Recent trends in multi-block data analysis in chemometrics for multi-source data integration

In recent years, multi-modal measurements of process and product properties have become widely popular. Sometimes classical chemometric methods such as principal component analysis (PCA) and partial least squares regression (PLS) are not adequate to analyze this kind of data. In recent years, several multi-block methods have emerged for this purpose; however, their use is largely limited to chemometricians, and non-experts have little experience with such methods. In order to deal with this, the present review provides a brief overview of the multi-block data analysis concept, the various tasks that can be performed with it and the advantages and disadvantages of different techniques. Moreover, basic tasks ranging from multi-block data visualization to advanced innovative applications such as calibration transfer will be briefly highlighted. Finally, a summary of software resources available for multi-block data analysis is provided

Independent components analysis with the JADE algorithm – Why ICA"

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Quelques extensions de la méthode ComDim

Quelques extensions de la méthode ComDim. 5. journées de statistique

Multi-block data analysis: new extensions and applications in chemometrics

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Independent components analysis: theory and applications

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Independent components analysis with the JADE algorithm – Why ICA"

absen

Quelques extensions de la méthode ComDim

Quelques extensions de la méthode ComDim. 5. journées de statistique

Independent components analysis with the JADE algorithm

absen

Fluorescence spectroscopy for monitoring rapeseed oil upon heating

The aim of this work was to determine the heating effect on the thermo-degradation process of rapeseed oil (RO) by rapid fluorescence method. Reference measurements were carried out by chromatographic methods in order to compare results with those obtained by fluorescence spectroscopy. The main compounds which were monitored are polar compounds and tocopherols. During heating process, two temperatures were used: 171°C and 189°C for 4.5 h. The results have showed that the tocopherol content decreases, especially at the highest temperature, and the polar content increases of 20% at the end of heating. These results are in agreement with literature. PLS model was built in order to predict polar and tocopherol contents. The results obtained from this method were satisfactory

Common components analysis: a new (?) exploratory data analysis method

Common components analysis: a new (?) exploratory data analysis method. Chimiométrie XVIII 201