Experts in Chemometrics and Machine Learning, Ondalys team stands at the cutting edge of the Research in terms of data analysis.
Through collaborations with research centers and manufacturers, Ondalys often participates to publication of scientific articles.
A. Biancolilloa, S.Preys, B. Gaci, JL Le-Queree, H. Labouree, Z. Deuschere, V. Cheynier, N. Sommerer, N. Fayeulle, P. Costet, C. Hue, R. Boulanger, K. Alary, M. Lebrun, MC Lahon,
G Morel, I.Maraval, F. Davrieux, JM Roger. Multi-block classification of chocolate and cocoa samples into sensory poles – Food Chemistry Vol 340, 127904, Mars 2021.
N Fayeulle, S Preys, JM Roger, R Boulanger, C Hue, V Cheynier & Ns Sommerer. Multiblock Analysis to Relate Polyphenol Targeted Mass Spectrometry and Sensory Properties of Chocolates and Cocoa Beans. Metabolites. 311. 10.3390/metabo10080311, July 2020
B. Barthès, E. Kouakoua, M. Clairotte, J. Lallemand, L. Chapuis-Lardy, M. Rabenarivo, S. Roussel. Performance comparison between a miniaturized and a conventional near infrared reflectance (NIR) spectrometer for characterizing soil carbon and nitrogen. – Geoderma, Volume 338, Pages 422-429, Mars 2019.
Z. Deuscher, I. Andriot, E. Sémon, M. Repoux, S. Preys, JM. Roger, R. Boulanger, H. Labouré, JL. Le Quéré. Volatile compounds profiling by using proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS). The case study of dark chocolates organoleptic differences. – Journal of Mass Spectrometry, Volume 54 Number 1, Pages 92–119, Janvier 2019.
Igne B, De Juan A, Jaumot J, Lallemand J, Preys S, Drennen J K, and Anderson C A, 2014. Modeling strategies for pharmaceutical blend monitoring and end-point determination by near-infrared spectroscopy, International Journal of Pharmaceutics,Volume 473, Issues 1–2, 1 October 2014, Pages 219-231
Roussel S., Preys, S., Lallemand J., Chauchard F.. “Chemometrics” Chapter in the book “PAT in the Food industry”, Pr. C. O’Donnell Ed., 2012.
Roussel S.A., Igne B., Funk D.B., Hurburgh C.R., 2011. Noise Robustness Comparison for Near Infrared Prediction Models, J.NIRS, Volume: 19, Issue: 1, Pages: 23.
Igne B., Roger J-M., Roussel S., Bellon-Maurel V., Hurburgh C. R., 2009. Improving the transfer of near infrared prediction models by orthogonal methods. Chemom. Intell. Lab. Syst., vol. 99, pp 57-65
Chauchard F., Fontange C. 2009. Introduction à l’apport des techniques proche infrarouge pour le contrôle des procédés de l’industrie pharmaceutique et démarche PAT, SPECTRA ANALYSE n° 269 • Septembre – Octobre 2009.
Preys S., Roger J.M., Boulet J.C., 2008. Robust calibration using orthogonal projection and experimental design – Application to the correction of the light scattering effect on turbid NIR spectra, Chemometrics and Intelligent Laboratory Systems, 91, 28-33.
Chauchard F., Svensson J., Axelsson J., Andersson Engel S., 2008. Localization of embedded inclusions using detection of fluorescence: Feasibility study based on simulation data, LS-SVM modelling and EPO pre-processing. Chemometrics and Intelligent Laboratory Systems 91, 34–42
Giordanengo,T., Charpentier, J.P., Roger, J.M., Roussel, S., Brancheriau, L., Chaix, G., Baillères H., 2008. Correction of moisture effects on near infrared calibration for the analysis of phenol content in eucalyptus wood extracts. Annals of Forest Science, vol. 65, n° 8, p. 1 – 8.
Preys S., Vigneau E., Mazerolles G., Cheynier V.and Bertrand D., 2007. Multivariate prototype approach for authentication of food products, Chemometrics and Intelligent Laboratory Systems, 87, 200-207.
Preys S., Mazerolles G., Courcoux P., Samson A., Fischer U., Hanafi M., Bertrand D. and Cheynier V., 2006. Relationship between polyphenolic composition and some sensory properties in red wines using multiway analyses, Analytica Chimica Acta, 563, 126-136.
Roussel S, Cogdill, RP, 2003. Book chapter: “Near-Infrared Spectroscopic Methods”, In Genetically Modified Organism Detection In Food, Ahmed FE (Ed.).
Roger J.M., Chauchard F., Bellon-Maurel V., 2003. External Parameter Orthogonalisation of PLS: Application to temperature-independent measurement of sugar content of intact fruits. Chemometrics and Intelligent Laboratory Systems, 1375, 1-14
“Ondalys, the brick that connects researchers and industrials.”
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With more than 15 years of experience in data analysis, chemometrics and machine learning, especially applicated to spectroscopic data, our team helps you in each step of your project.
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