整合破坏性和非破坏性分析确定,以评估在不同加工温度下处理的新鲜和烤子的质量
Riccardo Riggi1, Margherita Modesti1, Gianmarco Alfieri1
1Department of Innovation in Biological, Agro-Food and Forestry Systems (DIBAF) University of Tuscia Viterbo Italy.
Food science & nutrition
|March 14, 2025
概括
电子鼻子 (E-nose) 和里埃变换近红外光谱 (FT-NIR) 可以快速区分在不同温度下烤的子. 这些非破坏性方法精确监测食品行业至关重要的质量参数.
科学领域:
- 农业科学 农业科学
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
背景情况:
- 子质量,特别是脂肪降解,对于工业加工至关重要.
- 烤条件显著改变子的组成和挥发性.
研究的目的:
- 评估电子鼻子 (E-nose) 和FT-NIR光谱的效率,以区分在不同条件下烤的子.
- 评估FT-NIR能够预测子的关键质量参数的能力.
- 探索在收获后和加工阶段对子质量的非破坏性监测解决方案.
主要方法:
- 分析的样本包括从送货到烤的子.
- 三个烤温度 (140°C,150°C,160°C) 应用在一个恒定的时间 (24分钟).
- 部分最小平方模型 (PLS) 用于使用FT-NIR数据进行质量参数预测 (水分,可溶性固体,蛋白质,酸度,过氧化指数).
- 采用PLS差异分析 (PLS-DA) 和集群分析,使用E-nose和FT-NIR数据进行样本歧视.
主要成果:
- 在预测水分,可溶性固体,蛋白质和过氧化物指数方面,FT-NIR实现了优异的回归性能 (0.951-0.918相关性),但不预测酸度.
- 区分分析模型有效地根据使用FT-NIR和E-nose的烤温度区分了子.
- 来自与传统化学分析一致的非破坏性技术的结果,特别是通过GC/MS进行挥发性分析.
结论:
- FT-NIR和E-nose是有效的非破坏性工具,可以根据烤条件快速区分子.
- 这些技术为监测食品工业中关键质量参数提供了有价值的解决方案.
- 该研究强调了子加工中实时质量控制的潜力.
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