From dairy to plant products: Understanding their structural fingerprints with X-rays.

IF 6.3 1区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY
Eleonora Olsmats, Adrian R Rennie
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Abstract

Global interest in milk alternatives increases rapidly due to health awareness, their allergen-friendliness, and concerns about sustainability. While dairy product microstructure and rheology are widely studied, plant-based alternatives remain less understood, with limited comparative studies of different plant sources and brands. This study uses ultra-small, small and wide-angle X-ray scattering (USAXS, SAXS, WAXS) to analyse structural fingerprints of commercial plant-based milk, yoghurt and cream alternatives versus dairy products. These techniques allow characterization across multiple length scales from large oil droplets and aggregated structures to carbohydrate/protein networks and glyceride crystalline phases. Correlations between intensity and fat (USAXS) and carbohydrate content (SAXS) provide structural insights, while SAXS and WAXS data correlated with solid fat and crystal packing are important for melting behaviour and viscosity perception. Light scattering confirmed fat-content-related size trends and revealed larger structures of non-lipid materials in plant-based samples. The study provides a basis for understanding scattering data where structural fingerprint plots, using colour scales to compare intensity and intensity gradient, allow ready data interpretation that will be beneficial for analysis with artificial intelligence (AI) tools. This approach helps optimize plant-based formulations by connecting structure and functionality and demonstrates the potential of scattering techniques in food structure research and design.

从乳制品到植物产品:用x射线了解它们的结构指纹。
全球对牛奶替代品的兴趣迅速增加,这是由于健康意识、对过敏原的友好性以及对可持续性的关注。虽然乳制品的微观结构和流变学被广泛研究,但基于植物的替代品仍然知之甚少,对不同植物来源和品牌的比较研究有限。本研究使用超小、小和广角x射线散射(USAXS, SAXS, WAXS)来分析商业植物性牛奶、酸奶和奶油替代品与乳制品的结构指纹。这些技术允许在多个长度尺度上进行表征,从大油滴和聚集结构到碳水化合物/蛋白质网络和甘油晶体相。强度与脂肪(USAXS)和碳水化合物含量(SAXS)之间的相关性提供了结构洞察,而与固体脂肪和晶体堆积相关的SAXS和WAXS数据对于熔化行为和粘度感知很重要。光散射证实了脂肪含量相关的尺寸趋势,并揭示了植物基样品中非脂质材料的较大结构。该研究为理解散射数据提供了基础,其中结构指纹图使用颜色尺度来比较强度和强度梯度,允许现成的数据解释,这将有利于人工智能(AI)工具的分析。这种方法有助于通过连接结构和功能来优化基于植物的配方,并展示了散射技术在食品结构研究和设计中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
NPJ Science of Food
NPJ Science of Food FOOD SCIENCE & TECHNOLOGY-
CiteScore
7.50
自引率
1.60%
发文量
53
期刊介绍: npj Science of Food is an online-only and open access journal publishes high-quality, high-impact papers related to food safety, security, integrated production, processing and packaging, the changes and interactions of food components, and the influence on health and wellness properties of food. The journal will support fundamental studies that advance the science of food beyond the classic focus on processing, thereby addressing basic inquiries around food from the public and industry. It will also support research that might result in innovation of technologies and products that are public-friendly while promoting the United Nations sustainable development goals.
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