Authenticating white grape must variety with classification models based on aroma sensors, FT-IR and UV spectrometry

Roussel, Sylvie; Maurel, Véronique Bellon; Roger, Jean‐Michel; Grenier, Pierre

doi:10.1016/s0260-8774(03)00064-5

Cited by 94 publications

(50 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simplest approach is to concatenate the different data sets in a low-level fusion approach where the data matrix results in a fused data table that is used for multivariate analysis. 38 This approach is greatly affected by disparate signal intensities in the range and size of the data matrix obtained from the different analytical platforms. In order to address this issue, the selection of the most relevant/predictive variables from each data tables may solve the problem of dimensionality.…”

Section: C18 Analysismentioning

confidence: 99%

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

et al. 2015

View full text Add to dashboard Cite

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. The aims of this study were to characterize a metabolic signature of ASD and to evaluate multiplatform analytical methodologies in order to develop predictive tools for diagnosis and disease follow-up. Urine samples were analyzed using 1 H and 1 H− 13C NMR-based approaches and LC−HRMS-based approaches (ESI+ and ESI− on HILIC and C18 chromatography columns). Data tables obtained from the six analytical modalities on a training set of 46 urine samples (22 autistic children and 24 controls) were processed by multivariate analysis (orthogonal partial least-squares discriminant analysis, OPLS-DA). The predictions from each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and receiver operating characteristic curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLS-DA model showed an enhanced performance (R 2 Y(cum) = 0.88, Q 2 (cum) = 0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC = 0.91, p-value = 0.006). Metabolites that are most significantly different between autistic and control children (p < 0.05) are indoxyl sulfate, N-α-acetyl-L-arginine, methyl guanidine, and phenylacetylglutamine. This multimodality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population.

show abstract

Section: C18 Analysismentioning

confidence: 99%

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

et al. 2015

View full text Add to dashboard Cite

show abstract

“…The two correction factors are denoted 'offset' and 'slope', and each spectrum is corrected by subtraction of the offset followed by division by the slope. [41] Software The chemometric applications were performed by the UNSCRAM-BLER software version 9.6 from Computer Aided Modelling (CAMO, Trondheim, Norway).…”

Section: Multiplicative Scatter Correctionmentioning

confidence: 99%

Composition and authentication of virgin olive oil from French PDO regions by chemometric treatment of Raman spectra

Korifi

Dréau

Molinet

et al. 2011

J Raman Spectroscopy

View full text Add to dashboard Cite

International audienceThe search for the origin and the authentication of virgin olive oils (VOOs) is a problem of topical interest. VOOs with the protected designation of origin (PDO) label can be subject to fraudulent practices owing to high price commanded by these oils. This work evaluates the capability of confocal Raman spectroscopy combined with chemometric treatments for determining the fatty acid and triacylglycerol (TAG) compositions of VOOs and for authenticating the PDO labels of six French VOOs. Fatty acid and TAG compositions were determined by chemometric analysis of the Raman spectra using the partial least square (PLS) algorithms. Predictions have provided good results on the high percentage compounds, but for the fatty acids at very low percentages the predicted results were very poor. The PLS-discriminant analysis model on Raman spectra was able to correctly classify 92.3% of French PDOs and 100% of PDO samples made with only one principal cultivar. However, it was noticeable that the first regression coefficient (which explains the greatest amount of variation of the data) obtained for each PDO could be compared one by one with the first regression coefficient obtained for the quantitative analysis of fatty acids and TAGs. The first regression coefficients obtained for PDOs differed widely from each other. Their study allowed interpreting the PDOs according to their chemical composition. This work confirms that fatty acid and TAG percentages may be used to authenticate French VOOs into PDO

show abstract

“…where N c is the number of correctly classified samples and N ic is the number of incorrectly classified samples [25].…”

Section: Pls-discriminant Analysis Regressionmentioning

confidence: 99%

Chemometric analysis of combined NIR and MIR spectra to characterize French olives

Dupuy¹,

Galtier²,

Dréau³

et al. 2010

Euro J Lipid Sci & Tech

View full text Add to dashboard Cite

Chemometric treatment of near‐infrared (NIR) and mid‐infrared (MIR) combined spectra was used firstly to predict oil and water contents in fresh olive fruit samples (n = 223) and secondly to classify these samples into five principal French cultivar origins (Aglandau, Cailletier, Olivière, Salonenque, and Tanche). The study was carried out during four crop years (2005/2006 to 2008/2009) to take into account the seasonal variations. The comparison of the results obtained in the combined range (REP = 2.6% for the water content and 3.5% for the oil content) provides an obvious advantage compared to the NIR and MIR techniques used separately. Fresh olive fruit cultivars were satisfactorily classified with the partial least squares‐discriminant analysis (PLS‐DA) method in the combined range. After use of the K‐means clustering on the PLS‐DA scores, all the samples were well classified into their five groups of origin. The use of infrared combined spectra allows a considerable improvement in estimating olive fruit quality (oil and water contents, varietal origins).

show abstract

Authenticating white grape must variety with classification models based on aroma sensors, FT-IR and UV spectrometry

Cited by 94 publications

References 28 publications

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Composition and authentication of virgin olive oil from French PDO regions by chemometric treatment of Raman spectra

Chemometric analysis of combined NIR and MIR spectra to characterize French olives

Contact Info

Product

Resources

About