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1. Multiblock Analysis to Relate Polyphenol Targeted Mass Spectrometry and Sensory Properties of Chocolates and Cocoa Beans

Author

Fayeulle, Noémie, Preys, Sébastien, Roger, Jean-Michel, Boulanger, Renaud, Hue, Clotilde, Cheynier, Veronique, Sommerer, Nicolas, Sciences Pour l'Oenologie (SPO), Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ondalys, Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), CHEMHOUSE RESEARCH GROUP MONTPELLIER FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Démarche intégrée pour l'obtention d'aliments de qualité (UMR Qualisud), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Chocolaterie Valrhona, Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie])-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and ONDALYS CLAPIERS FRA

Subjects
Polyphénol, [SDV]Life Sciences [q-bio], lcsh:QR1-502, Composition des aliments, Spectroscopie, sensory, Chocolat, produits de cacao, Article, lcsh:Microbiology, Q04 - Composition des produits alimentaires, polyphenols, mass spectrometry, Méthode statistique, Analyse multivariée, chocolate, chemometrics, Propriété organoleptique, multiblock analysis
Abstract

International audience; Chocolate quality is largely due to the presence of polyphenols and especially of flavan-3-ols and their derivatives that contribute to bitterness and astringency. The aim of the present work was to assess the potential of a quantitative polyphenol targeted metabolomics analysis based on mass spectrometry for relating cocoa bean polyphenol composition corresponding chocolate polyphenol composition and sensory properties. One-hundred cocoa bean samples were transformed to chocolates using a standard process, and the latter were attributed to four different groups by sensory analysis. Polyphenols were analyzed by an ultra-high-performance liquid chromatography (UPLC) system hyphenated to a triple quadrupole mass spectrometer. A multiblock method called a Common Component and Specific Weights Analysis (CCSWA) was used to study relationships between the three datasets, i.e., cocoa polyphenols, chocolate polyphenols and sensory profiles. The CCSWA multiblock method coupling sensory and chocolate polyphenols differentiated the four sensory poles. It showed that polyphenolic and sensory data both contained information enabling the sensory poles' separation, even if they can be also complementary. A large amount of variance in the cocoa bean and corresponding chocolate polyphenols has been linked. The cocoa bean phenolic composition turned out to be a major factor in explaining the sensory pole separation.

Published
2020

2. Results from a French Inter‐laboratory Campaign on the Biological Methane Potential of Solid Substrates

Author

Cresson, Romain, Pommier, Sébastien, Beline, Fabrice, Bouchez, Théodore, Bougrier, Claire, Buffière, Pierre, Pauss, André, Pouech, Philippe, Preys, S., Ribeiro, Thierry, Rouez, Maxime, Torrijos, Michel, INRA Transfert Environnement, INRA Transfert, Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés (LISBP), Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de la Recherche Agronomique (INRA), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Hydrosystèmes et bioprocédés (UR HBAN), Veolia Recherche et Innovation, Veolia France, Déchets Eaux Environnement Pollutions (DEEP), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA), Transformation Intégrée de la Matière Renouvelable (TIMR), Université de Technologie de Compiègne (UTC), APESA, Département R&D Ondalys, Ondalys, Institut Polytechnique LaSalle Beauvais, CIRSEE, Suez Environnement, Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA), CRITT GENIE DES PROCEDES ET TECHNOLOGIES ENVIRONNEMENTALES TOULOUSE FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Gestion environnementale et traitement biologique des déchets (UR GERE), Hydrosystèmes et Bioprocédés (UR HBAN), Veolia Environnement (FRANCE), APESA PAU FRA, SUEZ ENVIRONNEMENT LE PECQ FRA, INRA Transfert Environnement [Narbonne], Institut National de la Recherche Agronomique (INRA)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon, Centre International de Recherche Sur l'Eau et l'Environnement [Suez] (CIRSEE), SUEZ ENVIRONNEMENT (FRANCE), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), and Veolia Recherche & Innovation (VeRI)

Subjects
[CHIM.GENI]Chemical Sciences/Chemical engineering, [SDE.IE]Environmental Sciences/Environmental Engineering, [SDE]Environmental Sciences, BMP, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, POTENTIEL METHANOGENE, ComputingMilieux_MISCELLANEOUS, SUBSTRAT SOLIDE
Abstract

International audience; A French inter-laboratory campaign on BMP assessment was realised in two phases: free protocol at first, then harmonized protocol. Results show good intra-laboratory repeatability and reproducibility, but in spite of an attempt in the harmonization of practices, the inter-laboratoryreproducibility could not be improved and ranges in the magnitude of 20% RSD.

Published
2015

3. Multi-block classification of chocolate and cocoa samples into sensory poles

Author

Clotilde Hue, Hélène Labouré, Gilles Morel, Nicolas Sommerer, Marie Christine Lahon, Marc Lebrun, Sébastien Preys, Renaud Boulanger, Fabrice Davrieux, Alessandra Biancolillo, Belal Gaci, Noémie Fayeulle, Zoé Deuscher, Jean-Michel Roger, Pierre Costet, Jean-Luc Le-Quere, Véronique Cheynier, Isabelle Maraval, Karine Alary, Università degli Studi dell'Aquila (UNIVAQ), Ondalys, Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), CHEMHOUSE RESEARCH GROUP MONTPELLIER FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Bourgogne Franche-Comté [COMUE] (UBFC), Sciences Pour l'Oenologie (SPO), Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Chocolaterie Valrhona, Démarche intégrée pour l'obtention d'aliments de qualité (UMR QualiSud), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Agropolis Foundation Valrhona, Projet CHAMAN, and ANR-10-LABX-0001,AGRO,Agricultural Sciences for sustainable Development(2010)

Subjects
Spectroscopie, Chocolat, 01 natural sciences, High-performance liquid chromatography, Mass Spectrometry, Analytical Chemistry, Fève de cacao, Chocolate, Spectroscopy, Chromatography, High Pressure Liquid, Chromatography, Spectroscopy, Near-Infrared, 04 agricultural and veterinary sciences, General Medicine, Q01 - Sciences et technologies alimentaires - Considérations générales, Composition chimique, Classification, Cocoa beans, Multi-block, Sensory analysis, 040401 food science, Analyse organoleptique, Taste, Materials science, Mass spectrometry, Fluorescence spectroscopy, Gas Chromatography-Mass Spectrometry, 0404 agricultural biotechnology, [CHIM]Chemical Sciences, Humans, Least-Squares Analysis, Q04 - Composition des produits alimentaires, Solid Phase Microextraction, Chocolate Flavor, Cacao, 010401 analytical chemistry, Near-infrared spectroscopy, Polyphenols, 0104 chemical sciences, Propriété organoleptique, Spectrometry, Fluorescence, Polyphenol, Chromatographie, U30 - Méthodes de recherche, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Food Analysis, Food Science
Abstract

International audience; The present study aims at developing an analytical methodology which allows correlating sensory poles of chocolate to their chemical characteristics and, eventually, to those of the cocoa beans used for its preparation. Trained panelists investigated several samples of chocolate, and they divided them into four sensorial poles (characterized by 36 different descriptors) attributable to chocolate flavor. The same samples were analyzed by six different techniques: Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), Solid Phase Micro Extraction-Gas Chromatography-Mass Spectroscopy (SPME-GC-MS), High-Performance Liquid Chromatography (HPLC) (for the quantification of eight organic acids), Ultra High Performance Liquid Chromatography coupled to triple-quadrupole Mass Spectrometry (UHPLC-QqQ-MS) for polyphenol quantification, 3D front face fluorescence Spectroscopy and Near Infrared Spectroscopy (NIRS). A multi-block classification approach (Sequential and Orthogonalized-Partial Least Squares – SO-PLS) has been used, in order to exploit the chemical information to predict the sensorial poles of samples. Among thirty-one test samples, only two were misclassified.

Published
2020

4. Measurement of Biochemical Methane Potential of Heterogeneous Solid Substrates: Results of a Two- Phase French Inter-Laboratory Study

Author

Romain Cresson, Sébastien Preys, Maxime Rouez, Fabrice Béline, Théodore Bouchez, Michel Torrijos, Pierre Buffière, L. André, Patricia Camacho, Jesús Cacho, André Pauss, Laurent Mazéas, Claire Bougrier, Philippe Pouech, Sébastien Pommier, T. Ribeiro, UniLaSalle, Transformations et Agro-ressources (UT&A), INRAE Transfert Environnement [Narbonne], INRAE Transfert, Toulouse Biotechnology Institute (TBI), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ondalys, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement (UR OPAALE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Procédés biotechnologiques au service de l'environnement (UR PROSE), Veolia Environnement Research and Innovation, Déchets Eaux Environnement Pollutions (DEEP), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA), SUEZ ENVIRONNEMENT (FRANCE), Transformation Intégrée de la Matière Renouvelable (TIMR), Université de Technologie de Compiègne (UTC), APESA [Pau], Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ADEME, grant number 1206C0036 (2012-2014)., Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
lcsh:Hydraulic engineering, [SDV.BIO]Life Sciences [q-bio]/Biotechnology, 020209 energy, Geography, Planning and Development, 02 engineering and technology, 010501 environmental sciences, Aquatic Science, 01 natural sciences, Biochemistry, Methane, chemistry.chemical_compound, lcsh:Water supply for domestic and industrial purposes, [CHIM.GENI]Chemical Sciences/Chemical engineering, Bioenergy, lcsh:TC1-978, inter-laboratory study, Phase (matter), parasitic diseases, 0202 electrical engineering, electronic engineering, information engineering, BMP, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, 0105 earth and related environmental sciences, Water Science and Technology, methanogenic potential, 2. Zero hunger, Methane potential, Reproducibility, lcsh:TD201-500, Chromatography, solid substrates, [SDE.IE]Environmental Sciences/Environmental Engineering, food and beverages, Substrate (chemistry), Repeatability, Straw, carbohydrates (lipids), chemistry, embryonic structures, lipids (amino acids, peptides, and proteins)
Abstract

Biochemical methane potential (BMP) is essential to determine the production of methane for various substrates, literature shows important discrepancies for the same substrates. In this paper, a harmonized BMP protocol was developed and tested with two phases of BMP tests carried out by eleven French laboratories. Surprisingly, for the three same solid tested substrates (straw, raw mix and dried-shredded mix of potatoes, maize, beef meat and straw, and mayonnaise), the standard deviations of the repeatability and reproducibility inter-laboratory were not enhanced by the harmonized protocol (average of about 25% depending on the substrate), as compared to a previous step where all laboratories used their own protocols. Moreover, statistical analyses of all the results, after removal of the outliers (about 15% of all observations), did not highlight significant effect of the operational effect on BMP (stirring, automatic or manual gas quantification, use of trace metal, uses a bicarbonate buffer, inoculum to substrate ratio) at least for the tested ranges. On the other hand, the average intra-laboratory repeatability was low, about 7%, whatever the protocol, the substrate and the laboratory. It also appears that drying the SA substrate, which contained proteins, carbohydrates, lipids and fibers, does not impact its BMP.

Published
2020

5. Performance comparison between a miniaturized and a conventional near infrared reflectance (NIR) spectrometer for characterizing soil carbon and nitrogen

Author

Bernard Barthès, Michel Rabenarivo, Michaël Clairotte, Lydie Chapuis-Lardy, Ernest Kouakoua, Jordane Lallemand, Sylvie Roussel, Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Ondalys, Institut de recherche pour le développement (IRD [Sénégal]), Laboratoire des Radio-Isotopes (LRI), Université d'Antananarivo, Université d'Antananarivo, IRD, UMR Eco&Sols, Montpellier, France, and Laboratoire des RadioIsotopes (LRI)

Subjects
Near infrared reflectance spectroscopy (NIRS), Materials science, Resolution (mass spectrometry), Soil Science, chemistry.chemical_element, 010501 environmental sciences, 01 natural sciences, Spectral line, Microspectrometer, Soil total nitrogen, [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry, Range (statistics), Madagascar, Near infrared reflectance, 0105 earth and related environmental sciences, Remote sensing, Spectrometer, Soil organic carbon, Near-infrared spectroscopy, 04 agricultural and veterinary sciences, Nitrogen, chemistry, Performance comparison, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries
Abstract

International audience; Miniaturized near infrared spectrometers are now available, at more affordable prices than conventional spectrometers, but their performances have been poorly studied to date. This paper aimed at comparing the performances of the JDSU MicroNIR 2200 spectrophotometer (weight < 0.1 kg) with those of a conventional bench-top instrument for predicting carbon and nitrogen contents in laboratory conditions, on a range of representative Malagasy soils. Though its noticeably narrower and less resolved spectra (1151-2186 nm at 8.15 nm step vs. 1100-2498 nm at 2 nm step), the microspectrometer yielded predictions in independent validation that were almost as accurate as those of the conventional instrument (standard errors of prediction were 4.6 vs. 3.4 gC kg(-1), but 3.9 vs. 3.4 gC kg(-1) after bias correction, and 0.36 vs. 0.35 gN kg(-1), respectively). Due to noisy features, the MicroNIR spectra needed mathematical pretreatment (e.g. standard normal variate SNV), and bias correction for C, for providing accurate predictions, while the raw absorbance spectra from the conventional instrument did not. Furthermore, building multivariate models with MicroNIR spectra required less latent variables than with their conventional counterparts, and these models were less prone to performance degradation when applied to independent validation samples. Fitting the spectra of the conventional instrument to those of the MicroNIR (1150-2182 nm at 2 or 8 nm step) showed that (moderately) less accurate MicroNIR predictions could be firstly attributed to narrower spectral range rather than to poorer resolution. Considering their performances, such microspectrometers could thus represent a cost-effective alternative to conventional spectrometers. They have now to be tested in field conditions.

Published
2019

6. Volatile compounds profiling by using proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS). The case study of dark chocolates organoleptic differences

Author

Sébastien Preys, Jean-Luc Le Quéré, Marie Repoux, Jean-Michel Roger, Renaud Boulanger, Etienne Sémon, Hélène Labouré, Isabelle Andriot, Zoé Deuscher, Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture (IRSTEA), Démarche intégrée pour l'obtention d'aliments de qualité (UMR Qualisud), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Projet CHAMAN, Institut National de la Recherche Agronomique (INRA), Université Bourgogne Franche-Comté [COMUE] (UBFC), VALRHONA TAIN L'HERMITAGE FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Ondalys, Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de La Réunion (UR)-Université de Montpellier (UM)-Avignon Université (AU)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université Montpellier 1 (UM1), and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Université de La Réunion (UR)-Université de Montpellier (UM)-Avignon Université (AU)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université Montpellier 1 (UM1)

Subjects
030309 nutrition & dietetics, Analyse qualitative, Chocolat, PLS-DA, 01 natural sciences, Mass Spectrometry, Partial least squares regression, Chocolate, Proton-transfer-reaction mass spectrometry, Spectroscopy, Composé volatil, 0303 health sciences, Systèmes de classification, Chemistry, Qualité des aliments, 04 agricultural and veterinary sciences, Composé aromatique, 040401 food science, Categorization, [SDE]Environmental Sciences, PROFILING, Sensation, VOCS, Feature selection, Mass spectrometry, Chemometrics, 03 medical and health sciences, 0404 agricultural biotechnology, Food Quality, Q04 - Composition des produits alimentaires, Technique analytique, Volatile Organic Compounds, 010405 organic chemistry, business.industry, 010401 analytical chemistry, Pattern recognition, PTR-MS, 0104 chemical sciences, Propriété organoleptique, COVSEL, Test set, Artificial intelligence, Time-of-flight mass spectrometry, U30 - Méthodes de recherche, business, PTR-TOF-MS, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

International audience; Direct-injection mass spectrometry (DIMS) techniques have evolved into powerful methods to analyse volatile organic compounds (VOCs) without the need of chromatographic separation. Combined to chemometrics, they have been used in many domains to solve sample categorization issues based on volatilome determination. In this paper, different DIMS methods that have largely outperformed conventional electronic noses (e-noses) in classification tasks are briefly reviewed, with an emphasis on food-related applications. A particular attention is paid to proton transfer reaction mass spectrometry (PTR-MS), and many results obtained using the powerful PTR-time of flight-MS (PTR-ToF-MS) instrument are reviewed. Data analysis and feature selection issues are also summarized and discussed. As a case study, a challenging problem of classification of dark chocolates that has been previously assessed by sensory evaluation in four distinct categories is presented. The VOC profiles of a set of 206 chocolate samples classified in the four sensory categories were analysed by PTR-ToF-MS. A supervised multivariate data analysis based on partial least squares regression-discriminant analysis allowed the construction of a classification model that showed excellent prediction capability: 97% of a test set of 62 samples were correctly predicted in the sensory categories. Tentative identification of ions aided characterisation of chocolate classes. Variable selection using dedicated methods pinpointed some volatile compounds important for the discrimination of the chocolates. Among them, the CovSel method was used for the first time on PTR-MS data resulting in a selection of 10 features that allowed a good prediction to be achieved. Finally, challenges and future needs in the field are discussed.

Published
2018

7. Organoleptic propoerties of dark chocolates investigated by direct-injection mass spectrometry (PTR-To-MS) and GC-olfactometry

Author

Deuscher, Zoé, Andriot, Isabelle, Gourrat, Karine, Semon, Etienne, Repoux, Marie, GUICHARD, Elisabeth, Preys, Sébastien, Boulanger, Renaud, Labouré, Hélène, Le Quéré, Jean-Luc, Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Centre National de la Recherche Scientifique (CNRS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB), Démarche intégrée pour l'obtention d'aliments de qualité (UMR Qualisud), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de La Réunion (UR)-Université de Montpellier (UM)-Avignon Université (AU)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université Montpellier 1 (UM1), Plateforme Chemosens [Dijon], Centre National de la Recherche Scientifique (CNRS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB), Chocolaterie Valrhona, Ondalys, Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Université de La Réunion (UR)-Université de Montpellier (UM)-Avignon Université (AU)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université Montpellier 1 (UM1), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), ProdInra, Migration, Université Bourgogne Franche-Comté [COMUE] (UBFC), and Projet Chaman

Subjects
[SDV.AEN] Life Sciences [q-bio]/Food and Nutrition, spectrométrie de masse, [SDV.IDA]Life Sciences [q-bio]/Food engineering, chocolat, headspace, odorants, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, ComputingMilieux_MISCELLANEOUS
Abstract

15. Weurman Flavour Research Symposium ; Graz (Autriche) - (2017-09-18 - 2017-09-22); International audience; A preliminary sensory study conducted on a set of 187 dark chocolates varying in terms of cocoa origin and variety allowed their classification into four distinct sensory categories. Fingerprints in volatile organic compounds (VOCs) of these chocolates wereobtained by a direct-injection mass spectrometry headspace method using Proton Transfer Reaction Mass Spectrometry (PTR-MS). This chemical analysis allowed discriminating the four sensory poles, so the sensory discrimination seemed to be mainly based on volatile compounds. Then, the key odorants responsible for chocolates differentiation were determined through identification of targeted aroma compounds by GC-MS after GC-O analyses of extracts representative of each subset of chocolates. Twelve dark chocolates were studied using the detection frequency method. The odour eventsgenerated by a panel of 12 assessors were grouped into 124 odorant areas (OAs).Correspondence analyses allowed distinguishing the samples while identifying 34 OAs that appear relevant to discriminate the chocolates sensory poles. Among these characteristic OAs, five were identified unambiguously with GC-MS and the remainingneed to be resolved from numerous coeluted peaks.

Published
2018

8. Multi-block classification of chocolate and cocoa samples into sensory poles.

Author

Biancolillo A, Preys S, Gaci B, Le-Quere JL, Laboure H, Deuscher Z, Cheynier V, Sommerer N, Fayeulle N, Costet P, Hue C, Boulanger R, Alary K, Lebrun M, Christine Lahon M, Morel G, Maraval I, Davrieux F, and Roger JM

Subjects
Chromatography, High Pressure Liquid, Food Analysis statistics & numerical data, Gas Chromatography-Mass Spectrometry methods, Humans, Least-Squares Analysis, Mass Spectrometry methods, Polyphenols analysis, Solid Phase Microextraction, Spectrometry, Fluorescence, Spectroscopy, Near-Infrared, Taste, Cacao chemistry, Chocolate analysis, Chocolate classification, Food Analysis methods
Abstract

The present study aims at developing an analytical methodology which allows correlating sensory poles of chocolate to their chemical characteristics and, eventually, to those of the cocoa beans used for its preparation. Trained panelists investigated several samples of chocolate, and they divided them into four sensorial poles (characterized by 36 different descriptors) attributable to chocolate flavor. The same samples were analyzed by six different techniques: Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), Solid Phase Micro Extraction-Gas Chromatography-Mass Spectroscopy (SPME-GC-MS), High-Performance Liquid Chromatography (HPLC) (for the quantification of eight organic acids), Ultra High Performance Liquid Chromatography coupled to triple-quadrupole Mass Spectrometry (UHPLC-QqQ-MS) for polyphenol quantification, 3D front face fluorescence Spectroscopy and Near Infrared Spectroscopy (NIRS). A multi-block classification approach (Sequential and Orthogonalized-Partial Least Squares - SO-PLS) has been used, in order to exploit the chemical information to predict the sensorial poles of samples. Among thirty-one test samples, only two were misclassified., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Published
2021
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9. Volatile compounds profiling by using proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS). The case study of dark chocolates organoleptic differences.

Author

Deuscher Z, Andriot I, Sémon E, Repoux M, Preys S, Roger JM, Boulanger R, Labouré H, and Le Quéré JL

Subjects
Food Quality, Mass Spectrometry methods, Sensation, Chocolate analysis, Volatile Organic Compounds analysis
Abstract

Direct-injection mass spectrometry (DIMS) techniques have evolved into powerful methods to analyse volatile organic compounds (VOCs) without the need of chromatographic separation. Combined to chemometrics, they have been used in many domains to solve sample categorization issues based on volatilome determination. In this paper, different DIMS methods that have largely outperformed conventional electronic noses (e-noses) in classification tasks are briefly reviewed, with an emphasis on food-related applications. A particular attention is paid to proton transfer reaction mass spectrometry (PTR-MS), and many results obtained using the powerful PTR-time of flight-MS (PTR-ToF-MS) instrument are reviewed. Data analysis and feature selection issues are also summarized and discussed. As a case study, a challenging problem of classification of dark chocolates that has been previously assessed by sensory evaluation in four distinct categories is presented. The VOC profiles of a set of 206 chocolate samples classified in the four sensory categories were analysed by PTR-ToF-MS. A supervised multivariate data analysis based on partial least squares regression-discriminant analysis allowed the construction of a classification model that showed excellent prediction capability: 97% of a test set of 62 samples were correctly predicted in the sensory categories. Tentative identification of ions aided characterisation of chocolate classes. Variable selection using dedicated methods pinpointed some volatile compounds important for the discrimination of the chocolates. Among them, the CovSel method was used for the first time on PTR-MS data resulting in a selection of 10 features that allowed a good prediction to be achieved. Finally, challenges and future needs in the field are discussed., (© 2018 John Wiley & Sons, Ltd.)

Published
2019
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10. Modeling strategies for pharmaceutical blend monitoring and end-point determination by near-infrared spectroscopy.

Author

Igne B, de Juan A, Jaumot J, Lallemand J, Preys S, Drennen JK, and Anderson CA

Subjects
Acetaminophen chemistry, Carboxymethylcellulose Sodium chemistry, Cellulose chemistry, Excipients chemistry, Lactose chemistry, Least-Squares Analysis, Principal Component Analysis, Spectroscopy, Near-Infrared, Stearic Acids chemistry, Chemistry, Pharmaceutical methods, Models, Theoretical
Abstract

The implementation of a blend monitoring and control method based on a process analytical technology such as near infrared spectroscopy requires the selection and optimization of numerous criteria that will affect the monitoring outputs and expected blend end-point. Using a five component formulation, the present article contrasts the modeling strategies and end-point determination of a traditional quantitative method based on the prediction of the blend parameters employing partial least-squares regression with a qualitative strategy based on principal component analysis and Hotelling's T(2) and residual distance to the model, called Prototype. The possibility to monitor and control blend homogeneity with multivariate curve resolution was also assessed. The implementation of the above methods in the presence of designed experiments (with variation of the amount of active ingredient and excipients) and with normal operating condition samples (nominal concentrations of the active ingredient and excipients) was tested. The impact of criteria used to stop the blends (related to precision and/or accuracy) was assessed. Results demonstrated that while all methods showed similarities in their outputs, some approaches were preferred for decision making. The selectivity of regression based methods was also contrasted with the capacity of qualitative methods to determine the homogeneity of the entire formulation., (Copyright © 2014. Published by Elsevier B.V.)

Published
2014
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