Determination of Peroxide Value in Sunflower Halva using a Spectrophotometric Method

Mureşan, Vlad; Muste, Sevastița; Racolța, Emil; Semeniuc, Cristina Anamaria; Man, Simona; Birou, Anamaria; Chircu, Carmen

doi:10.15835/buasvmcn-agr:5116

Cited by 17 publications

(4 citation statements)

References 9 publications

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“…Peroxide value (PV) of liposome was evaluated using the method of Shantha & Decker (1994) (detailed in Appendix S1) by the equation given by Muressan et al . (2010) (Eq. 1), using the standard curve of Fe 3+ .

PV (mEq O_{2} false/ kg fat) = \frac{normalAbs}{55.84 \times w} \times \frac{1}{normalb}

…”

Section: Methodsmentioning

confidence: 99%

Nanoliposomal encapsulation of chia oil for sustained delivery of α‐linolenic acid

Choudhary

Dutta

Moses

et al. 2021

Int J of Food Sci Tech

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Summary Chia oil is a popular source of ω‐3 fatty acids, typically α‐linolenic acid. This study reports the encapsulation of chia oil in nanoliposome to protect ω‐3 fatty acids and to obtain a sustained release of chia oil during digestion. Nanoliposomal encapsulation was carried out using solvent evaporation, followed by sonication. The encapsulation process was conducted using different lipid contents, with different concentrations of soy phosphatidylcholine (S), Tween 80 (T) and volumes of the aqueous phase. The maximum encapsulation efficiency was found to be 88.31%, and the average particle size was 49.25 nm; a moderate repulsion among the particles was observed. Differential scanning calorimetry study revealed enhanced thermal stability of chia oil in nanoliposomes. A negligible release (3.39%) of encapsulated chia oil was observed in the simulated gastric fluid, and a 74.72% sustained release was recorded in the simulated intestinal fluid. This formulation can be a suitable supplement of ω‐3 fatty acids for food and therapeutic applications.

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PV (mEq O_{2} false/ kg fat) = \frac{normalAbs}{55.84 \times w} \times \frac{1}{normalb}

…”

Section: Methodsmentioning

confidence: 99%

Nanoliposomal encapsulation of chia oil for sustained delivery of α‐linolenic acid

Choudhary

Dutta

Moses

et al. 2021

Int J of Food Sci Tech

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“…116 This can be observed via the work of Guarrasi et al 108 wherein the upper limit of linoleic acid (65 mM) in soybean oil after dilution as per the PV test (Table 2) would be equivalent to 12 mM. 41 The reaction time used in the PV test varies significantly across the literature, 50,85,88,117,118 with the majority employing a reaction time of <1 h. The bias induced by OE in the PV test was simulated with our kinetic model with peroxide and OE concentrations relevant to the oil matrix. Details on this model are provided in Section S8.…”

Section: Discussionmentioning

confidence: 99%

Potential Matrix Effects in Iodometry Determination of Peroxides Induced by Olefins

Gautam

et al. 2022

J. Phys. Chem. A

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Peroxides (H 2 O 2 , ROOR, and ROOH) are an important reaction intermediate involved in a number of natural processes, including atmospheric autoxidation and lipid peroxidation in oils and animal tissues. Iodometry is an established spectroscopic technique that has been widely used to quantify total peroxide concentration in food, indoor, and outdoor samples. Iodometry provides selectivity toward peroxides through a quantitative reaction between I − and peroxides to form I 3 − via a molecular iodine (I 2 ) intermediate. However, equilibrium changes caused by a potential interaction between olefinic species and I 2 can suppress I 3 − formation, thereby underestimating peroxide concentration. For the first time in the current study, this unrecognized interference posed by olefins (OEs) is systematically investigated to gauge its effects on the accuracy of iodometry. A number of model molecules were investigated. The interference was observed to be unique to OEs, but universally affecting different peroxide species such as H 2 O 2 , tert-butyl hydroperoxide, and aerosol-bound peroxides. A simple kinetic box model was built to explain this chemistry. The measured rate constant for 3-octenoic acid was found to be 0.84 ± 0.02 M −1 s −1 . Overall, our results show matrix effects induced by OEs can underestimate peroxide concentration determined by iodometry for edible oils, indoor environments, and animal fat, but absent in most of the atmospheric samples. Nonetheless, our results point out the importance of this interfering chemistry in matrices enriched with OEs.

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“…Corn oil (Columbus Vegetable Oils, Des Moines, Iowa, USA) was used to provide fat content for the high fat diet, but without significant addition of LOPs, while spent restaurant oil (i.e., used for cooking) from local restaurants (Sanimax Industries Inc, DeForest, WI, USA) was used to provide fat content for the high fat diet containing high amounts of LOPs. The concentration of primary LOPs, specifically lipid peroxides, in the fat sources were measured using a modified version of an iron-based spectrophotometric method as previously described, 34,35 and reported as peroxide value (PV). Secondary LOPs, such as aldehydes and ketones, in the fat sources were measured using p-anisidine value (AV) test as previously described.…”

Section: Methodsmentioning

confidence: 99%

Dietary Lipid Oxidization Products Alter Growth, Adiposity and Gut Microbial Ecology in Prepubertal Porcine Model

Arowolo

Willis

Karabayir

et al. 2022

Preprint

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Elevated levels of dietary fats in westernized diets, associated with increased risk of obesity and other chronic diseases, are increasingly consumed by children in the United States. Cooking practices such as high heat frying and increased use of oxidizable sources of fats have introduced high levels of lipid oxidation products (LOPs) into these diets. The effects of these highly reactive dietary compounds on human biology are largely unstudied, especially in the gut where these compounds are likely present at higher concentrations. Given that the gut microbiome can be influenced by dietary components and then in turn have a systemic impact, we investigated the effects of consuming LOPs on gut bacterial and fungal communities and on growth and body composition during the prepubertal period in a porcine model. The presence of LOPs in the high fat diet reduced growth and body fat gain in the model. The gut microbiome was uniquely altered by both high fat and the presence of LOPs, with notable changes in the abundances of Turicibacterales, Spriochaetales, RF39, Lactobacillales and Erysipelotrichales. The mycobiome was dominated by Kazachstania, a porcine specific yeast, which was only minimally influenced by the dietary regimen. Application of machine learning identified dietary fat and LOPs as strong predictors of body fat. The genus Methanobrevibacter was the key microbial predictor of body fat. This study highlights the need for further studies on the biological effects of LOPs which have become ubiquitous in human, livestock and pet diets in developed countries.

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Determination of Peroxide Value in Sunflower Halva using a Spectrophotometric Method

Cited by 17 publications

References 9 publications

Nanoliposomal encapsulation of chia oil for sustained delivery of α‐linolenic acid

Nanoliposomal encapsulation of chia oil for sustained delivery of α‐linolenic acid

Potential Matrix Effects in Iodometry Determination of Peroxides Induced by Olefins

Dietary Lipid Oxidization Products Alter Growth, Adiposity and Gut Microbial Ecology in Prepubertal Porcine Model

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