Systematic transition from description to prediction for the oxidation in packaged olive oil

Investigation on food packaging polymers: Effects on vegetable oil oxidation

Polyethylene (PE), polypropylene (PP), polyamide (PA), and polyethylene terephthalate (PET) surfaces and particles were employed to study effects of polymer materials on linseed oil, peanut oil, rapeseed oil and sunflower seed oil oxidation. The surface types of the materials, hydroperoxide content and volatile in oils were determined by contact angle, Fourier transform infrared spectroscopy and gas chromatography-mass spectrometry. Oils on PP surfaces underwent a more rapid oxidation, followed by PA, PE and PET. Except PP sets, this order was consistent with surface hydrophilicity of polymers. Further study using polymer particles avoiding packaging barrier suggested this was probably due to barrier factors. Although PE surfaces allowed oil to have lower content of hydroperoxides, it can promote oil hydroperoxide decomposition into volatile products. Surface types of polymer materials are correlated with oxidation of contacted oil, and these surfaces can also affect the oil secondary oxidation and the degradation of oxidation products.

The Role of an Acidic Peptide in Controlling the Oxidation Process of Walnut Oil

Here, the mechanism of action of an antioxidant peptide rich in acidic amino acid residues in controlling lipid oxidation is discussed. Firstly, in the presence of this peptide, the fluorescence intensity of lipid peroxide in samples of walnut oil was very low, indicating that the peptide prevented the formation of lipid peroxides. Secondly, the production of lipid-derived radicals of oil was reduced by 23% following addition of the anti-oxidative peptide. Thirdly, Raman shifts of the lipid with the anti-oxidative peptide showed that acidic amino acid residues of the peptide were involved in delaying lipid oxidation. Finally, seven peptide inhibitors were synthesized with variations to the amino acid sequence of the original peptide, and Glu-Asp was proven to enhance the peptide's superoxide anion radical scavenging activity and decrease the formation of linoleic acid peroxides. Our findings emphasize the potential value of acidic amino acid residues in protecting unsaturated fatty acids from oxidation.

Oxidative stability of virgin olive oil: evaluation and prediction with an adaptive neuro-fuzzy inference system (ANFIS)

BACKGROUND

An adaptive neuro-fuzzy inference system (ANFIS) was employed to predict the oxidative stability of virgin olive oil (VOO) during storage as a function of time, storage temperature, total polyphenol, α-tocopherol, fatty acid profile, ultraviolet (UV) extinction coefficient (K₂₆₈ ), and diacylglycerols (DAGs).

RESULTS

The mean total quantities of polyphenols and DAGs were 1.1 and 1.9 times lower in VOOs stored at 25 °C than in the initial samples, and the mean total quantities of polyphenols and DAGs were 1.3 and 2.26 times lower in VOOs stored at 37 °C than in the initial samples, respectively. In a single sample, α-tocopherol was reduced by between 0.52 and 0.91 times during storage, regardless of the storage temperature. The mean specific UV extinction coefficients (K₂₆₈ ) for VOO stored at 25 and 37 °C were reported as 0.15 (ranging between 0.06-0.39) and 0.13 (ranging between 0.06-0.35), respectively. The ANFIS model created a multi-dimensional correlation function, which used compositional variables and environmental conditions to assess the quality of VOO. The ANFIS model, with a generalized bell-shaped membership function and a hybrid learning algorithm (R²  = 0.98; MSE = 0.0001), provided more precise predictions than other algorithms.

CONCLUSION

Minor constituents were found to be the most important factors influencing the preservation status and freshness of VOO during storage. Relative changes (increases and reductions) in DAGs were good indicators of oil oxidative stability. The observed effectiveness of ANFIS for modeling oxidative stability parameters confirmed its potential use as a supplemental tool in the predictive quality assessment of VOO. © 2019 Society of Chemical Industry.