近红外光谱结合区间偏最小二乘法应用于花生油酸价的测定

采用近红外光谱法结合不同区间偏最小二乘波长筛选法建立花生油酸价的定量分析模型。采用酸碱滴定法测定花生油样本的酸价同时采集近红外光谱数据;采用区间偏最小二乘法(iPLS)、向后区间偏最小二乘法(BiPLS)、移动窗口偏最小二乘法(mwPLS)优选光谱特征区间;采用偏最小二乘法(PLS)对优选出来的谱段建立酸价的定量模型。结果表明,采用mwPLS选择的谱段建立的模型预测效果最佳,RMSECV和RMSEP分别为0.247 76和0.131 5,校正相关系数和预测相关系数分别为0.993 2和0.996 9。因此,近红外光谱结合移动窗口偏最小二乘法可以快速准确测定花生油的酸价。

Determination of acid value of peanut oil by near-infrared spectrometry combined with interval partial least squares

Quantitative analysis model of acid value of peanut oil was performed using near-infrared spectrometry combined with different interval partial least squares (iPLS). Acid value of peanut oil were determined by acid-base titration while NIR spectra data were recorded; three improved partial least squares (PLS) methods, including interval partial least squares (iPLS), backward interval partial least-squares (BiPLS) and moving window partial least-squares (mwPLS), were used to find the most informative ranges; PLS regression models of acid value were built based on the optimal ranges.The results showed that the model by mw PLS method had the best predictive ability, the RMSECV and RMSEP were 0.24776 and 0.1315, and the calibration and prediction coefficient were 0.9932 and 0.9969. Rapidly and accurately determination of acid value of peanut oil can be achieved by NIR combined with mwPLS.