基于脂肪酸指纹的胡麻油真实性判别模型的建立
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(内蒙古农业大学 食品科学与工程学院, 内蒙古 呼和浩特 010018)

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Establishment of Authenticity Discrimination Model of Flaxseed Oil Based on Fatty Acid Fingerprint
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(College of Food Science and Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

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    摘要:

    胡麻油富含α-亚麻酸,价格是其他食用油的3~20倍,极易被掺假和冒充,因此,基于脂肪酸(fatty acids,FAs) 指纹建立了胡麻油真实性判别模型。采集胡麻油、菜籽油、葵花籽油、大豆油、花生油、玉米油、芝麻油、调和油8种食用油及餐厨垃圾油和地沟油2种废弃油,利用气相色谱法测定油脂中的12种FAs,进行主成分分析(principal component analysis,PCA),观察10种油脂以FAs聚类的特征,用正交偏最小二乘判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)评价以FAs指纹鉴别胡麻油物种、冷热榨工艺及品级真实性的可行性,并建立胡麻油中菜籽油掺假量的偏最小二乘回归(partial least squares,PLS)定量预测模型。胡麻油与其他油脂FAs指纹极其不同,C18∶3ω3质量比为(50.14±9.68)g/100g,显著高于其他油脂;而C18∶1ω9和 C18∶2ω6质量比分别为(16.62±5.02)、(14.62±4.64)g/100g,显著低于其他油脂。PCA和OPLS-DA均可对胡麻油物种、加工方法和品级进行区分,OPLS-DA的鉴别效果更好。PCA和OPLS-DA显示,胡麻油与菜籽油、大豆油聚类最靠近。OPLS-DA对胡麻油物种判别准确率为100.0%,冷热榨判别准确率96.7%,品级判别准确率90.0%。胡麻油物种、加工方法和品级鉴别的关键FAs为C18∶3ω3、C18∶1ω9和C18∶2ω6。胡麻油5种关键FAs与菜籽油掺假量相关性分析显示,C18:3ω3含量与菜籽油掺假量呈极显著负相关,C18∶1ω9和C18∶2ω6含量与菜籽油掺假量呈极显著正相关。胡麻油掺菜籽油样品的PLS定量模型相关系数R2为0.986,校正均方差RMSEE为4.2635,交叉验证均方差RMSEcv为4.2648,掺假量预测误差不超过10%。结果表明:基于FAs指纹建立胡麻油真实性判别模型较为可行,该模型有继续优化的空间。

    Abstract:

    Flaxseed oil is rich in α-linolenic acid, and its price is 3 to 20 times higher than that of other edible oils, and it is very vulnerable to be adulterated and counterfeited. The authenticity discrimination model of flaxseed oil based on fatty acid (FAs) fingerprints was established. Eight kinds of edible oil samples (flaxseed oil, rapeseed oil, sunflower oil, soybean oil, peanut oil, corn oil, sesame oil, blended oil), two kinds of waste oil samples (kitchen waste oil and gutter oil) were collected, and 12 FAs were determined by gas chromatography. Principal component analysis (PCA) was conducted to observe the clustering properties of these 10 kinds of oils according to their FAs fingerprint. Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to evaluate the feasibility of FAs fingerprint on authenticity of species origin, processing methods (cold or hot pressing) and grade of flaxseed oil, and partial least squares (PLS) quantitative prediction model was established to estimate the adulteration dosage of rapeseed oil in flaxseed oil. The FAs fingerprint of flaxseed oil was extremely different from other oils. Content of C18:3ω3[(50.14±9.68)g/100g] was significantly higher than that of other oils, while content of C18:1ω9[(16.62±5.02) g/100g] and C18:2ω6[(14.62±4.64)g/100g] were significantly lower than that of other oils. PCA and OPLS-DA both could distinguish species origin, processing methods and grade of flaxseed oil. OPLS-DA had better discrimination formance. PCA and OPLS-DA showed that flaxseed oil was the closest cluster to rapeseed and soybean oil. Accuracy of OPLS-DA for flaxseed oil species discrimination was 100%, accuracy of cold and hot pressing discrimination was 96.7%, and accuracy of grade discrimination was 90.0%. The key FAs for discrimination of flaxseed oil species, processing methods and grade were C18:3ω3, C18:1ω9 and C18:2ω6. Correlation analysis of five key FAs contents in flaxseed oil and adulteration dosage of rapeseed oil showed that C18:3ω3 content was negatively correlated with rapeseed oil adulteration dosage, C18:1ω9 and C18:2ω6 content were positively correlated with rapeseed oil adulteration dosage. R2 of PLS quantitative discrimination model for flaxseed oil adulterated with rapeseed oil was 0.986, RMSEE was 4.2635, while RMSEcv was 4.2648, and the prediction error of adulteration dosage was no more than 10%. The results showed that it was feasible to establish the authenticity discrimination model of flaxseed oil by FAs fingerprint, and there was optimization space of this mold.

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叶乐,李茹,郭军.基于脂肪酸指纹的胡麻油真实性判别模型的建立[J].食品科学技术学报,2023,41(6):139-149.

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  • 收稿日期:2023-01-31
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  • 在线发布日期: 2023-11-07
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