Yazar "Can, Aygul" seçeneğine göre listele

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    Development and Characterization of Phytosterol-Enriched Oil Microcapsules for Foodstuff Application
    (Springer, 2018) Tolve, Roberta; Condelli, Nicola; Can, Aygul; Tchuenbou-Magaia, Fideline Laure
    Phytosterols are lipophilic compounds contained in plants and have several biological activities. The use of phytosterols in food fortification is hampered due to their high melting temperature, chalky taste, and low solubility in an aqueous system. Also, phytosterols are easily oxidized and are poorly absorbed by the human body. Formulation engineering coupled with microencapsulation could be used to overcome these problems. The aim of this study was to investigate the feasibility of encapsulating soybean oil enriched with phytosterols by spray-drying using ternary mixtures of health-promoting ingredients, whey protein isolate (WPI), inulin, and chitosan as carrier agents. The effect of different formulations and spray-drying conditions on the microencapsules properties, encapsulation efficiency, surface oil content, and oxidation stability were studied. It was found that spherical WPI-inulin-chitosan phytosterol-enriched soybean oil microcapsules with an average size below 50 mu m could be produced with good encapsulation efficiency (85%), acceptable level of surface oil (11%), and water activity (0.2-0.4) that meet industrial requirements. However, the microcapsules showed very low oxidation stability with peroxide values reaching 101.7 meq O-2/kg of oil just after production, and further investigations and optimization are required before any industrial application of this encapsulated system.
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    Rapid detection of milk fat adulteration in yoghurts using near and mid-infrared spectroscopy
    (Elsevier Sci Ltd, 2020) Temizkan, Riza; Can, Aygul; Dogan, Muhammed Ali; Mortas, Mustafa; Ayvaz, Huseyin
    Both Fourier-transform near-infrared (FT-NIR) and mid-infrared (FT-MIR) spectroscopy with chemometrics were used for the fast detection of milk fat adulteration in yoghurts without sample preparation. Soft independent modelling of class analogy models of both NIR and MIR spectra showed successful detection of milk fat adulteration and identification of the type of adulterant oils. Partial least squares regression models of a representative adulterant yielded high correlation coefficients (above 0.98), low standard error of prediction (lower than 7.12%) and high residual predictive deviation values (above 4.35) for both NIR and MIR spectra. Additionally, regardless of the source of adulterant oils used, separate NIR and MIR PLSR models were developed for quantification of milk fat ratio (%) in yoghurts as an alternative approach to measuring the level of adulterant oil (%); NIR spectroscopy was found to be superior in these models. (C) 2020 Elsevier Ltd. All rights reserved.
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    The potential of near and mid-infrared spectroscopy for rapid quantification of oleuropein, total phenolics, total flavonoids and antioxidant activity in olive tree (Olea europaea) leaves
    (Springer, 2018) Can, Aygul; Ayvaz, Huseyin; Pala, Cigdem Uysal; Condelli, Nicola; Galgano, Fernanda; Tolve, Roberta
    Natural foods and food-related antioxidants such as phenolic phytochemicals are of great interest due to their preventive properties against oxidative damage. Olive tree leaves contain high quality and amount of phenolic compounds including oleuropein and therefore considered as nutraceutically valuable materials. The composition of olive leaves, its phenolics and antioxidant power are influenced by numerous factors causing great variation among samples. Additionally, traditional analytical methods performed to quantify these parameters in each product entail long and complicated sample preparation procedures, the use of toxic chemicals, skilled labors, instrumentation and sophisticated laboratory conditions. One appealing alternative is the use of infrared spectroscopy since it gives information about the food composition quickly and it is a multi-parametric and environmentally friendly choice. Therefore, we investigated the oleuropein, total phenolic content, total flavonoid content and antioxidant activity levels of 23 common cultivars of olive leaves harvested from Turkey and Italy using traditional reference methods and also developed near and mid-infrared based partial least squares regression (PLSR) models to predict these parameters without the need of sample preparation. Internal validations of the PLSR calibration models were done using full cross-validation and yielded very high correlation coefficients (0.95) and low errors in predictions (% standard error of cross-validation for parameters were lower than 7.54%). The levels of all the parameters of interest could be successfully predicted using both NIR and MIR instrumentation within seconds. Overall, infrared spectroscopy along with chemometrics exhibited great potential for future olive leave studies.