Chen Tong, Qi Xingpu, Chen Mingjie, Chen Bin
School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Jiangsu Agri-animal Husbandry Vocational College, No. 8 East Phoenix Road, Taizhou, Jiangsu 225300, China.
J Anal Methods Chem. 2019 Aug 4;2019:3163204. doi: 10.1155/2019/3163204. eCollection 2019.
In this work, gas chromatography-ion mobility spectrometry (GC-IMS) was used to analyze the volatile organic compound changes of rapeseed oil with different refined grades, the odor fingerprints of refined rapeseed oil were constructed, and a nonlinear model was built to realize rapid and accurate discrimination of rapeseed oil with different refined grades. 124 rapeseed oil samples with different refined grades were collected and analyzed by GC-IMS and chemometric tools, and 34 characteristic peaks were selected by the colorized difference method as variables to characterize the internal quality in rapeseed oil of different refined grades. The principal component analysis algorithm was used to further reduce dimensionality and extract the most relevant information. The -nearest neighbor algorithm was applied to build a discriminant model. All the samples were recognized accurately without errors, and the results show the potential of this method to discriminate different refined grades of vegetable oil.
在本研究中，采用气相色谱 - 离子迁移谱（GC - IMS）分析不同精炼等级菜籽油中挥发性有机化合物的变化，构建精炼菜籽油的气味指纹图谱，并建立非线性模型以实现对不同精炼等级菜籽油的快速准确鉴别。收集了124个不同精炼等级的菜籽油样品，通过GC - IMS和化学计量学工具进行分析，并采用彩色差异法选择34个特征峰作为变量来表征不同精炼等级菜籽油的内在品质。利用主成分分析算法进一步降维和提取最相关信息。应用 - 最近邻算法建立判别模型。所有样品均被准确无误地识别，结果表明该方法在鉴别不同精炼等级植物油方面具有潜力。
