Contributors: Sécurité et Qualité des Produits d'Origine Végétale (SQPOV); Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Centre Wallon de Recherches Agronomiques (CRA-W); Statistique, Sensométrie et Chimiométrie (StatSC); École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Département Aliments, produits biosourcés et déchets - INRAE (TRANSFORM); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); ZJU-Hangzhou Global Scientific and Technological Innovation Center (ZJU); The ‘Interfaces’ project is an Agropolis Fondation project publicly funded through the ANR (French Research Agency) under “Investissements d’Avenir” programme (ANR-10-LABX-01-001 Labex Agro, coordinated by Agropolis Fondation). Studies conducted with the phytotron were supported by the various CPER Platform 3A funders: European Union, European Regional Development Fund, the French Government, the Sud Provence-Alpes-Cote ˆ d’Azur Region, the Departmental Council of Vaucluse and the Urban Community of Greater Avignon. Weijie Lan was supported by a doctoral grant from Chinese Scholarship Council.
نبذة مختصرة : International audience ; Near-infrared (NIR), mid-infrared (MIR), Raman spectroscopy and hyperspectral imaging (HSI) were comprehensively compared for their capacity to evaluate the composition and texture characteristics of apple purees issued from a large variability (cultivar, fruit thinning, post-harvest mealy texture and processing). NIR, MIR and HSI techniques had a good ability to estimate puree composition such as soluble solids (RPD >2.5), titratable acidity (RPD >2.4) and dry matter (RPD >2.3). Raman spectroscopy was less accurate to determine puree biochemical (RPD <1.8) and textural parameters (RPD <1.4) than the other techniques. MIR was the best tool to identify aforementioned factors (>91.7% of correct classification) and satisfactory predict the puree average particle size (RPD = 2.9), viscosity (RPD ≥2.1) and viscoelasticity (RPD >2.3). Consequently, NIR, MIR and HSI should be prioritized as process analytical technologies to detect apple puree variability, and assess their texture and taste.
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