与多变量算法相结合的新型染色体感应光谱方法,用于识别不同处理的Trionycis Carapax
Gaoyuan Chen1, Huangliang Cao1, Yangxin Xiao1
1College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430065, China.
Talanta
|August 30, 2025
概括
这项研究开发了一种方法,使用彩色,电子鼻子和近红外光谱来评估Trionycis Carapax的处理水平. 这些发现有助于对这种受欢迎的健康食品进行质量控制.
科学领域:
- 食品科学
- 分析化学
- 生物技术
背景情况:
- Trionycis Carapax是一种广泛消费的健康食品.
- 处理对其质量产生重大影响,因此需要准确的评估方法.
研究的目的:
- 开发一个全面的框架来区分Trionycis Carapax的不同加工水平.
- 阐明加工过程中氨基酸,梅拉德反应和蛋白质水解的动态变化.
主要方法:
- 使用的表面和粉末颜色参数 (a*,b*,L*).
- 使用电子鼻子 (E鼻子) 来区分原始和加工产品.
- 应用近红外 (NIR) 光谱与正常化预处理.
- 综合融合分析和反向传播神经网络模型.
主要成果:
- 确定关键的颜色参数 (a*,b*,L*) 对于差异化至关重要.
- E-nose成功地区分了原始和加工的样本.
- NIR光谱有效地区分了各种处理程度.
- 融合分析揭示了颜色与化学成分之间的相关性.
- BP的神经网络模型实现了91.7%的区分精度.
结论:
- 一个多技术的分析框架准确地评估了Trionycis Carapax的处理水平.
- 颜色,E鼻子和NIR光谱是有效的质量控制工具.
- 这些发现支持食品加工业的数字化转型,以提高质量管理.
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