摘要
探讨应用傅立叶近红外光谱法(FNIR)快速定量测定腊肉中亚硝酸盐。腊肉样品经粉碎、混匀后在Antaris II傅立叶近红外光谱分析仪上扫描,获得其近红外光谱与国标法测定的亚硝酸盐和食盐含量数据进行关联,用傅立叶变换近红外光谱技术结合偏最小二乘法(PLS)建立近红外光谱与腊肉亚硝酸盐含量的数学模型并进行预测。模型中,校正决定系数(R2cal)和交叉验证决定系数(R2cv)分别是0.997 49和0.963 98,校正均方差(RMSEC)和交叉验证均方差(RMSECV)分别是0.179和0.880。用该模型对验证集样本进行预测并统计分析,表明预测值与测定值无显著差异。傅立叶近红外光谱技术快速测定腊肉中亚硝酸盐是可行的。
Nitrite of Chinese bacon was determined by using Fourier transform near-infrared spectroscopy （FT- NIR） for exploring a rapid determination of them. The samples were scanned on the Antaris II FTNIR reflected spectra instrument after being smashed and admixture. The spectra was connectioned with content data of Nitrite from National Standard Method. A correlation model of near-infrared spectrum and Nitrite content in Chinese bacon was established and the Nitrite contents in Chinese bacon samples were predicted by using Fouriertransform near-infrared spectroscopy （FT-NIR） combined with partial least squares （PLS）. In the correlation model of Nitrite ,the calibration coefficient of determination （R2c~） and validationcoefficient of determination （R2,,v） are 0.997 49 and 0.963 98 respectively;root mean standard error of estimation （RMSEE） and root mean standard error cross validation （RMSECV） are 0.179 and 0.880 respectively.The model was used to verify samples and the statistical results showed that there is no significant difference between the predictive and chemical values. FF-NIR spectroscopy analysis technology can be used for rapid detecting Nitrite in the Chinese Bacon.
出处
《食品研究与开发》
CAS
北大核心
2013年第17期89-91,共3页
Food Research and Development
基金
重庆市科技攻关计划项目(CSTC
2009AB1173)
关键词
近红外光谱
亚硝酸盐
腊肉
偏最小二乘法
快速测定
spectroscopy （FT-NIR）
nitrite
Chinese bacon
partial least squares （PLS）
rapid determination
