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使用近红外传输光谱学快速定量检测生牛奶中的精神变质细菌
Na Li1, Xuexia Ma1, Changhao Li1
1College of Food Science and Engineering, Ningxia University, Yinchuan 750021, China.
Journal of dairy science
|February 12, 2026
概括
这项研究引入了一种新的近红外光谱法,用于快速检测生牛奶中的精神变质细菌. 开发的SG-UVE-LSTM模型为监测牛奶质量和安全提供了一种高效可靠的工具.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 微生物学 微生物学
背景情况:
- 心理变质细菌及其酶会导致大量的乳制品腐烂.
- 检测这些细菌的传统方法很慢,对于快速安全评估来说不切实际.
- 需要有效和可靠的方法来检测生牛奶中的精神变质细菌.
研究的目的:
- 开发一种使用近红外 (NIR) 传输光谱技术在原牛奶中检测精神变质细菌的定量检测方法.
- 优化光谱预处理和特征选择技术,以准确检测细菌.
- 评估不同机器学习算法的性能,以预测心理变质细菌水平.
主要方法:
- 生牛奶的NIR光谱是在900-1700nm之间收集的.
- 应用了先进的光谱预处理 (光滑,散射校正) 和特征选择 (IV-ISA,CARS,I-RELIEF,UVE).
- 开发和比较了部分最小平方回归 (PLSR),随机森林 (RF) 和长短期记忆 (LSTM) 网络模型.
主要成果:
- 该SG-UVE-LSTM模型在预测心理变质细菌方面表现出卓越的表现.
- 最好的模型实现了0.9277的确定系数 (R2) 和0.2820 log cfu/mL的预测平方平均误差 (RMSEP).
- 该模型显示出高可靠性,预测剩余偏差 (RPD) 为3.8256.
结论:
- 近红外传输光谱学,结合先进的数据分析和机器学习,提供了一种高效可靠的方法来检测生牛奶中的精神变质细菌.
- 这种方法可以显著提高生牛奶的快速微生物安全性评估.
- 开发的SG-UVE-LSTM模型为乳制品行业提供了一个强大的工具来监测和控制细菌污染.
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