首页|基于近红外光谱技术的蜂胶萃余物中黄酮提取的原位实时监测

基于近红外光谱技术的蜂胶萃余物中黄酮提取的原位实时监测

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[目的]针对蜂胶经过超临界CO2萃取后的萃余物,实时检测该物质在二次提取过程中黄酮类化合物的含量变化。[方法]利用近红外光谱技术,通过收集提取过程中的光谱信息及其相应的黄酮含量化学值,建立定量分析模型,用以实时检测黄酮含量的变化和提取终点的判断。[结果]经过归一化预处理后的近红外光谱数据结合偏最小二乘(PLS)算法所构建模型的校正相关系数(Rc)和校正均方根误差(RMSEC)分别为0。999 1和 0。044 5,预测相关系数(Rp)和预测均方根误差(RMSEP)分别为0。929 1和0。242 7,该原位监测模型具有较好的回归与预测能力。[结论]近红外光谱技术能够快速、精确地监测蜂胶萃余物提取过程中的黄酮含量,实现提取过程的原位实时监测。
In-situ real-time monitoring of flavonoids extraction from propolis extracts based on near infrared spectroscopy
[Objective]For the residue of propolis after supercritical CO2 extraction,the content of flavonoids in the secondary extraction process was detected in real time.[Methods]Near-infrared spectroscopy was used to establish a quantitative analysis model by collecting the spectral information and the corresponding chemical values of flavonoids during the extraction process,which was used to detect the changesof flavonoids content in real time and to determine the end point of extraction.[Results]The Rc(corrected correlation coefficient)and RMSEC(corrected root mean square error)of the model constructed by the PLS(partial least squares)algorithm after normalization preprocessing were 0.999 1 and 0.044 5,respectively.The Rp(prediction correlation coefficient)and RMSEP(the root mean square prediction error)were 0.929 1 and 0.242 7 respectively,which showed that the in-situ monitoring of the model had good regression and prediction ability.[Conclusion]Near-infrared spectroscopy can be used to quickly and accurately monitor the flavonoid content in the extraction process of propolis residue,and realize real-time monitoring in situ.

propolisflavonoidsnear infraredin-situ monitoring

王武力、马海乐、李含、张勇、夏宏

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江苏大学食品物理加工研究院,江苏 镇江 212013

江苏大学食品物理加工省高校重点实验室,江苏 镇江 212013

江苏蜂奥生物科技有限公司,江苏 泰州 225300

蜂胶 黄酮类化合物 近红外 原位监测

泰州市中小企业科技成果转化项目

SCG202214

2024

食品与机械
长沙理工大学

食品与机械

CSTPCD北大核心
影响因子:0.89
ISSN:1003-5788
年,卷(期):2024.40(9)