亚麻油中主要组分的定量分析法

Quantitative analysis method of primary components in linseed oil

用厚度为 1 cm的玻璃比色皿作为吸收池 ,测定了亚麻油的近红外光谱 ,利用70 0 0～ 60 0 0 cm- 1 范围内的透波率 ,建立了主成分回归分析模型和 BP人工神经网络模型 ,用二模型预测了亚麻油中油酸、亚油酸和亚麻酸的含量 ,预测结果的平均相对误差均在 2 %以内 ,并且 BP人工神经网络模型预测的效果较好 .该法可用于亚麻油中主要组分的实时成分分析 .

Using a 1cm glass cell as the absorption cell, the spectra of linseed oil was determined and analyzed. The transmittance in 7 000～6 000 cm -1 were analyzed with principal component regression and BP artificial neural network (ANN). The content of oleic acid , linoleic acid and linolenic acid in linseed oil were forecasted. The average of the relative error of the forecasted results is less than 2%, and BP ANN has a better outcome. This method can be developed into a real time quantificational analysis of primary components in linseed oil.