近红外光谱技术结合IDBO-SVR实时监测姜黄素逆流提取中多组分含量

doi:10.7506/spkx1002-6630-20250811-054

食品科学 ›› 2026, Vol. 47 ›› Issue (4): 172-179.doi: 10.7506/spkx1002-6630-20250811-054

近红外光谱技术结合IDBO-SVR实时监测姜黄素逆流提取中多组分含量

张恺琦，查丽，车鑫，王立红

（贵州中医药大学药学院，贵州贵阳 550025）

出版日期:2026-02-25 发布日期:2026-03-16
基金资助:
大同市科技局重点研发计划基金项目（2023013）

Near-Infrared Spectroscopy Combined with Support Vector Regression Optimized by Hybrid Strategy Improved Dung Beetle Optimizer for Real-Time Monitoring of the Contents of Multiple Components during Counter-Current Extraction of Curcumin

ZHANG Kaiqi, ZHA Li, CHE Xin, WANG Lihong

(College of Pharmacy, Guizhou University of Traditional Chinese Medicine, Guiyang 550025, China)

Online:2026-02-25 Published:2026-03-16

摘要/Abstract

摘要： 为实时监测逆流提取过程中多组分指标含量变化，以逆流提取的姜黄素类特征成分为实验对象，首先采集各提取点的近红外光谱数据，采用高效液相色谱（high performance liquid chromatography，HPLC）法测定目标组分的含量作为参考值，然后通过光谱预处理与变量筛选方法优化光谱数据，并分别采用混合策略改进的蜣螂优化算法（hybrid strategy improved dung beetle optimizer，IDBO）、人工蜂鸟优化算法和鲸鱼优化算法对支持向量回归（support vector regression，SVR）模型的关键参数进行优化。结果表明，IDBO-SVR的检测性能最优，其预测集决定系数R2p均大于0.93，寻优效率高。本研究构建的IDBO-SVR模型能在10 s内同步监测提取过程中多组分含量变化，相比传统HPLC法（单样品需40 min）分析效率大幅提升，该模型可实现姜黄素逆流提取过程的可视化监测，为提取过程的实时调控提供技术支撑，进而有效提升提取效率与产品质量稳定性。

关键词: 近红外光谱技术；支持向量回归；逆流提取；姜黄素；混合策略改进的蜣螂优化算法

Abstract: To monitor in real-time changes in the contents of multiple components during the counter-current extraction of curcumin, near-infrared spectra of samples collected at different times were acquired, preprocessed and optimized by variable selection methods. The contents of the target components in the samples were determined by high performance liquid chromatography (HPLC) and used as reference values. The key parameters of the support vector regression (SVR) model were optimized by hybrid strategy improved dung beetle optimizer (IDBO), artificial hummingbird algorithm (AHA), or whale optimization algorithm (WOA). The results indicated that the IDBO-SVR model performed best, with coefficients of determination of prediction (R2p) exceeding 0.93. It enabled simultaneous monitoring of changes in the contents of multiple components within 10 seconds, faster than traditional HPLC (40 minutes per sample). This model facilitates visual monitoring of curcumin counter-current extraction, providing technical support for real-time process control to enhance extraction efficiency and product quality stability.

Key words: near-infrared spectroscopy; support vector regression; countercurrent extraction; curcumin; hybrid strategy improved dung beetle optimizer

中图分类号:

O657.33

张恺琦，查丽，车鑫，王立红. 近红外光谱技术结合IDBO-SVR实时监测姜黄素逆流提取中多组分含量[J]. 食品科学, 2026, 47(4): 172-179.

ZHANG Kaiqi, ZHA Li, CHE Xin, WANG Lihong. Near-Infrared Spectroscopy Combined with Support Vector Regression Optimized by Hybrid Strategy Improved Dung Beetle Optimizer for Real-Time Monitoring of the Contents of Multiple Components during Counter-Current Extraction of Curcumin[J]. FOOD SCIENCE, 2026, 47(4): 172-179.

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近红外光谱技术结合IDBO-SVR实时监测姜黄素逆流提取中多组分含量

Near-Infrared Spectroscopy Combined with Support Vector Regression Optimized by Hybrid Strategy Improved Dung Beetle Optimizer for Real-Time Monitoring of the Contents of Multiple Components during Counter-Current Extraction of Curcumin

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