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基于高光谱图像分析的化学测量来估计金的发酵和质量特性

Ji-Young Choi¹, Minjung Lee¹, Minji Kim¹

¹Kimchi Industry Promotion Division, World Institute of Kimchi, Gwangju 61755, Republic of Korea.

Food research international (Ottawa, Ont.)

|December 6, 2024

概括

超光谱成像 (HSI) 与化学测量相结合,可以有效监测金发酵过程. 这种方法可以准确地预测储存期间的pH和乳酸细菌等关键质量指标.

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:

金发酵对于其质量和风味至关重要.
监测发酵需要评估pH,酸度和微生物含量等参数.
传统的方法可能是耗时和破坏性的.

研究的目的:

开发和验证一种用于评估金发酵度的非破坏性方法.
利用高光谱成像 (HSI) 和化学测量来预测金的关键品质属性.

主要方法:

使用高光谱成像 (HSI) 来捕获金奇的光谱数据.
使用了化学测量技术,包括主要成分分析 (PCA),部分最小平方 (PLS) 和支向量回归 (SVR).
开发了多变量模型来预测总溶性固体 (TSS),pH,可定位酸度 (TA),盐度和乳酸细菌 (LAB).

主要成果:

对于不同的参数,PLS模型显示了不同的预测与偏差比率 (RPD) 值.
使用特征波长的优化SVR模型实现了pH (Rp2 = 0.9166,RPD = 3.281) 和LAB (Rp2 = 0.8488,RPD = 2.466) 的高预测精度.
基于HSI的可视化有效地说明了质量指标随时间的分布.

结论:

拟议的HSI战略提供了一种可靠且非破坏性的方法来监测金发酵.
化学测量分析提高了HSI在预测关键质量属性的能力.
这种方法可以在金生产和储存期间用于实时质量控制.

关键词:

二维相关性光谱学矩阵的二维相关性.金发酵的特点金发酵的特点这就是PLS PLS.这是一个SVRSVR.短波红外线是短波的红外线.视觉化的可视化

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