Volatiles for mycological quality grading of barley grains: determinations using gas chromatography-mass spectrometry and electronic nose
| Autor: | T. Börjesson, J. Olsson, Johan Schnürer, T. Lundstedt |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Ergosterol
Chromatography Electronic nose Nonanal Analytical chemistry Fungi Hordeum General Medicine Mass spectrometry Microbiology Sensory analysis Gas Chromatography-Mass Spectrometry chemistry.chemical_compound chemistry Odor Odorants Gas chromatography Gas chromatography–mass spectrometry Volatilization Food Science |
| Zdroj: | International journal of food microbiology. 59(3) |
| ISSN: | 0168-1605 |
| Popis: | The possibility of using an electronic nose or gas chromatography combined with mass spectrometry (GC-MS) to quantify ergosterol and colony forming units (CFU) of naturally contaminated barley samples was investigated. Each sample was split into three parts for (i) ergosterol and CFU analysis, (ii) measurements with the electronic nose and (iii) identification of volatiles collected on an adsorbent with a GC-MS system. Forty samples were selected after sensory analysis to obtain 10 samples with normal odour and 30 with some degree of off-odour. The data set of volatile compounds and the data collected from the electronic nose were evaluated by multivariate analyse techniques. SIMCA classification (soft independent modelling of class analogy) was used for objective evaluation of the usefulness of the data from the GC-MS or electronic nose measurements for classification of grain samples as normal or with off-odour. The main volatile compounds of grain with normal odour were 2-hexenal, benzaldehyde and nonanal, while 3-octanone, methylheptanone and trimethylbenzene were the main volatile compounds of grain with off-odours. Using data from the electronic nose three samples of 40 were misclassified, while data analysis of the volatile compounds detected with the GC-MS, led to six misclassified samples. Regression models (partial least-squares, PLS) were built to predict ergosterol- and CFU-levels with data from the GC-MS or electronic nose measurements. PLS models based on both GC-MS and electronic nose data could be used to predict the ergosterol levels with high accuracy and with low root mean square error of prediction (RMSEP). CFU values from naturally infected grain could not be predicted with the same degree of confidence. |
| Databáze: | OpenAIRE |
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