| Title: |
Dataset for common wheat (Triticum aestivum L.) grain and flour characterization using classical and advanced analyses |
| Authors: |
Munch, Mélanie; Rezette, Laura; Buche, Patrice; Chambrey, Baptiste; Deborde, Catherine; Dervaux, Stéphane; Geoffroy, Sonia; Kansou, Kamal; Le Gall, Sophie; Linossier, Laurent; Meleard, Benoit; Menut, Luc; Morel, Marie-Hélène; Weber, Magalie; Saulnier, Luc |
| Contributors: |
Science et Technologie du Lait et de l'Oeuf (STLO); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers; 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); Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); BIBS - Plateforme Bioressources : Imagerie, Biochimie & Structure; 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)-INRAE, PROBE Research Infrastructure; Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier; 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 Montpellier (UM); Axiane Meunerie; Mathématiques et Informatique Appliquées (MIA Paris-Saclay); AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); ARVALIS - Institut du Végétal Boigneville; ARVALIS - Institut du végétal Paris; Groupe Limagrain; Evagrain; ANR-20-CE21-0008,EVAGRAIN,Des outils intelligents pour une utilsation agile du blé(2020) |
| Source: |
ISSN: 2352-3409 ; Data in Brief ; https://hal.inrae.fr/hal-04937377 ; Data in Brief, 2025, 59, pp.111375. ⟨10.1016/j.dib.2025.111375⟩. |
| Publisher Information: |
CCSD; Elsevier |
| Publication Year: |
2025 |
| Subject Terms: |
Bread; Wheat; Grain; Quality; Biochemical composition; [SDV.IDA]Life Sciences [q-bio]/Food engineering; [SDV.BBM]Life Sciences [q-bio]/Biochemistry; Molecular Biology |
| Description: |
International audience ; As global warming and changing market demand reshape agricultural practices, optimising the quality and utility of crop products, particularly wheat, is becoming increasingly complex and critical. Wheat plays a central role in human and animal nutrition, with its quality influenced by multiple factors at different scales, from grain composition to end-product performance, usually evaluated through sensory evaluation. Understanding the relationship between wheat composition and technological quality is essential for improving product value in agri-food systems. This dataset represents a broad panel of wheat samples encompassing diverse genetic backgrounds grown under varying environmental conditions in France. It collects measurements of grain, flour, dough and bread characteristics, facilitating a comprehensive comparison of wheat quality at different stages of production. The dataset encompasses 35 classical technological tests, 31 detailed compositional analyses—including in-depth characterization of protein composition (glutenin and gliadin), pentosan content measurement, and fatty acid profile analysis—and 37 sensory evaluations from the French Bread baking test providing detailed assessments of flour quality and dough behavior across key bread-making stages. In addition, raw data sets from Alveograph® and Farinograph® tests are included to support the development of innovative quality assessment criteria. This dataset will be valuable not only for the crop industry in its efforts to optimize wheat quality, but also for researchers and data scientists exploring the complex relationships between composition, processing and final bread quality. The data are registered in the French Research Data Gouv public repository and also stored in the PO2 Evagrain database using the PO2/TransformON ontology. The SPO2Q web tool allows for online database consultation, with further access available through the PO2 Manager desktop application. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
https://doi.org/10.57745/9T6Q56; https://doi.org/10.57745/EBBGE8; https://doi.org/10.57745/GQC1L9; https://doi.org/10.57745/SUPRIB; info:eu-repo/semantics/altIdentifier/pmid/40034728; PUBMED: 40034728; WOS: 001427916000001 |
| DOI: |
10.1016/j.dib.2025.111375 |
| Availability: |
https://hal.inrae.fr/hal-04937377; https://hal.inrae.fr/hal-04937377v2/document; https://hal.inrae.fr/hal-04937377v2/file/2025_Munch_DataInBrief.pdf; https://doi.org/10.1016/j.dib.2025.111375 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.AD8A7F1B |
| Database: |
BASE |