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采用多元动力学方法对迷迭香叶树脂(Rosmarinus officinalis L.)稳定的向日葵油混合物进行分类

Classification of Sunflower Oil Blends Stabilized by Oleoresin Rosemary (Rosmarinus officinalis L.) Using Multivariate Kinetic Approach.

作者信息

Upadhyay Rohit, Mishra Hari Niwas

机构信息

Agricultural & Food Engineering Dept, Indian Inst. of Technology Kharagpur, Kharagpur, 721302, West Bengal, India.

出版信息

J Food Sci. 2015 Aug;80(8):E1746-54. doi: 10.1111/1750-3841.12966. Epub 2015 Jul 3.

Abstract

The sunflower oil-oleoresin rosemary (Rosmarinus officinalis L.) blends (SORB) at 9 different concentrations (200 to 2000 mg/kg), sunflower oil-tertiary butyl hydroquinone (SOTBHQ ) at 200 mg/kg and control (without preservatives) (SO control ) were oxidized using Rancimat (temperature: 100 to 130 °C; airflow rate: 20 L/h). The oxidative stability of blends was expressed using induction period (IP), oil stability index and photochemiluminescence assay. The linear regression models were generated by plotting ln IP with temperature to estimate the shelf life at 20 °C (SL20 ; R(2) > 0.90). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to classify the oil blends depending upon the oxidative stability and kinetic parameters. The Arrhenius equation adequately described the temperature-dependent kinetics (R(2) > 0.90, P < 0.05) and kinetic parameters viz. activation energies, activation enthalpies, and entropies were calculated in the range of 92.07 to 100.50 kJ/mol, 88.85 to 97.28 kJ/mol, -33.33 to -1.13 J/mol K, respectively. Using PCA, a satisfactory discrimination was noted among SORB, SOTBHQ , and SOcontrol samples. HCA classified the oil blends into 3 different clusters (I, II, and III) where SORB1200 and SORB1500 were grouped together in close proximity with SOTBHQ indicating the comparable oxidative stability. The SL20 was estimated to be 3790, 6974, and 4179 h for SO control, SOTBHQ, and SORB1500, respectively. The multivariate kinetic approach effectively screened SORB1500 as the best blend conferring the highest oxidative stability to sunflower oil. This approach can be adopted for quick and reliable estimation of the oxidative stability of oil samples.

摘要

采用Rancimat法(温度:100至130°C;气流速率:20L/h)对9种不同浓度(200至2000mg/kg)的向日葵油-迷迭香叶油树脂(迷迭香(Rosmarinus officinalis L.))混合物(SORB)、200mg/kg的向日葵油-叔丁基对苯二酚(SOTBHQ)以及对照品(无防腐剂)(SO对照品)进行氧化。混合物的氧化稳定性通过诱导期(IP)、油脂稳定性指数和光化学发光分析来表示。通过绘制ln IP与温度的关系图生成线性回归模型,以估算20°C下的货架期(SL20;R(2)>0.90)。主成分分析(PCA)和层次聚类分析(HCA)用于根据氧化稳定性和动力学参数对油脂混合物进行分类。阿伦尼乌斯方程充分描述了温度依赖性动力学(R(2)>0.90,P<0.05),并计算了动力学参数,即活化能、活化焓和熵,范围分别为92.07至100.50kJ/mol、88.85至97.28kJ/mol、-33.33至-1.13J/mol K。使用PCA时,在SORB、SOTBHQ和SO对照品样品之间观察到了令人满意的区分。HCA将油脂混合物分为3个不同的簇(I、II和III),其中SORB1200和SORB1500与SOTBHQ紧密分组在一起,表明具有相当的氧化稳定性。SO对照品、SOTBHQ和SORB1500的SL20分别估计为3790、6974和4179小时。多变量动力学方法有效地筛选出SORB1500为赋予向日葵油最高氧化稳定性的最佳混合物。该方法可用于快速可靠地评估油样的氧化稳定性。

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