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

Nazari, Roshanak Rafiei; Noorian, Simin; Arabameri, Majid

doi:10.1002/jsfa.8693

Cited by 15 publications

(10 citation statements)

References 38 publications

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“…In this research, a grid partition for data classification, and a Sugeno first‐order fuzzy inference system with a corresponding equivalent ANFIS structure is used. Interested readers are referred to references for further details about ANFIS, FIS structure, and the hybrid learning algorithm.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2019

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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, -tocopherol, fatty acid profile, ultraviolet (UV) extinction coefficient (K 268 ), 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, -tocopherol was reduced by between 0.52 and 0.91 times during storage, regardless of the storage temperature. The mean specific UV extinction coefficients (K 268 ) 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 (R 2 = 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.(3) X: the input value to the node. J Sci Food Agric 2019; 99: 5358-5367

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Section: Methodsmentioning

confidence: 99%

“…Artificial intelligence can be applied to predict and model food processing and processes such as the bleaching of olive oil, food packaging, wastewater treatment, and drying . The adaptive neuro‐fuzzy inference system (ANFIS) is a popular mathematical model.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…PAEs are used mainly as plasticizers to increase durability, workability, and exibility of polymeric materials in polyethylene terephthalate (PET) packaging or other plastic packaging, But, in addition, they can be present in many products such as inks, paints, cosmetics and adhesives. (Ra ei Nazari et al 2018). The phthalates are not covalently bound to the polymer matrix composites, so easily released from the products and then transported to the environment (with migration way), and nally can cause contaminate air, soil, water, and food products.…”

Section: Introductionmentioning

confidence: 99%

Measurement of phthalate acid esters in non-alcoholic malt beverages by MSPE-GC/MS method in Tehran city: chemometrics

Rezaei

Moazzen

Shariatifar

et al. 2021

Environ Sci Pollut Res

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The goal of this research was to assess the phthalic acid esters (DEP, DMP, BBP, DBP, DEHP, DnOP and total PAE) in non-alcoholic malt beverages bottled were magnetized with iron (MWCNT-Fe3O4) using Mass spectrometry is gas chromatography (GC-MS) in Tehran. The results showed that maximum and minimum of total phthalate esters in samples were 9483.93 and 2412.50 ng/l, respectively. The mean of DEHP (which has also been found to be carcinogenic) in all samples was lower than 5944.73 ng/l. The maximum concentration of DEHP in four samples was upper than 8957.87 ng/l. Multivariate techniques and heat-map visualization were used to assess the correlation among the type and levels of PAEs with brand, color, product date, pH, sugar, volume and gas pressure. Therefore, based on heat-map and principal component analysis (PCA) results, the Bis (2-ethyl hexyl) phthalate (DEHP) and total PAEs were the closest accessions, indicating that these variables had similar trends. Based on the results, it can be stated that due to the low average of total phthalate esters in non-alcoholic malt beverages, there is no serious health hazard of these compounds for humans.

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“…For this, mixture design and RSM can be combined to determine the effects of extraction processing factors. So, combined design was used for obtaining many detailed information about relationship between many independent and dependent factors at specified conditions (Arabameri et al., 2019; Ghelichkhani et al., 2019; Icyer et al., 2016; Rafiei Nazari et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

Use of D‐optimal combined design methodology to describe the effect of extraction parameters on the production of quinoa–barley malt extract by superheated water extraction

Sabah

Sharifan

Basti

et al. 2021

Food Science & Nutrition

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Superheated water extraction was applied to produce quinoa–barley malt extract. D‐optimal combined design was used to optimize the extraction conditions (time (min), solid–water ratio and particle size to obtain maximum protein and carbohydrate content, and minimum turbidity and pH. Quinoa flour (10%–30%), barley malt flour (70%–90%), different particle sizes (F = 420 µm, G = 710 µm), time (15–45 min), and solid–water ratio (0.1–0.2) were selected as independent variable and protein, carbohydrate, turbidity, and pH as dependent factors. Polynomials models satisfactorily fitted the experimental data with the R2 values of .9961, .9909, .9949, and .9987, respectively. The protein and carbohydrate value was affected by superheated water extraction parameters. Our results revealed that increasing quinoa/barley malt ratio has significant effect on the turbidity and pH. The optimum extraction conditions were quinoa flour (30%), barley malt flour (70%), solid–water ratio (0.2), time (45 min), and particle size (F = 420 µm).

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

Abstract: 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.

Cited by 15 publications

References 38 publications

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

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

Measurement of phthalate acid esters in non-alcoholic malt beverages by MSPE-GC/MS method in Tehran city: chemometrics

Use of D‐optimal combined design methodology to describe the effect of extraction parameters on the production of quinoa–barley malt extract by superheated water extraction

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