Food Engineering / Gıda Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/12
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Article 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.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: 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: 17Phenolics Profile of a Naturally Debittering Olive in Comparison To Regular Olive Varieties(John Wiley and Sons Inc., 2014) Aktaş, Ayşe Burcu; Özen, Banu; Tokatlı, Figen; Şen, İlknurBACKGROUND: Hurma, an olive variety that grows in a specific area in Turkey, loses its bitterness before harvesting, and therefore does not need further processing steps for the production of table olives. The total phenol content and phenolic profiles of (1) this naturally debittered olive type, Hurma; (2) the same olive variety, but not a naturally debittered type, Erkence; and (3) another variety, Gemlik, which is commonly consumed as table olive, were determined during their maturation period for two harvest years. RESULTS: The total phenol content of Hurma is the lowest compared to the other types regardless of harvest year, which has a significant effect on the phenolic content and composition of individual components for all olive types. All three olive types can be differentiated from each other especially during the late phase of maturation using the phenolics profile in combination with principal component analysis. CONCLUSION: The natural debittering phenomenon of Hurma olive on the tree involves a decrease in phenol content and a change in phenol composition. The differentiation in phenol composition especially becomes very significant in the late of period of maturation.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%.Article Citation - WoS: 76Citation - Scopus: 90Optimization of a Growth Medium Using a Statistical Approach for the Production of an Alkaline Protease From a Newly Isolated Bacillus Sp. L21(Elsevier Ltd., 2006) Tarı, Canan; Gençkal, Hande; Tokatlı, FigenBacillus sp. L21 was isolated from the by-products of a leather factory (located in Izmir, Turkey) working under extreme alkaline conditions. Its phenotypic and genotypic identifications were completed, and determined as a potential alkaline protease producer. After screening various elements, carbon and nitrogen sources, soybean meal, maltose50, tween80 and the initial pH conditions were chosen as main factors to be used in the experimental design and response surface methodology (RSM) for the optimization of a low cost enzyme producing media for potential use on an industrial scale. The optimized values obtained by the statistical analysis showed that soybean meal at 3.0 g/l, maltose50 between the ranges of 30 and 40 g/l, tween80 at 0.35 g/l and an initial pH of 8.0 gives maximum protease activity.Article Citation - WoS: 51Citation - Scopus: 55Kinetic Modelling of Lactic Acid Production From Whey by Lactobacillus Casei (nrrl B-441)(John Wiley and Sons Inc., 2006) Altıok, Duygu; Tokatlı, Figen; Harsa, Hayriye ŞebnemThe biomass growth, lactic acid production and lactose utilisation kinetics of lactic acid production from whey by Lactobacillus casei was studied. Batch fermentation experiments were performed at controlled pH and temperature with six different initial whey lactose concentrations (9-77 g dm-3) in a 3 dm3 working volume bioreactor. Biomass growth was well described by the logistic equation with a product inhibition term. In addition, biomass and product inhibition effects were defined with corresponding power terms, which enabled adjustment of the model for low- and high-substrate conditions. The Luedeking-Piret equation defined the product formation kinetics. Substrate consumption was explained by production rate and maintenance requirements. A maximum productivity of 2.5 g dm-3 h-1 was attained with an initial lactose concentration of 35.5 g dm-3.