桂花酒中山梨酸钾拉曼表面增强预测模型在其他果酒中的传递  

Calibration Transfer of Surface-Enhanced Raman Spectroscopy Quantitative Prediction Model of Potassium Sorbate in Osmanthus Wine to Other Wine

作　　者：杨宇[1] 彭彦昆[1] 李永玉[1] 房晓倩 翟晨[1] 王文秀[1] 郑晓春[1] YANG Yu;PENG Yan-kun;LI Yong-yu;FANG Xiao-qian;ZHAI Chen;WANG Wen-xiu;ZHENG Xiao-chun(College of Engineering,China Agricultural University,National Research and Development Center for Agro-Processing Equipment,Beijing　100083,China)

机构地区：[1]中国农业大学工学院,国家农产品加工技术装备研发分中心,北京100083

出　　处：《光谱学与光谱分析》2018年第3期824-829,共6页Spectroscopy and Spectral Analysis

基　　金：中央高校基本科研业务费专项资金项目(2017GX001)资助

摘　　要：自行搭建的拉曼光谱点扫描系统,以柠檬酸钠还原法配制的SC银溶胶为表面增强剂,建立了桂花酒中山梨酸钾的定量预测模型,模型校正集决定系数(R_C^2)和均方根误差(RMSEC)分别为0.978 9和0.070 3g·kg^(-1),验证集决定系数(R_P^2)和均方根误差(RMSEP)分别为0.934和0.165 7g·kg^(-1)。桂花酒中山梨酸钾的定量预测模型为主光谱模型,结合K/S算法,探讨了基于DS算法和PDS算法将桂花酒主光谱模型向杨梅酒的修正传递方法。结果显示,用K/S算法选取4个杨梅酒样品,基于DS算法传递桂花酒主光谱模型验证结果R_P和RMSEP值分别为0.906 1和0.215 0g·kg^(-1)。K/S算法选取3个杨梅酒样品(窗口宽度为5),基于PDS算法传递桂花酒主光谱模型验证结果R_P和RMSEP值分别为0.905 5和0.225 0g·kg^(-1)。DS算法和PDS算法均可以用少量样品将桂花酒中山梨酸钾的主光谱预测模型有效传递给杨梅酒,实现了一种被测物预测模型在同类物种间的传递,具有重要实用意义。Based on a self-built Raman scanning system and the SERS substrate named SC silver sol which was prepared with sodium citrate reduction method,a quantitativeprediction model of potassium sorbate in osmanthus wine was established.The 34 osmanthus wine samples were divided into calibration set and validation set,and the potassium concentration prediction model was established by multiple linear regression method.The determination coefficient and the root mean square error ofthe calibration set were 0.978 9 and 0.070 3 g·kg-1 respectively,the determination coefficient and the root mean square error of the validation setwere 0.934 and 0.165 7 g·kg-1 respectively.The quantitative prediction model of potassium sorbate in osmanthus wine as the main spectrum model and by using the DS algorithm and the PDS algorithm,discussed the model transfer method of potassium sorbateintwo different wines.The K/S algorithm was used to sort the Raman spectra of bayberry wine.The main spectrum correction matrix wascomposed of osmanthus wine samples which had the same concentration ascalibration matrix.15 bayberry wine samples were prepared to verify the effect of the transfer model.The results of the DS algorithm showed that R P and RMSEP were 0.906 1 and 0.215 0 g·kg-1 respectively.The results of the PDS algorithm showed that R P and RMSEP were 0.905 5 and 0.225 g·kg-1 respectively.DS algorithm and PDS algorithm can be achieved with a small number of samples for effective model transfer,and the best samples of the two methodswere 4 and 3 respectively.In addition,window width of 5 was the best choiceof PDS algorithm.Prediction model of potassium sorbate in osmanthus wine wassuitable for the quantitative prediction of potassium sorbate in red bayberry wine by DS algorithm or PDS algorithm.The DS algorithm and PDS algorithm can achieve the transfer of prediction model for potassium sorbate in different wines.Potassium sorbatein red bayberry wine can be predicted by the prediction model of osmanthus wine.

关 键 词：果酒 山梨酸钾 表面增强拉曼光谱 模型传递 

分 类 号：O657.3[理学—分析化学]