检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:杜一平[1] 向春兰[1] 黄子夏[1] 方娟娟[1] 孟绮[1] 卫雪梅[1]
机构地区:[1]华东理工大学上海市功能性材料化学重点实验室,上海200237
出 处:《计算机与应用化学》2013年第1期36-38,共3页Computers and Applied Chemistry
基 金:国家自然科学基金(20975039)
摘 要:研究应用漫反射近红外光谱快速鉴别辣椒粉中的苏丹红及其含量测定的方法。利用漫反射模式直接测定含有苏丹红的辣椒粉的近红外光谱,采用多元散射校正(MSC)方法对光谱进行校正,利用主成分分析研究含有苏丹红的辣椒粉和未含苏丹红的辣椒粉空白样品的分类。根据高效液相色谱测定辣椒粉中的苏丹红含量,利用偏最小二乘方法(PLS)建立苏丹红含量与近红外光谱之间的线性模型。结果显示,利用主成分分析可以方便、快速和准确地区分有无苏丹红的辣椒粉;苏丹红含量与近红外光谱具有良好的线性关系,当隐变量数目为7时,PLS模型的预测误差达到0.428μg/g,预测相关系数达0.973。Method of determination and discrimination of sudan red in powered paprika using diffuse reflectance near-infrared spectroscopy (NIRS) was studied. Paprika was detected by diffuse reflectance N1RS directly. Multiplicative scatter correction (MSC) was applied to correct the spectra measured. Identification of sudan red from paprika samples was carried out by Principal Component Analysis (PCA) to the NIR spectra. Partial least squares (PLS) regression was used to build model between the corrected spectra and concentrations of sudan red, which were determined by HPLC, and segmental cross validation was used to search for a reasonable number of PLS factors with minimum root mean squares error of prediction (RMSEP). The results showed that PCA is a rapid and accurate method to discriminate paprika samples containing and not containing sudan red. The minimum RMSEP was 0.428 p.g/g and correlation coefficient of prediction was 0.973 when the latent variable number was 7, meanwhile the relative error was 15.3%.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.104