Biomedical subjects

Jean-Louis Berdagué

Publications and source records attributed to Jean-Louis Berdagué.

3 recordsLinked to original sources

PubMed2006

Comprehensive combinatory standard correction: a calibration method for handling instrumental drifts of gas chromatography-mass spectrometry systems.

The current work describes a new method, the comprehensive combinatory standard correction (CCSC), for the correction of instrumental signal drifts in GC-MS systems. The method consists in analyzing together with the products of interest a mixture of n selected internal standards, and in normalizing the peak area of each analyte by the sum of standard areas and then, select among the summation operator sigma(p = 1)(n)C(n)p possible sums, the sum that enables the best product discrimination. The CCSC method was compared with classical techniques of data pre-processing like internal normalization (IN) or single standard correction (SSC) on their ability to correct raw data from the main drifts occurring in a dynamic headspace-gas chromatography-mass spectrometry system. Three edible oils with closely similar compositions in volatile compounds were analysed using a device which performance was modulated by using new or used dynamic headspace traps and GC-columns, and by modifying the tuning of the mass spectrometer. According to one-way ANOVA, the CCSC method increased the number of analytes discriminating the products (31 after CCSC versus 25 with raw data or after IN and 26 after SSC). Moreover, CCSC enabled a satisfactory discrimination of the products irrespective of the drifts. In a factorial discriminant analysis, 100% of the samples (n = 121) were well-classified after CCSC versus 45% for raw data, 90 and 93%, respectively after IN and SSC.

Analysis of Variance↗

PubMed2002

Standard gas addition: a calibration method for handling temporal drifts of mass spectrometry-based sensors.

This work describes a new method for the correction of signal drift of a MS-based sensor by standard gas addition (SGA). It consists of introducing a gaseous He-Xe mixture continuously and independently of the carrier gas into the mass spectrometer source. To mimic the disturbances generated by periodical tuning of the mass detector, three series of adjustments were made to the main acquisition parameters. The influence of the SGA signal correction on the discriminating power of the data was evaluated from the analysis of three batches of cheeses by dynamic headspace coupled to mass spectrometry. SGA afforded a good correction of the main types of drift classically observed in mass spectrometry.

Biosensing Techniques↗

PubMed2002

Fast characterization of cheeses by dynamic headspace-mass spectrometry.

This study describes a rapid method to characterize cheeses by analysis of their volatile fraction using dynamic headspace-mass spectrometry. Major factors governing the extraction and concentration of the volatile components were first studied. These components were extracted from the headspace of the cheeses in a stream of helium and concentrated on a Tenax TA trap. They were then desorbed by heating and injected directly into the source of a mass spectrometer via a short deactivated silica transfer line. The mass spectra of the mixture of volatile components were considered as fingerprints of the analyzed substances. Forward stepwise factorial discriminant analysis afforded a limited number of characteristic mass fragments that allowed a good classification of the batches of cheeses studied.

Cheese↗