芝麻油掺伪的近红外透射光谱检测技术

采用近红外光谱技术结合间隔偏最小二乘法分别建立芝麻油中掺入大豆油、玉米油和花生油的定量检测模型。实验配制不同比例的掺假芝麻油混合样品,采集样品在4 000～12 000 cm-1范围内的近红外透射光谱,把数据分为校正集与预测集。将4 420～12 000 cm-1波段的光谱进行各种预处理,最佳方法为平滑预处理,并利用间隔偏最小二乘波长筛选法(iPLS)选取光谱特征波段,最后采用偏最小二乘法建立掺假芝麻油的定标模型。结果显示:3种掺假芝麻油的PLS模型预测相关系数分别达到0.998、0.999、0.999,预测均方根误差分别为0.24%、0.24%和0.19%,具有较高的预测精度。实验证明近红外光谱技术对芝麻油掺假的快速检测具有可行性。

Analysis of Sesame Oil Adulteration Using Near Infrared Transmission Spectroscopy

Near-infrared spectroscopy(NIRS) quantitative detection models of sesame oil adulterated respectively with soybean oil,corn oil and peanut oil were established by interval partial least squares(iPLS).Mixed samples of sesame and adulterated oils with different proportions were scanned by using a FT-NIR spectrometer and the near infrared transmission spectra were collected in 4000 ~12000cm-1 region which divided into calibration and prediction set.The spectra in 4420~12000cm-1 region was pretreated with different ways and the best was Savitzky-Golay moving.The characteristic wavelength bands were selected by iPLS and the quantitative models were established by PLS finally.The results showed that predicted correlation coefficients of the models built with PLS for three kinds of vegetable oil reached to 0.998,0.999,0.999 respectively,while the root mean square error of prediction were 0.24%,0.24%,0.19%,which have high accuracy.The experiments proved that NIRS technique used for rapid detection of adulterated oil in sesame oil possesses certain feasibility.