Health risk assessment of PAHs in fruit juice samples marketed in city of Tehran, Iran

The objective of the present study was to investigate the level of 16 PAHs in fruit juice samples (orange, apple, peach, pineapple, and mango) with three different packages (PET bottle, Tetra Pak, and canned packaging) by using MSPE/GC-MS (magnetic solid-phase extraction and gas chromatography-mass spectrometry) method. In this method limit of detection (LOD), and limit of quantitation (LOQ), and recovery were 0.030-0.280 μg/L, 0.090-0.840 μg/L, and 94.8-102%, respectively. Our results showed the median of total PAHs and PAH4 (in all samples) were 7.67 ± 3.19 and 0.370 ± 0.160 μg/L, respectively. The median of BaP in samples was )0.060 ± 0.030 μg/L( lower than the standard level (0.200 μg/L in drinking water) of US Environmental Protection Agency (USEPA). Also, our results showed that pineapple juice had a maximum median of total PAHs of 12.4 ± 4.84 μg/L and mango juice had a minimum median of total PAHs of 5.17 ± 1.24 μg/L. Additionally, canned packaging had a maximum average total PAHs of 10.6 ± 5.22 μg/L and PET bottles had a minimum average total PAH of 5.25 ± 2.03 μg/L. A heat map approach was also used to cluster samples. The Monte Carlo results indicated that the estimated daily intake (EDI) rank order was Na > B(g)P > Ch > I(cd)P > B(b)F > Ph > B(k)F > F > Ace > Fl > B(a)P > B(a)A > P >A. The Monte Carlo simulation (MCS) results showed the incremental lifetime cancer risk (ILCR) at the 95th percentiles for adults and children was 4.91 × 10^-7 and 9.12 × 10^-7, respectively. It is concluded that the concentration of PAHs compounds in Iranian fruit juices is lower than the existing standards, and in terms of the risk of carcinogenesis, it does not threaten the human health (< 10^-6).

Concentration and health risk assessment of polycyclic aromatic hydrocarbons in commercial tea and coffee samples marketed in Iran

The aim of the current study was to evaluate the probabilistic health risk and the concentration of 16 polycyclic aromatic hydrocarbons (PAHs) in commercial tea and coffee samples. For determining the mentioned contaminants in sixty-four samples, a reliable and sensitive technique was validated and developed. The technique is established on magnetic solid-phase extraction and gas chromatography-mass spectrometry analysis (MSPE/GC-MS). The maximum mean of ƩPAHs in coffee samples was 13.75 ± 2.90 μg kg^-1, while the minimum mean ƩPAHs in tea samples was 4.77 ± 1.01 μg kg^-1. The mean concentration of benzo(a)pyrene (BaP) in samples ranged from 0.64 to 2.07 μg kg^-1 which was lower than that of standard levels (10 μg kg^-1) established by the European Union (EU). The Monte Carlo simulation results showed that the actual target hazard quotient (THQ) for the adult and children was equal to 1.63E-04 and 1.67E-04, respectively; hence, non-carcinogenic health risk for consumers is negligible. The result of actual incremental lifetime cancer risk (ILCR) was lower than the limits of safe risk (1E-4), indicating no notable possibility of cancer risk due to the digestion of tea and coffee for children and adults. Therefore, it can be concluded that the amount of contamination of popular commercial coffee and tea available in the Iranian market with PAHs is often similar to that found in other countries and was lower than the standard of EU. Thus, the processing conditions of these products must be controlled to prevent the formation of PAHs due to the suspicion of carcinogenicity and mutation.

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.

Migration modelling of phthalate from non-alcoholic beer bottles by adaptive neuro-fuzzy inference system

BACKGROUND

There are limitations to the basic knowledge regarding various ways by which packaging components migrate into food as well as ways by which various conditions, elements and molecules related to this phenomenon are analysed. This research aimed to model phthalate migration from polyethylene terephthalate bottles containing non-alcoholic beer by performing adaptive neuro-fuzzy inference system (ANFIS) analysis.

RESULTS

The data showed that storage temperature, contact surface and storage period correlates with the rate of migration. Migration of phthalate increases with storage duration gradually and reduces under different temperatures and contact surface. Moreover, increased temperature and storage duration resulted in an increase in migration level ranging from 0.6 μg L^-1 to 2.9 μg L^-1 . In summary, the present study used an ANFIS architecture which consists of three inputs (temperature, surface and storage period), Gauss-bell membership functions for each input variable and one output layer, which represent the migration level. The validation and training models showed an excellent match between the experimental and predicted values of ANFIS.

CONCLUSION

Analysis of the model showed that ANFIS is a powerful tool for predicting phthalate migration from bottles containing non-alcoholic beer. © 2017 Society of Chemical Industry.