Quality assessment and degradative changes of deep-fried oils in street fried food chain of Kashmir, India

Manzoor, Shaziya; Masoodi, F. A.; Rashid, Rubiya; Ahmad, Mudasir; Kounsar, Mumtahin-ul

doi:10.1016/j.foodcont.2022.109184

Cited by 13 publications

(9 citation statements)

References 33 publications

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Section: Introductionmentioning

confidence: 99%

“…The presence of TFAs and SFAs may be influenced by the use of TFAs- or SFAs-rich ingredients, such as butter [ 7 ] and partially hydrogenated vegetable oils [ 9 , 12 ], and the preparation methods used, such as deep-frying [ 9 , 11 , 13 ]. Practices related to the frying process, such as the reuse of frying oil [ 6 ], the frying temperature [ 14 ], and the duration of frying using different types of oils [ 10 , 13 , 15 , 16 , 17 ], also affect the levels of SFAs and TFAs in foods. As most Malaysian foods incorporate ingredients that are rich in fats, such as coconut milk and peanuts, and approximately 30% of Malaysian street foods are deep-fried [ 18 ], local street foods may contain high amounts of SFAs and TFAs, as well as MUFAs and PUFAs [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

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Fatty Acid Composition of Selected Street Foods Commonly Available in Malaysia

Arifen

Shahril

Shahar

et al. 2023

Foods

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Despite growing evidence of increased saturated and trans fat contents in street foods, little is known about their fatty acid (FA) compositions. This study aimed to analyse the saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), and trans fatty acids (TFAs) content of 70 selected and most commonly available street foods in Malaysia. The street foods were categorised into main meals, snacks, and desserts. TFAs were not detected in any of the street foods. Descriptively, all three categories mainly contained SFAs, followed by MUFAs, and PUFAs. However, the one-way ANOVA testing showed that the differences between each category were insignificant (p > 0.05), and each FA was not significantly different (p > 0.05) from one to another. Nearly half of the deep-fried street foods contained medium to high SFAs content (1.7 g/100 g–24.3 g/100 g), while the MUFAs were also high (32.0–44.4%). The Chi-square test of association showed that the type of preparation methods (low or high fat) used was significantly associated (p < 0.05) with the number of SFAs. These findings provide valuable information about fat composition in local street foods for the Malaysian Food Composition Database and highlight the urgency to improve nutritional composition.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fatty Acid Composition of Selected Street Foods Commonly Available in Malaysia

Arifen

Shahril

Shahar

et al. 2023

Foods

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“…While this approach allows minimizing the potential organoleptic and toxic effects of these compounds, predicting how these mixtures of antioxidants will behave has traditionally been one of the most challenging tasks, − often leading to simple additive (even antagonistic) effects, instead of the desired synergistic response. − Although the interaction between some classes of antioxidants is well-known, there is a current need for a strategy that could enable broader and more rational predictions related to the antioxidant capacity of mixtures. Approaches to understanding these interactions have been predominantly empirically driven, where the total antioxidant effectiveness is assessed by using assays such as total oxidation index (TOTOX), thiobarbituric acid reactive substances (TBARS), peroxide value (PV), p -anisidine test, ferric reducing antioxidant power (FRAP), or DPPH scavenging . The gathered experimental data can be then analyzed as a function of the composition of the antioxidant mixture through the use of standard methods such as isobole diagrams, response curves, or interaction index parameters .…”

Section: Introductionmentioning

confidence: 99%

Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data

Ayres,

Benavidez,

Varillas

et al. 2023

J. Agric. Food Chem.

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Lipid oxidation is a major issue affecting products containing unsaturated fatty acids as ingredients or components, leading to the formation of low molecular weight species with diverse functional groups that impart off-odors and off-flavors. Aiming to control this process, antioxidants are commonly added to these products, often deployed as combinations of two or more compounds, a strategy that allows for lowering the amount used while boosting the total antioxidant capacity of the formulation. While this approach allows for minimizing the potential organoleptic and toxic effects of these compounds, predicting how these mixtures of antioxidants will behave has traditionally been one of the most challenging tasks, often leading to simple additive, antagonistic, or synergistic effects. Approaches to understanding these interactions have been predominantly empirically driven but thus far, inefficient and unable to account for the complexity and multifaceted nature of antioxidant responses. To address this current gap in knowledge, we describe the use of an artificial intelligence model based on deep learning architecture to predict the type of interaction (synergistic, additive, and antagonistic) of antioxidant combinations. Here, each mixture was associated with a combination index value (CI) and used as input for our model, which was challenged against a test (n = 140) data set. Despite the encouraging preliminary results, this algorithm failed to provide accurate predictions of oxidation experiments performed in-house using binary mixtures of phenolic antioxidants and a lard sample. To overcome this problem, the AI algorithm was then enhanced with various amounts of experimental data (antioxidant power data assessed by the TBARS assay), demonstrating the importance of having chemically relevant experimental data to enhance the model’s performance and provide suitable predictions with statistical relevance. We believe the proposed method could be used as an auxiliary tool in benchmark analysis routines, offering a novel strategy to enable broader and more rational predictions related to the behavior of antioxidant mixtures.

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“…During repeated use, nutritional value and safety decrease (Ng et al 2014). Manzoor et al (2022) reported that only 20% of the in-use frying oil and 10% food products were safe for consumption in street vendors in Kashmir. Chen et al (2007) measured gaseous and particulate emissions in Chinese restaurants and reported that deep frying produced the highest amount of total gaseous PAHs, with the dominance of naphthalene ranging between 67-89%.…”

Section: Introductionmentioning

confidence: 99%

Biomonitoring PAH levels in domestic kitchens using commonly grown culinary herbs

Eck-Varanka

Hubai

Kováts

et al. 2023

Preprint

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Cooking is a significant source of polycyclic aromatic hydrocarbon (PAH) emissions in indoor environments. A biomonitoring study was carried out in previously selected rural Hungarian kitchens to evaluate cooking-related PAH concentrations in 4 common kitchen vegetables such as basil, parsley, rocket and chives. After 1 month exposure, PAH accumulation pattern in tested plants clearly indicated differences in cooking methods and cooking oils used in the selected households. Use of lard and animal fats in general resulted in the high concentrations of higher molecular weight (5- and 6-ring) PAHs, while olive oil usage could be associated with the emission of 2- and 3-ring PAHs. Culinary herbs, however, accumulated carcinogenic PAHs such as benzo[a]anthracene, benzo[b]fluoranthene and chrysene which might question their safe use.

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Quality assessment and degradative changes of deep-fried oils in street fried food chain of Kashmir, India

Cited by 13 publications

References 33 publications

Fatty Acid Composition of Selected Street Foods Commonly Available in Malaysia

Fatty Acid Composition of Selected Street Foods Commonly Available in Malaysia

Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data

Biomonitoring PAH levels in domestic kitchens using commonly grown culinary herbs

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