Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 3Citation - Scopus: 3Development of a Yeast-Free Bread Using Legume and Nut Flours in a Gluten-Free Flour: Techno-Functional Characteristics and Sensory Evaluation(Wiley, 2024) Tuna, Ayca; Başer, Filiz; Ortiz-Sola, Jordi; Tokatlı, Figen; Lopez-Mas, Laura; Baser, Filiz; Kallas, Zein; Aguilo-Aguayo, Ingrid; Tokatli, FigenThis study aimed to investigate the effect of combined use of legume and nut flours on physical, nutritional and sensory properties of yeast-free bread by substituting gluten-free flour with hazelnut and white bean flours. Yeast-free bread containing a mixture of 30% hazelnut and white bean flours was found to have the lowest hardness (9.04 N) and the largest specific volume (1.51 mL g-1) compared to the reference gluten-free bread (18 N and 1.43 mL g-1) using a mixture design. Hazelnut and bean flours improved the in vitro starch digestion, reducing rapidly digestible starch by 29% and increasing resistant starch compared to the reference bread. Free choice profiling sensory analysis revealed that the developed breads containing nuts and legumes differed from the standard gluten-free formulation and a commercial product available on the market. The combined use of bean and hazelnut flours was demonstrated as functional ingredients for enhancement of nutritional, sensory and textural aspects. Gluten- and yeast-free bread formulated using combination of white bean and hazelnut flours had significantly better textural and nutritional properties. Free choice profiling showed the different characteristics of the new product compared to standard gluten-free breads based on rice flour and corn starch.dagger imageArticle Citation - WoS: 13Citation - Scopus: 14Uv-Vis Spectroscopy for the Estimation of Variety and Chemical Parameters of Olive Oils(Springer, 2021) Jolayemi, Olusola Samuel; Tokatlı, Figen; Özen, BanuOlive oils produced in different years from different varieties were studied with UV-Vis spectroscopy for classification and prediction. Multivariate models were created with second derivative spectral data, and tested with external validation sets. For varietal classification, orthogonal partial least square discriminant analysis resolved oil samples into various classes with correct classification rate more than 89% for validation set (n = 20). A sample of fresh and stored oils were also classified with a correct classification rate more than 90% for validation set (n = 20). In the predictions of chemical parameters (70 for calibration, 30 for validation), the combination of UV-Vis spectroscopy with orthogonal partial least square regression models showed potential for simultaneous quantification of chlorophylls (0.6-5.6 mg/kg; R-val(2) , 0.79; RPD, 1.97); carotenoids (0.6-3.3 mg/kg; R-val(2), 0.80; RPD, 2.38); ratio of mono to polyunsaturated fatty acids (3.6-8.8; R-val(2) , 0.77; RPD, 1.90), oleuropein derivatives (1.2-62.3 mg/kg; R-val(2) , 0.66; RPD, 1.77), and total phenol content (62.2-505 mg/kg; R-val(2) , 0.67; RPD, 1.74), although showed poor to moderate results for the quantification of free fatty acid (0.3-5.4%; R-val(2), 0.67; RPD, 1.64); monounsaturated fatty acids (66-76.5%; R-val(2) , 0.71; RPD, 1.67); polyunsaturated fatty acids (8.6-18.2%; R-val(2) , 0.73; RPD, 1.65). The models were unable to estimate oxidative stability, saturated fatty acids, and individual phenolics such as hydroxytyrosol, pinoresinol, luteolin, total phenolic acids (R-val(2) , 0.26-0.64; RPD, 0.60-1.52). Results showed the capacities of UV-Vis spectroscopy for classification of olive oils, and prediction of total pigments and phenol content and ratio of mono to polyunsaturated fatty acids.Editorial Citation - Scopus: 1Novel Methodologies for Food Quality and Provenance Fingerprints Assessment(Hindawi Publishing Corporation, 2019) Ceto, Xavier; Diaz-Cruz, Jose M.; Tokatlı, Figen; Lucci, Paolo; Moret, SabrinaThe development of novel reliable methodologies that allow the control, assessment, and prediction of the characteristics of food products is a field under expansion nowadays, especially those that allow their characterization, classification, and authentication. On the one side, the highly competitive global environment in food industry requires continuous innovation and a better sustainable usage of our natural resources in order to improve the high standards of food producers, leading to high value-added products. The linkage of new research ideas with food production provides a competitive advantage to food makers to fulfil the competitive market challenges.Article Citation - WoS: 30Citation - Scopus: 30Discriminative Capacities of Infrared Spectroscopy and E-Nose on Turkish Olive Oils(Springer Verlag, 2017) Jolayemi, Olusola Samuel; Tokatlı, Figen; Buratti, Susanna; Alamprese, CristinaThe potentials of Fourier transform (FT) near- (NIR) and mid-infrared (IR) spectroscopy, and electronic nose (e-nose) on varietal classification of Turkish olive oils were demonstrated. A total of 63 samples were analyzed, comprising Ayvalik, Memecik, and Erkence oils. Spectra were pretreated with standard normal variate and second derivative. Classification models were built with orthogonal partial least square-discriminant analysis (OPLS-DA), considering the single data sets and also the combined FT-NIR-IR spectra. OPLS-DA models were validated both by cross validation and external prediction. All the models gave good results, being the average correct classification percentages in prediction higher than 90% for spectroscopic data and equal to 82% for e-nose data. The combined FT-NIR-IR data set gave the best results in terms of coefficients of determination (0.95 and 0.67). Different e-nose sensors discriminated Ayvalik, Memecik, and Erkence oils, explaining their distinct aromatic profiles.Article Citation - WoS: 27Citation - Scopus: 29Differentiation of Wines With the Use of Combined Data of Uv-Visible Spectra and Color Characteristics(Academic Press Inc., 2016) Şen, İlknur; Tokatlı, FigenUV-visible spectra and color parameters of monovarietal wines with orthogonal partial least square-discriminant analysis (OPLS-DA) were shown to be practical and rapid methods for classification purposes. Red and white wines from the 2006-2009 vintages were characterized in terms of color, anthocyanin content and UV-visible spectra. Syrah and Cabernet Sauvignon wines had high color density and intensity. Kalecik Karasi wines had the highest CIELab parameters and the lowest color density. Boğazkere and Öküzgözü wines showed similarities with respect to their high red color parameters and were distinct from other wines. Merlot, Syrah and Öküzgözü wines had the highest total anthocyanin content (61.9-55. mg/L as median values). White wines made from Chardonnay, Muscat and Emir grapes were found to have different color characteristics. The vintage-based discrimination of red wines was mostly apparent in total anthocyanin contents. Different UV wavelength regions were found to be effective in classification with respect to variety and vintage. Correct classification rates in the validation set were 100% and 75%, for varietal and vintage classifications, respectively. This study demonstrated the potential of combination of UV-visible spectra and color characteristics to be used in the authentication of wines.Article Citation - WoS: 22Citation - Scopus: 23Characterization and Classification of Turkish Wines Based on Elemental Composition(American Society for Enology and Viticulture, 2014) Şen, İlknur; Tokatlı, FigenCommercial wines from 13 native and nonnative varieties in Turkey were analyzed for their elemental composition. Wines from four vintages (2006-2009) were analyzed by inductively coupled plasma with atomic emission spectrometry and mass spectroscopy (ICP-AES and ICP-MS) followed by multivariate statistics to study vintage, varietal, and regional differences. According to the partial least squares-discriminant analysis, wines from western regions could be discriminated with their higher Pb content. The red wines of two native grapes, Boǧazkere and Öküzgözü, were separated from the remaining varieties based on their high Ca and low B and Cu levels. Öküzgözü wines were different from Syrah and Cabernet Sauvignon wines. Similarly, native Emir wines showed differences from Muscat wines. The effective variables for discrimination analysis were natural minerals (Sr, Li, Al, Ba, and B) and minerals originating from agricultural activities, processing, or pollution (Ca, Cu, Mg, Co, Pb, and Ni). Characteristics of Turkish wines from native and nonnative grape varieties such as Cabernet Sauvignon, Merlot, Syrah, and Chardonnay were defined in terms of their mineral content for the first time.Article Citation - WoS: 14Citation - Scopus: 16Classification of Turkish Extra Virgin Olive Oils by a Saw Detector Electronic Nose(John Wiley and Sons Inc., 2011) Kadiroğlu, Pınar; Korel, Figen; Tokatlı, FigenAn electronic nose (e-nose), in combination with chemometrics, has been used to classify the cultivar, harvest year, and geographical origin of economically important Turkish extra virgin olive oils. The aroma fingerprints of the eight different olive oil samples [Memecik (M), Erkence (E), Gemlik (G), Ayvalik (A), Domat (D), Nizip (N), Gemlik-Edremit (GE), Ayvalik-Edremit (AE)] were obtained using an e-nose consisting a surface acoustic wave detector. Data were analyzed by principal component analysis (PCA) and discriminant function analysis (DFA). Classification of cultivars using PCA revealed that A class model was correctly discriminated from N in two harvest years. The DFA classified 100 and 97% of the samples correctly according to the cultivar in the 1st and 2nd harvest years, respectively. Successful separation among the harvest years and geographical origins were obtained. Sensory analyses were performed for determining the differences in the geographical origin of the olive oils and the preferences of the panelists. The panelists could not detect the differences among olive oils from two different regions. The cultivar, harvest year, and geographical origin of extra virgin olive oils could be discriminated successfully by the e-nose.Article Citation - WoS: 40Citation - Scopus: 45Phenolic Characterization and Geographical Classification of Commercial Extra Virgin Olive Oils Produced in Turkey(John Wiley and Sons Inc., 2012) Alkan, Derya; Tokatlı, Figen; Özen, BanuThe aim of this research was to characterize the extra virgin olive oil samples from different locations in the Aegean coastal area of Turkey in terms of their phenolic compositions for two consecutive years to show the classification of oil samples with respect to harvest year and geography. Forty seven commercial olive oil samples were analyzed with HPLC-DAD, and 17 phenolic compounds were quantified. Hydroxytyrosol, tyrosol, vanillic acid, p-coumaric acid, ferulic acid, cinnamic acid, luteolin and apigenin were the characteristic phenols observed in all oil samples for two harvest years. Syringic acid, vanillin and m-coumaric acid were the phenolic compounds appeared in the olive oil depending on the harvest year. Partial least square-discriminant analysis (PLS-DA) of data revealed that oils from the north Aegean and south Aegean areas had different phenolic profiles. The phenolic compounds, which played significant roles in the discrimination of the olive oils, were tyrosol, oleuropein aglycon, cinnamic acid, apigenin and hydroxytyrosol to tyrosol ratio. The Aegean coastal region is the largest olive oil producer and exporter of Turkey. This study shows that the olive oils from different parts of the region have their own defining characteristics that can be used in the authentication studies and geographical labeling of Turkish olive oils. © AOCS 2011.Article Citation - WoS: 8Citation - Scopus: 9Modeling of Polygalacturonase Enzyme Activity and Biomass Production by Aspergillus Sojae Atcc 20235(Springer Verlag, 2009) Tokatlı, Figen; Tarı, Canan; Ünlütürk, Mehmet; Göğüş, NihanAspergillus sojae, which is used in the making of koji, a characteristic Japanese food, is a potential candidate for the production of polygalacturonase (PG) enzyme, which of a major industrial significance. In this study, fermentation data of an A. sojae system were modeled by multiple linear regression (MLR) and artificial neural network (ANN) approaches to estimate PG activity and biomass. Nutrient concentrations, agitation speed, inoculum ratio and final pH of the fermentation medium were used as the inputs of the system. In addition to nutrient conditions, the final pH of the fermentation medium was also shown to be an effective parameter in the estimation of biomass concentration. The ANN parameters, such as number of hidden neurons, epochs and learning rate, were determined using a statistical approach. In the determination of network architecture, a cross-validation technique was used to test the ANN models. Goodness-of-fit of the regression and ANN models was measured by the R 2 of cross-validated data and squared error of prediction. The PG activity and biomass were modeled with a 5-2-1 and 5-9-1 network topology, respectively. The models predicted enzyme activity with an R 2 of 0.84 and biomass with an R 2 value of 0.83, whereas the regression models predicted enzyme activity with an R 2 of 0.84 and biomass with an R 2 of 0.69.Article Citation - WoS: 61Citation - Scopus: 75Optimization of Biomass, Pellet Size and Polygalacturonase Production by Aspergillus Sojae Atcc 20235 Using Response Surface Methodology(Elsevier Ltd., 2007) Tarı, Canan; Göğüş, Nihan; Tokatlı, FigenA two-step optimization procedure using central composite design with four factors (concentrations of maltrin and corn steep liquor (CSL), agitation speed and inoculation ratio) was used in order to investigate the effect of these parameters on the polygalacturonase (PG) enzyme activity, mycelia growth (biomass) and morphology (pellet size) of Aspergillus sojae ATCC 20235. According to the results of response surface methodology (RSM), initial concentrations of maltrin and CSL and agitation speed were significant (p < 0.05) on both PG enzyme production and biomass formation. As a result of this optimization, maximum PG activity (13.5 U/ml) was achievable at high maltrin (120 g/l), at low CSL (0 g/l), high agitation speed (350 rpm) and high inoculation ratio (2 × 107 total spore). Similarly, maximum biomass (26 g/l) could be obtained under the same conditions with only the difference for higher level of CSL requirement. The diameter of pellets in all optimization experiments ranged between 0.05 and 0.76 cm. The second optimization step improved the PG activity by 74% and the biomass by 40%.