014.09.068

Cited by 10 publications

(3 citation statements)

References 16 publications

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“…The residue was first dissolved in 400 μL of dichloromethane, and then 100 µL of 0.2 M trimethylsulfonium hydroxide in methanol (TMSH, Macherey-Nagel) was added, thus performing a derivatization into volatile methyl esters (Macherey-Nagel). 55…”

Section: Samplingmentioning

confidence: 99%

Discriminating cereal and pseudocereal species using a binary system of GC/MS data: A pattern recognition approach

Pastor

Pezo

Vujić³

et al. 2018

JSCS

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Various cultivars of different cereal and pseudocereal species (9 wheat, 8 barley, 1 rye, 3 oat, 2 triticale, 3 spelt, 12 corn, 3 amaranth and 9 buckwheat cultivar samples) were milled into flour, extracted using n-hexane, derivatized with trimethylsulfonium hydroxide solution, and subjected to GC-MS analysis. Fatty acid methyl esters and non-saponifiable compounds (phytosterols, α-tocopherol and squalene) were identified by comparing mass spectra with the Wiley MS library. A binary system was applied in further data processing: the presence or the absence of a particular lipid component in each sample was coded with either (1) or (0). Major lipid components that were present in all analyzed flour samples were removed from further data analysis, leaving only those that represent a good pattern to differentiate the flour samples according to corresponding cereal/pseudocereal species. Pattern recognition tools (cluster analysis and principal component analysis) were applied to visualize groupings and separations among the samples. The presented approach enables the rapid differentiation of flour samples made from various cereal/pseudocereal species according to their botanical origin and gluten content, thereby, successfully avoiding exact quantitative determinations.

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Section: Samplingmentioning

confidence: 99%

Discriminating cereal and pseudocereal species using a binary system of GC/MS data: A pattern recognition approach

Pastor

Pezo

Vujić³

et al. 2018

JSCS

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“…The temperature of the injector was 250 °C, and the helium flow, as a gas carrier, was 1.1563 ml•min -1 . One μl of a solution from every analyzed sample was injected with the split--ratio of 1:50 [23,24].…”

Section: Gc-ms Analysismentioning

confidence: 99%

Fatty acid profile changes in Ricotta-filled pastry during storage investigated by a GC/MS-ANOVA

Psodorov

Lazić

Ačanski

et al. 2018

CI&CEQ

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Fatty acid composition of Ricotta cheese filled bakery product was examined using a GC-MS method immediately after production and packaging in the case of a control sample, and after production, packaging under air atmosphere in a seven-layer packaging material consisting of PE/Ad/PA/Ad/PE/Ad/PET, and storing during a four weeks period at room temperature, in the case of the experimental samples. The statistical significance of the fatty acid profile change was examined using ANOVA method. The results of this research showed that there are no significant changes of fatty acids composition and content after defined storing period, with the exception of diunsaturated cis,cis-9,12-octadecadienoic (linoleic) acid, whose average content was reduced by 83.705%. However, a small amount of linoleic acid was converted to cis,trans-9,11-octadecadienoic (conjugated linoleic) acid. Therefore, it could be considered as appropriate to pack and storage Ricotta-filled pastry for the period of four weeks, considering the insignificant changes of fatty acid composition and content.

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“…Minor fatty acids are: eicosanoic (arachidic 20:0), eicosenoic (C20:1) and docosanoic (behenic, 22:0). In previous studies [12,13] it has been proven that it is possible to unambiguously distinguish buckwheat flour from wheat flour, based on GC-MS and multivariate analysis of characteristic ions of (1) simple sugars in alcoholic extracts of flour samples, and (2) fatty acid methyl esters and non-saponifiable components in fatsoluble (hexane) extracts of flour samples. Previous research has also shown that it is possible to determine the content of buckwheat flour in crusts and crumbs of bread samples with addition of buckwheat flour, based on the content of simple sugars and methyl esters of dominant fatty acids [14,15].…”

Section: Introductionmentioning

confidence: 99%

Determination of the presence of buckwheat flour in bread by the analysis of minor fatty acid methyl esters

Ačanski¹,

Pastor²,

Psodorov³

et al. 2015

Adv techn

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Five samples of bread were prepared by mixing wheat and buckwheat flour. The buckwheat flour content was raised from 0, 20, 40, 50 to 60%. Fatty acids were extracted with hexane from crusts and crumbs of bread, and afterwards derivatised with TMSH (trimethylsulfonium hydroxide in methanol) into corresponding methyl esters and subjected to the analysis on a GC-MS device. Only the areas of methyl esters of the minor fatty acids: eicosenoic (C20:1), eicosanoic (C20:0) and docosanoic (C22:0) acid, were integrated. Multivariate analysis was applied for data processing. The results show that it is possible to determine the presence of buckwheat flour in crusts and crumbs of bread, successfully avoiding the need for quantitative determinations.

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Practical method for the confirmation of authentic flours of different types of cereals and pseudocereals

Cited by 10 publications

References 16 publications

Discriminating cereal and pseudocereal species using a binary system of GC/MS data: A pattern recognition approach

Discriminating cereal and pseudocereal species using a binary system of GC/MS data: A pattern recognition approach

Fatty acid profile changes in Ricotta-filled pastry during storage investigated by a GC/MS-ANOVA

Determination of the presence of buckwheat flour in bread by the analysis of minor fatty acid methyl esters

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