Caroline Peltier

Scientist
Caroline peltier

General informations

Engineer & Technician

Chemosens Platform

caroline.peltier@inrae.fr

HAL

Job

INRAE Researcher (PhD)
  • M2 in computer science and statistics
  • Doctoral thesis in food sciences

Activities

Research theme
Caroline Peltier specializes in data analysis and statistics applied to chemistry (chemometrics) as well as sensory analysis (sensometrics). Within the scope of her activities, she contributes to the statistical data processing for some CSGA projects.

Her work primarily relies on the use of the R programming language, where she develops packages to make her tools available including R packagings : PTRMSR (for analysis of PTR-MS data), LCMS (lipidomic data), AFCR (sensory threshold data) and CSProfile (sensory profiling) packages. These resources are accessible to everyone on the platform's GitHub (https://github.com/Chemosens).

Her areas of interest particularly focuse on the analysis of complex temporal data (Functional Data Analysis) as well as multiblock approaches (Regularized Generalized Canonical Correlation Analysis). She aims to apply these techniques for a better analysis of physico chemical and sensory data acquired simultaneously and seeks to model the relationship between the two types of data.
Key words
R package, sensometrics, chemometrics, multiblock methods
  • Peltier, C., Vasku, G., Crepin, M., Cabaret, S., Berdeaux, O., (2024) An R package for automated semi-targeted analysis in lipidomics.(2024) European Journal of Lipid Science and Technology https://hal.inrae.fr/hal-04532909
  • Peltier C., Visalli, M., Schlich, P., Cardot, H., Analyzing temporal dominance of sensations data with categorical functional data analysis (2023). Food Quality and Preference 109 https://hal.inrae.fr/hal-04107401
  • Peltier C., Visalli, M., Labouré, H., Hélard, C., Andriot, I., Cordelle, S., Le Quéré, J.-L., Schlich, P. Automatic pre-treatment and multiblock analysis of flavor release and sensory temporal data simultaneously collected in vivo. (2022) Journal of chemometrics doi: 10.1002/cem.3450 https://amu.hal.science/INSTITUT-AGRO-DIJON-CSGA/hal-03819873v1
  • Peltier C., Le Brusquet, L., Lejeune F.-X., Moszer, I., Tenenhaus, A.,(2023) Missing values in RGCCA: algorithms and comparison. Chapitre d’ouvrage https://hal.science/hal-04272129
  • Peltier, C., Visalli, M., Thomas, A. (2019) Using temporal dominance of emotions at home. Impact of coffee advertisements on consumers’behavior and methodological perspectives. Food Quality and Preference, 71,311-319. https://hal.inrae.fr/view/index/identifiant/hal-02173253
  • Peltier, C., Visalli, M., Schlich, P., (2018) Enhancing canonical variate analysis by taking the scaling effecti into account. Food Quality and Preference, 64, 88-93. https://u-bourgogne.hal.science/hal-01706679/
  • Peltier, C., Visalli, M., Schlich, P. (2014) Comparison of Canonical Variate Analysis and Principal Component Analysis on 422 descriptive sensory studies. Food Quality And Preference ,40B, 326-333. https://hal.inrae.fr/hal-02640508

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