基于近红外光谱技术的茶油脂肪酸含量的快速检测

发布时间：2018-09-14 20:15

【摘要】：为快速准确地测定茶油中脂肪酸含量,建立了应用近红外光谱技术检测茶油中脂肪酸含量的方法。选取市售的156份茶油样品,利用气相色谱仪测定其脂肪酸组成及含量,同时采用近红外光谱仪采集油样的光谱数据,并分析原始(R)光谱、SG平滑(SG)光谱和二阶导数变换(SD)光谱与茶油中脂肪酸含量的相关性,采用偏最小二乘回归法(PLSR)比较全光谱波段与显著性波段对建模精度的影响,优选出茶油中脂肪酸含量的定量检测模型。结果表明:茶油中棕榈酸、油酸和亚油酸含量较高,分别为4.428%~10.931%、78.036%~84.621%、7.013%~9.863%;采集的茶油近红外光谱曲线特征变化较为明显,光谱特征峰的位置分布于8 600~8 200、7 300~6 900、6 000~5 500、4 800~4 500和4 500~4 000 cm 1;茶油中棕榈酸含量与R、SG光谱吸光度呈正相关,油酸和亚油酸含量与R、SG光谱吸光度呈负相关,SD光谱数据与棕榈酸、油酸和亚油酸含量之间的相关系数与R和SG光谱吸光度比较,相关性极大被削弱;基于全波段建立的PLSR模型对棕榈酸、油酸和亚油酸含量的整体预测精度略高于显著性波段所建立的模型,校正集相关系数RC和预测集相关系数RP分别为0.837~0.956和0.818~0.938。从模型的复杂程度分析,采用显著性波段建模的输入变量的数量可压缩至全波段建模的25%以下;SG PLSR模型对棕榈酸、油酸和亚油酸含量的综合预测性能最优,相应的RP和预测集均方根误差(RMSEP)分别为0.938、0.930、0.925和0.560、0.438、0.287。
[Abstract]:In order to determine the fatty acid content of tea oil quickly and accurately, a near infrared spectrometric method was established for the determination of fatty acid content in tea oil. The fatty acid composition and content of 156 tea oil samples sold on the market were determined by gas chromatograph, and the spectral data of oil samples were collected by near infrared spectrometer. The correlation between the smooth (SG) spectrum and the second derivative transform (SD) spectrum of the original (R) spectrum and the fatty acid content in tea oil was analyzed. The effects of the full spectral band and the significant band on the modeling accuracy were compared by partial least square regression (PLSR). A quantitative determination model of fatty acid in tea oil was selected. The results showed that the contents of palmitic acid, oleic acid and linoleic acid in tea oil were 4.428, 10.931and 78.03636, respectively, and the content of palmitic acid, oleic acid and linoleic acid in tea oil was 84.62113 and 7.0133.The characteristic changes of the near infrared spectrum curve of tea oil were obvious, the results showed that the content of palmitic acid, oleic acid and linoleic acid in tea oil was 4.428. The position of the spectral characteristic peak was distributed in 8 600 ~ 8 200 ~ 7 300 ~ 6 900 ~ 6 000 ~ 6 000 ~ 5 500 ~ 5 500 ~ 4 800 ~ 4 000 cm ~ (-1) and 4 500 ~ 4 000 cm ~ (-1), the content of palmitic acid in tea oil was positively correlated with the spectral absorbance of RGG, the content of oleic acid and linoleic acid was negatively correlated with the absorption of R ~ (2 +) SG and the SD spectral data were negatively correlated with palmitic acid. The correlation coefficient between the content of oleic acid and linoleic acid was greatly weakened compared with the absorbance of R and SG spectra. The overall prediction accuracy of oleic acid and linoleic acid content is slightly higher than that of the model established in the significant band. The correlation coefficient RC and the correlation coefficient RP of the corrected set and the predicted set are 0.837 ~ 0.956 and 0.818 ~ 0.938, respectively. From the analysis of the complexity of the model, the synthetic prediction performance of palmitic acid, oleic acid and linoleic acid content can be optimized by using the input variables of significant band modeling to 25% or less than 25% of the full-band modeling model, and the results show that the model can be used to predict the content of palmitic acid, oleic acid and linoleic acid. The root mean square error (RMSEP) of the corresponding RP and prediction set were 0.938 0. 930 0. 925 and 0. 560 0. 438 / 0.287, respectively.
【作者单位】： 中南林业科技大学机电工程学院;中南林业科技大学理学院;
【基金】：国家自然科学基金项目(31401281) 湖南省自然科学基金项目(14JJ3115) 湖南省高校科技创新团队支持计划(2014207) 湖南省科技计划重点研发项目(2016NK2151)
【分类号】：TS225.1;O657.3
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