{"title":"Selection of oat varieties with unique nutritional qualities based on near-infrared spectroscopy and HS-SPME-GC-MS","authors":"Yuting Zhu , Jiankang Zhou , Shengyuan Guo , Zhuo Zhang , Wenting Wang , Chaofan Zhao , Jiaxue Wang , Haitao Zhou , Guixing Ren","doi":"10.1016/j.jcs.2025.104217","DOIUrl":null,"url":null,"abstract":"<div><div>Oats (<em>Avena sativa</em>) are a globally valued crop with exceptional nutritional and functional properties, yet their quality evaluation remains constrained by traditional methods. In this study, we successfully constructed a multidimensional quality assessment system for oat ‘chemical composition-volatile characteristics-processing suitability’, aiming to evaluate 71 oat varieties from 9 regions around the world. Key innovations include: (1) The optimized non-destructive NIRS model achieved highly accurate prediction of β-glucan (R<sup>2</sup> = 0.95) and AVNs, and the use of composite spectral preprocessing significantly enhanced the robustness of the model. (2) A total of 77 flavor compounds were detected by HS-SPME-GC-MS, OAV analysis revealed 8 aromatic compounds, and PLS-DA identified 13 volatile markers (VIP >1) for geographic source differentiation. (3) A PCA-driven quality ranking system prioritizing Baiyan 8, Baiyan 11 and Zhangyou 14 as superior varieties. This work provides assistance for variety evaluation and product development of oats.</div></div>","PeriodicalId":15285,"journal":{"name":"Journal of Cereal Science","volume":"124 ","pages":"Article 104217"},"PeriodicalIF":3.9000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cereal Science","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S073352102500116X","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Oats (Avena sativa) are a globally valued crop with exceptional nutritional and functional properties, yet their quality evaluation remains constrained by traditional methods. In this study, we successfully constructed a multidimensional quality assessment system for oat ‘chemical composition-volatile characteristics-processing suitability’, aiming to evaluate 71 oat varieties from 9 regions around the world. Key innovations include: (1) The optimized non-destructive NIRS model achieved highly accurate prediction of β-glucan (R2 = 0.95) and AVNs, and the use of composite spectral preprocessing significantly enhanced the robustness of the model. (2) A total of 77 flavor compounds were detected by HS-SPME-GC-MS, OAV analysis revealed 8 aromatic compounds, and PLS-DA identified 13 volatile markers (VIP >1) for geographic source differentiation. (3) A PCA-driven quality ranking system prioritizing Baiyan 8, Baiyan 11 and Zhangyou 14 as superior varieties. This work provides assistance for variety evaluation and product development of oats.
期刊介绍:
The Journal of Cereal Science was established in 1983 to provide an International forum for the publication of original research papers of high standing covering all aspects of cereal science related to the functional and nutritional quality of cereal grains (true cereals - members of the Poaceae family and starchy pseudocereals - members of the Amaranthaceae, Chenopodiaceae and Polygonaceae families) and their products, in relation to the cereals used. The journal also publishes concise and critical review articles appraising the status and future directions of specific areas of cereal science and short communications that present news of important advances in research. The journal aims at topicality and at providing comprehensive coverage of progress in the field.