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
INRAE, UMR 1253 STLO, Institut Agro Rennes, 35042 Rennes, France.
INRAE, UR 1268 BIA, 44300 Nantes, France.
Data Brief. 2025 Feb 7;59:111375. doi: 10.1016/j.dib.2025.111375. eCollection 2025 Apr.
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.
随着全球变暖和市场需求的变化重塑农业生产方式，优化作物产品，特别是小麦的质量和实用性正变得越来越复杂和关键。小麦在人类和动物营养中起着核心作用，其质量受多种因素影响，这些因素在不同尺度上，从谷物组成到最终产品性能，通常通过感官评价来评估。了解小麦组成与工艺质量之间的关系对于提高农业食品系统中的产品价值至关重要。该数据集代表了一组广泛的小麦样本，涵盖了在法国不同环境条件下种植的各种遗传背景。它收集了谷物、面粉、面团和面包特性的测量数据，便于全面比较生产不同阶段的小麦质量。该数据集包括35项经典工艺测试、31项详细的成分分析，包括蛋白质组成（谷蛋白和醇溶蛋白）的深入表征、戊聚糖含量测量和脂肪酸谱分析，以及来自法国面包烘焙测试的37项感官评价，提供了关键面包制作阶段对面粉质量和面团行为的详细评估。此外，还包括来自粉质仪和拉伸仪测试的原始数据集，以支持创新质量评估标准的制定。该数据集不仅对致力于优化小麦质量的作物行业有价值，而且对探索成分、加工和最终面包质量之间复杂关系的研究人员和数据科学家也有价值。这些数据已在法国研究数据Gouv公共存储库中注册，并使用PO2/TransformON本体存储在PO2 Evagrain数据库中。SPO2Q网络工具允许在线数据库查询，也可通过PO2 Manager桌面应用程序进一步访问。
