Analysis Of Phenolic Antioxidant Interactions In Olive Oil And Their Applications Using Molecular Simulations And Artificial Neural Networks

In this paper,four antioxidants,tert-butylhydroquinone（TBHQ）,flavanol（TP）,syringic acid（CA）,and hydroxytyrosol（DOPET）,were used as the main objects of study.Investigating the interaction between compounded antioxidants and the effect of antioxidant on olive oil were invested through a combination of multi-scale molecular simulation,experimental analysis and artificial neural network.The main research content is as follows:（1）Molecular simulation section:first,the molecular unit model was constructed from the perspective of molecular structure by quantum mechanical simulation（QM）.By comparing the magnitude of the bond dissociation energy,it was found that TBHQ had the lowest hydroxyl dehydrogenation dissociation energy,followed by TP,DOPET and CA.Then,there was LUMO energy level distribution in the hydroxyl position of the antioxidant,which further proved that the hydroxyl position was the active site of the antioxidant involved in chemical reactions.The transition state energy of TBHQ was much smaller than that of TP,indicating that TBHQ was more stable than TP in binding to oil radicals.Secondly,the molecular dynamics simulation（MD）was used to calculate the solubility parameters（）,mean square displacement（MSD）,diffusion coefficient（D）and binding energy(E_binding)of the whole system.TBHQ and TP were found to have high migration resistance,good compatibility and dispersion with olive oil.（2）Experimental analysis section:the antioxidant properties of olive oil were determined by infrared total reflectance spectroscopy,DPPH radical scavenging ability test and DSC oxidation induction period test with different antioxidants and 1:1combination of two.The results showed that the compounded antioxidants CA and TP gradually exerted synergistic effects with increasing aging time when the samples were aged at 80℃for 2,4 and 6 days,respectively.Meanwhile,this system had the most stable DPPH free radical scavenging ability and the best effect in inhibiting the production of carbonyl groups in oils and fats.（3）Artificial neural network:based on the molecular simulations and experimental results of the four antioxidants,the natural antioxidant TP（X∈[0,3.6 mg]）and the synthetic antioxidant TBHQ（Y∈[0,1.8 mg]）were selected as the main objects of study.First,through the calculation of bias and interference degree,When X+2Y>3.6,TBHQ is the main antioxidant,on the contrary,TP is the main antioxidant.When Y+1.1X>2.3,the interaction between TP and TBHQ shows a synergistic effect,on the contrary,it is an antagonistic effect.Meanwhile,the established model found that the best antioxidant effect on olive oil was achieved when X and Y were added at 3.6 mg and 1.8 mg,respectively.Then,the ratio of carbonyl absorption peak（C=O）to methylene absorption peak（CH₂）was analyzed by infrared spectroscopy,which further proved that the compound antioxidant could effectively inhibit the formation of carbonyl group in olive oil.In this paper,we firstly explored the mechanism of antioxidants in olive oil from a microscopic perspective and screened out antioxidants with better antioxidant properties.Second,the quantitative analysis of antioxidant interactions in olive oil was achieved by artificial neural networks.An efficient method is established to identify and quantify the synergistic and antagonistic effects of the compounded antioxidants,which provides ideas and theoretical basis for the selection and practical application of multiple compounding antioxidants.