Optimisation of gradient HPLC analysis of phenolic compounds and flavonoids in beer using a CoulArray detector

Řehová, Lucie; Škeříková, Veronika; Jandera, Pavel

doi:10.1002/jssc.200401916

Cited by 44 publications

(15 citation statements)

References 40 publications

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“…According to our previous experience [64,65] ammonium acetate and formic acid provide sufficient buffer capacity and lower gradient base-line noise in comparison to formate -formic acid or acetate -acetic acid buffers. The pH of the buffer was measured in aqueous solutions, before the addition of organic solvent.…”

Section: Materials and Reagentsmentioning

confidence: 98%

Development of different comprehensive two dimensional systems for the separation of phenolic antioxidants

Cacciola

Jandera²,

Blahová

et al. 2006

J of Separation Science

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Three different comprehensive 2-D HPLC systems for the separation of phenolic antioxidants have been developed on the basis of different selectivities of a PEG-silica column in the first dimension and a packed or monolithic C18 or a ZR-CARBON column, respectively, in the second dimension. Two-dimensional comprehensive liquid chromatography using a serially connected short PEG-silica column and a conventional C18-silica or a ZR-CARBON column in the second dimension was tested to improve the resolution of the earlier eluting compounds in the first dimension. Various types of interface were used to connect the columns in the first and in the second dimension: i) two injection sampling loops of 100 microL in conventional arrangement; ii) a 10-port 2-position valve equipped with two trapping X-Terra columns instead of loops; and iii) two analytical D2 columns in parallel. The mobile phase in the first dimension has a lower elution strength than in the second dimension, allowing band compression of the solutes transferred from the first to the second dimension. This effect was enhanced using trapping columns instead of sampling loops as the interface between the two dimensions, thus allowing a decrease in the time of analysis. These systems were used for the analysis of beer samples. The relative location of the components in the 2-D retention plane varied in relation to their chemical structure in each instrumental set-up and allowed positive peak identification.

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Section: Materials and Reagentsmentioning

confidence: 98%

Development of different comprehensive two dimensional systems for the separation of phenolic antioxidants

Cacciola

Jandera²,

Blahová

et al. 2006

J of Separation Science

Self Cite

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show abstract

“…In our previous work [39], we used resolution maps for the individual sample components and the "normalized resolution product", r, related to the average resolution taken over all the peaks in the chromatogram, R av , as the separation quality criteria. (r reflects the regularity of peak spacing over the chromatogram and varies from 0 to 1, r = 0 when one or more peaks co-elute and r = 1 when all the pairs of peaks show the same resolution in the chromatogram [40 -41]).…”

Section: Optimization Of the Separation Conditionsmentioning

confidence: 99%

“…(r reflects the regularity of peak spacing over the chromatogram and varies from 0 to 1, r = 0 when one or more peaks co-elute and r = 1 when all the pairs of peaks show the same resolution in the chromatogram [40 -41]). Based on the earlier comparison of the suitability of 11 different stationary phases for simultaneous analysis of 32 flavonoids and phenolic antioxidants [39], we selected four columns providing best separation for the analysis of various types of samples in the present work. We used the "normalized resolution product", r, and the overlapping resolution maps to optimize the pH (in the range from 2.74 to 4.4), the flow rate, and the gradient program.…”

Section: Optimization Of the Separation Conditionsmentioning

confidence: 99%

“…As the oxidation potentials of the free acid forms of the antioxidants may differ from the oxidation potentials of their anionic forms, the mobile phase pH affects the response of the coulometric detectors [39]. Figure 2.A -C show the effect of pH on the peak areas of epicatechin, sinapic, and syringic acids.…”

Section: Optimization Of Detection Conditions With the Coularray Detementioning

confidence: 99%

“…Recently, we presented an optimised method for the analysis of 27 phenolic and flavonoid antioxidants in beer using gradient HPLC with CoulArray detection [39]. In the present work, we adapted this method for the analysis of 32 natural antioxidants in various beverages, including beer, wine, tea, and plant extracts.…”

Section: Introductionmentioning

confidence: 98%

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RP‐HPLC analysis of phenolic compounds and flavonoids in beverages and plant extracts using a CoulArray detector

Jandera¹,

Škeříková²,

Řehová³

et al. 2005

J of Separation Science

Self Cite

109

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Methods were developed for the analysis of natural antioxidants including phenolic compounds and flavonoids in beverages and plant extracts using gradient HPLC with multi-channel electrochemical coulometric detection. Suitability of various reversed-phase columns for this purpose was compared; pH and mobile phase gradients were optimized with respect to the separation selectivity and sensitivity of detection. Because of different target compounds in various sample types, the overlapping resolution maps and the normalized resolution product approaches described earlier were used to select optimum columns and gradients to suit the analysis of the individual sample types. The methods were applied to the analysis of phenolic compounds and flavonoids in beer, wine, tea, and yacon extracts. 32 phenolic compounds were identified and determined, including derivatives of benzoic and cinnamic acids, flavones, and a few related glycosides. Eight-channel CoulArray detection offers high selectivity and sensitivity with limits of detection in the low microg L(-1) range, at least an order of magnitude lower than single-channel coulometric detection using the Coulochem detector. No special sample pretreatment is necessary and, because of the compatibility of the CoulArray detector with gradient elution, phenolic antioxidants of different polarities can be determined in a single run. In addition to the retention times, the ratios of the areas of the pre-dominant and post-dominant peaks to the area of the dominant peak can be used for improved identification of natural antioxidants.

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Strategies in the Analysis of Plant Flavonoids

Santos‐Buelga

Gonzaléz-Paramás

2014

Encyclopedia of Analytical Chemistry

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Flavonoids are one of the largest groups of plant secondary metabolites. They comprise several thousand compounds that share a phenylchromane skeleton and can be classified into different classes, namely flavones, flavonols, flavanones, flavanols, anthocyanins, dihydroflavonols, isoflavones, and chalcones. Flavonoids occur in their natural sources as aglycones or glycosylated forms and as monomers or constituting polymerized structures and can be found both as free and matrix‐bound compounds. This structural diversity affects their physicochemical behavior, and different flavonoid classes and compounds may have different requisites for their extraction and analysis, so that there is not a unique analytical strategy that applies in all situations. In this chapter, the main methodological approaches to the analysis of flavonoids in plant materials are revised paying particular attention to more recent extraction techniques and high performance liquid chromatography‐based methodologies that currently dominate the field of flavonoid analysis.

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Optimisation of gradient HPLC analysis of phenolic compounds and flavonoids in beer using a CoulArray detector

Cited by 44 publications

References 40 publications

Development of different comprehensive two dimensional systems for the separation of phenolic antioxidants

Development of different comprehensive two dimensional systems for the separation of phenolic antioxidants

RP‐HPLC analysis of phenolic compounds and flavonoids in beverages and plant extracts using a CoulArray detector

Strategies in the Analysis of Plant Flavonoids

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