| Literature DB >> 31245650 |
Yasiel Arteaga Crespo1, Luis Ramón Bravo Sánchez1, Yudel García Quintana1, Andrea Silvana Tapuy Cabrera1, Abdel Bermúdez Del Sol2, Dorys Magaly Guzmán Mayancha1.
Abstract
Essential oils (EOs) are known for their antioxidant properties, and are widely employed in the food industry as preservatives. They can be used as condiments or as preservatives to achieve certain organoleptic effects for consumers. The aim of this research was to evaluate antioxidant activity in mixtures of three EOs: Apium graveolens L., Thymus vulgaris L. and Coriandrum sativum L., using the Simplex Lattice Mixture Design. Ultimately, a linear model was used, as it best adjusted to the experimental behavior, and it allowed the prediction of EOs mixtures antioxidant activity, determined by FRAP and ABTS techniques. The mixture of the three EOs that showed the best antioxidant activity and also had the highest synergistic effect, was composed of 66.7% of T. vulgaris, 16.7% of C. sativum and 16.7% of A. graveolens. The greatest contribution to the potentiation of antioxidant activity was shown by T. vulgaris followed by A. graveolens and then C. sativum.Entities:
Keywords: Additives; Aromatic crops; Food science; Natural antioxidants; Spice
Year: 2019 PMID: 31245650 PMCID: PMC6582160 DOI: 10.1016/j.heliyon.2019.e01942
Source DB: PubMed Journal: Heliyon ISSN: 2405-8440
Experimental conditions of mixture design. Antioxidant experimental activity and synergistic effect calculated from individual ingredients.
| Mixture | Ingredient proportions | Measured antioxidant | Synergistic effect (%) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| FRAP (g Eq. Trolox L−1) | ABTS (% Inhibition) | ||||||||||
| Actual value | Predicted value | Residual | Actual value | Predicted value | Residual | FRAP | ABTS | ||||
| 1 | 1/6 | 1/6 | 2/3 | 61.5 | 61.31 | 0.26 | 19.0 | 18.69 | 0.35 | 10.1 | 8.0 |
| 2 | 1/2 | 1/2 | 0 | 169.2 | 163.49 | 5.72 | 52.4 | 51.77 | 0.7 | 8.9 | 4.9 |
| 3 | 1 | 0 | 0 | 19.9 | 23.24 | −3.33 | 3.2 | 3.89 | −0.68 | 0 | 0 |
| 4 | 0 | 1/2 | 1/2 | 169.5 | 156.98 | 12.57 | 51.9 | 50.9 | 1.02 | 13.2 | 5.7 |
| 5 | 0 | 1 | 0 | 288.2 | 303.74 | −15.51 | 96.5 | 99.64 | −3.12 | 0 | 0 |
| 6 | 1/6 | 2/3 | 1/6 | 226.5 | 208.07 | 18.5 | 72.1 | 67.44 | 4.7 | 13.3 | 9.7 |
| 7 | 0 | 0 | 1 | 5.9 | 10.22 | −4.26 | 1.3 | 2.16 | −0.83 | 0 | 0 |
| 8 | 0 | 1 | 0 | 298.0 | 303.74 | −5.72 | 98.5 | 99.64 | −1.12 | 0 | 0 |
| 9 | 1 | 0 | 0 | 21.0 | 23.24 | −2.18 | 3.5 | 3.89 | −0.38 | 0 | 0 |
| 10 | 2/3 | 1/6 | 1/6 | 69.3 | 67.82 | 1.5 | 19.5 | 19.56 | 0.023 | 10.1 | 5.7 |
| 11 | 0 | 0 | 1 | 6.1 | 10.22 | −4.06 | 1.6 | 2.16 | −0.54 | 0 | 0 |
| 12 | 1/2 | 0 | 1/2 | 14.8 | 16.73 | −1.87 | 2.3 | 3.03 | −0.66 | 12.9 | 4.2 |
| 13 | 1/3 | 1/3 | 1/3 | 110.7 | 112.4 | −1.61 | 35.7 | 35.23 | 0.52 | 5.5 | 5.7 |
non-randomized sequence.
Analysis of variance (ANOVA) for linear model.
| FRAP | Sum of Squares | df | Mean Square | F Value | p-value Prob > F | |
|---|---|---|---|---|---|---|
| Model Linear | 15561.76 | 2 | 7780.88 | 2100.33 | <0.0001 | significant |
| Residual | 37.05 | 10 | 3.7 | |||
| Lack of Fit | 34.96 | 7 | 4.99 | 7.18 | 0,0664 | not significant |
| Pure Error | 2.09 | 3 | 0.7 | |||
| Cor Total | 15598.8 | 12 | ||||
| Model Linear | 1.38E+05 | 2 | 68752.6 | 794.55 | <0.0001 | significant |
| Residual | 865.3 | 10 | 86.53 | |||
| Lack of Fit | 816.69 | 7 | 116.67 | 7.2 | 0,0667 | not significant |
| Pure Error | 48.6 | 3 | 16.2 | |||
| Cor Total | 1,38E+05 | 12 |
Fig. 1Relationship between experimental and predicted values and residues vs. run number (A and B, FRAP method; C and D, ABTS method).
Fig. 2Antioxidant responses of the mixture of A. graveolens, T. vulgaris and C. sativum (A and B, FRAP method; C and D, ABTS method).
Fig. 3Relationship between FRAP and ABTS assays.