2009
Quantification of Fructo-Oligosaccharides Based on the Evaluation of Oligomer Ratios using an Artificial Neural Network
ONOFREJOVÁ, Lucia, Marta FARKOVÁ a Jan PREISLERZákladní údaje
Originální název
Quantification of Fructo-Oligosaccharides Based on the Evaluation of Oligomer Ratios using an Artificial Neural Network
Název česky
Kvantifikace fruktooligosacharidů založená na vyhodnocení poměrů oligomerů pomocí umělých neuronových sítí
Autoři
ONOFREJOVÁ, Lucia (203 Česká republika), Marta FARKOVÁ (203 Česká republika) a Jan PREISLER (203 Česká republika, garant)
Vydání
Analytica Chimica Acta, AMSTERDAM, NETHERLANDS, Elsevier, 2009, 0003-2670
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10406 Analytical chemistry
Stát vydavatele
Nizozemské království
Utajení
není předmětem státního či obchodního tajemství
Impakt faktor
Impact factor: 3.757
Kód RIV
RIV/00216224:14310/09:00029382
Organizační jednotka
Přírodovědecká fakulta
UT WoS
000265333300011
Klíčová slova anglicky
quantification; artificial neural networks (ANN); matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF MS); fructo-oligosaccharides; internal standard
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 27. 6. 2009 23:48, prof. Mgr. Jan Preisler, Ph.D.
V originále
The application of an internal standard in quantitative analysis is desirable in order to correct for variations in sample preparation and instrumental response. In mass spectrometry of organic compounds, the internal standard is preferably labelled with a stable isotope, such as 18O, 15N or 13C. In this study, a method for the quantification of fructo-oligosaccharides using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF MS) was proposed and tested on raftilose, a partially hydrolysed inulin with a degree of polymeration 2-7. A tetraoligosaccharide nystose, which is chemically identical to the raftilose tetramer, was used as an internal standard rather than an isotope-labelled analyte. Two mathematical approaches used for data processing, conventional calculations and artificial neural networks (ANN), were compared. The conventional data processing relies on the assumption that a constant oligomer dispersion profile will change after the addition of the internal standard and some simple numerical calculations. On the other hand, ANN was found to compensate for a non-linear MALDI response and variations in the oligomer dispersion profile with raftilose concentration. As a result, the application of ANN led to lower quantification errors and excellent day-to-day repeatability compared to the conventional data analysis. The developed method is feasible for MS quantification of raftilose in the range of 10-750 pg with errors below 7 %. The content of raftilose was determined in dietary cream; application can be extended to other similar polymers. It should be stressed that no special optimisation of the MALDI process was carried out. A common MALDI matrix and sample preparation were used and only the basic parameters, such as sampling and laser energy, were optimised prior to quantification.
Česky
Viz popis v anglickém jazyce.
Návaznosti
| GA525/06/0663, projekt VaV |
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| LC06035, projekt VaV |
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| MSM0021622415, záměr |
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