使用近红外光谱学预测马片中的烯胺含量
Chuanqi Xie1, Changyan Wang2, Mengyao Zhao2
1State Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, Shanghai 200237, China; State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, The Institute of Animal Husbandry and Veterinary Science, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China.
概括
近红外 (NIR) 光谱可以预测马片中的烯胺 (ACR) 含量. 这种非破坏性方法为监测食品中的ACR水平提供了一种可行的方法.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 烯胺 (ACR) 是一种神经毒素和致癌物,存在于炸和烤食品中,如马片.
- 高水平的ACR对人类健康构成风险,包括潜在的生育问题.
- 在食品中检测ACR的准确和有效方法至关重要.
研究的目的:
- 开发和验证一种方法来预测马片中的烯胺含量.
- 使用近红外 (NIR) 光谱技术进行非破坏性ACR分析.
- 识别有效的光谱特征,以提高预测准确度.
主要方法:
- 接近红外光谱 (NIR) 用于分析烯胺含量.
- 竞争性适应性重权取样 (CARS) 和连续预测算法 (SPA) 用于选择有效的波数.
- 部分最小平方 (PLS) 模型是使用完整和选择的光谱数据构建的,用于ACR预测.
主要成果:
- 基于完整波数和选择波数的PLS模型实现了R2值分别为0.7707和0.6670.
- 根平均平方预测误差 (RMSEP) 在各自模型中为53.0442μg/kg和64.3810μg/kg.
- 该研究表明,在预测ACR含量方面,选定波数的有效性.
结论:
- 近红外 (NIR) 光谱是一种适合的非破坏性技术,用于预测马片中的烯胺含量.
- 鉴定到的有效波数可以提高ACR监测的准确性和效率.
- 这种方法为食品安全和质量控制提供了有价值的工具.
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