蜂蜜制造的端到端数据流工程框架,从中间产品到TAS1R2@AuNPs/SPCE生物传感器的加工,加上质量转移原则
Xiaoyan Hu1,2,3, Jingqi Zeng1,2,3, Lijuan Ma2,3
1Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China.
Fundamental research
|April 1, 2025
概括
一个新的数据流工程框架通过整合物理,化学和生物属性来改善蜂蜜质量控制. 该系统识别不稳定的前端炼制过程,确保更好的蜂蜜制造质量.
科学领域:
- 食品科学与技术 食品科学与技术
- 生物传感器工程学
- 数据科学数据科学数据科学
背景情况:
- 在现实世界中,蜂蜜制造面临着质量挑战.
- 现有的方法很难全面评估蜂蜜的质量属性.
研究的目的:
- 为蜂蜜制造中的质量转移原则开发一个端到端的数据流工程框架.
- 整合物理,化学和生物质量属性,以改善质量管理.
主要方法:
- 使用多个传感器对65个蜂蜜批次的650个物理和化学质量数据点进行了表征.
- 开发一个过敏的TAS1R2@AuNPs/SPCE生物传感器用于生物质量属性识别.
- 建立一个端到端的数据流,整合关键的质量属性.
主要成果:
- 发现蜂蜜中间体和TAS1R2受体 (KD < 1 × 10-8 M) 之间存在强烈的亲缘关系.
- 使用生物传感器和多变量算法诊断异常蜂蜜批量 (B2,B23,C23).
- 解释质量转移原则,揭示不稳定的前端精炼和可以忽略的后端影响.
结论:
- 开发的框架成功地解释了蜂蜜制造中的质量转移原则.
- 该框架整合了质量管理,质量转移和生物传感器信息,用于智能制造.
- 这种方法有助于通过加强蜂蜜生产的质量控制来促进工业创新.
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