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Öğe Determination of Optimum Ethanolic Extraction Conditions and Phenolic Profiles of Thyme, Mint, Uckun, Grape Seeds and Green Tea Waste Fiber(2020) Bulu, Menekşe; Akpolat, Hacer; Tunçtürk, Yusuf; Alwazeer, Duried; Türkhan, AyşeThe objective of this study was to investigate the effect of different ethanol ratios inextraction solvent as well as the antioxidant properties of five plants. Thyme, mint, uckun, grapeseeds and green tea waste fiber was analyzed to determine total phenolic content (TPC) andantioxidant activity by ABTS and DPPH radical scavenging activity assays. Individual phenoliccomponents were analyzed with reverse phase high performance liquid chromatography (HPLC).TPC varied significantly from 2.00±0.27 to 172.68±0.19 mg GAE g-1 dw depending on the plant typeand ethanol ratio of the solvent. The effect of ethanol ratio also varied among different plants. HPLCanalysis was performed for the extracts showing highest antioxidant activity, and green tea wastefiber (699.89 mg 100 g-1 dw) had the highest concentration of phenolic compounds overall, whilemint (173.67 mg 100 g-1 dw) had the lowest amount. Correlations between TPC and antioxidantactivity was significant which is comparable to the previous report.Öğe High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods(Mdpi, 2020) Akpolat, Hacer; Barineau, Mark; Jackson, Keith A.; Akpolat, Mehmet Z.; Francis, David M.; Chen, Yu-Ju; Rodriguez-Saona, Luis E.Our objective was to develop a rapid technique for the non-invasive profiling and quantification of major tomato carotenoids using handheld Raman spectroscopy combined with pattern recognition techniques. A total of 106 samples with varying carotenoid profiles were provided by the Ohio State University Tomato Breeding and Genetics program and Lipman Family Farms (Naples, FL, USA). Non-destructive measurement from the surface of tomatoes was performed by a handheld Raman spectrometer equipped with a 1064 nm excitation laser, and data analysis was performed using soft independent modelling of class analogy (SIMCA)), artificial neural network (ANN), and partial least squares regression (PLSR) for classification and quantification purposes. High-performance liquid chromatography (HPLC) and UV/visible spectrophotometry were used for profiling and quantification of major carotenoids. Seven groups were identified based on their carotenoid profile, and supervised classification by SIMCA and ANN clustered samples with 93% and 100% accuracy based on a validation test data, respectively. All-trans-lycopene and beta-carotene levels were measured with a UV-visible spectrophotometer, and prediction models were developed using PLSR and ANN. Regression models developed with Raman spectra provided excellent prediction performance by ANN (r(pre)= 0.9, SEP = 1.1 mg/100 g) and PLSR (r(pre)= 0.87, SEP = 2.4 mg/100 g) for non-invasive determination of all-trans-lycopene in fruits. Although the number of samples were limited for beta-carotene quantification, PLSR modeling showed promising results (r(cv)= 0.99, SECV = 0.28 mg/100 g). Non-destructive evaluation of tomato carotenoids can be useful for tomato breeders as a simple and rapid tool for developing new varieties with novel profiles and for separating orange varieties with distinct carotenoids (high in beta-carotene and high incis-lycopene).Öğe The impact of the COVID-19 pandemic on eating and food shopping habits(2023) Akpolat, Hacer; Bayraktar, Mukaddes Kılıç; Demirer, BüşraObjective: This study aimed to investigate the effect of the COVID-19 pandemic on eating and food shopping habits among the Turkish adult population. Material and method: Demographics, eating and food shopping habits, and food label reading habits of the participants were collected via online surveys. Coronavirus anxiety was assessed using the Coronavirus Anxiety Scale. The survey was conducted from November 2021 to the end of January 2022. Student's t-test was used to determine the statistical difference between quantitative variables. Chi-Square and Marginal Homogeneity Tests, depending on the number of categories, were used to determine the difference between qualitative variables. Results and discussion: Unpackaged food consumption decreased during the pandemic. More than half of the participants started to pay more attention to food labels, spend less time for grocery shopping, and started using nutritional supplements. The changes in eating, grocery shopping, and food label reading habits among Turkish consumers during the pandemic have been demonstrated.Öğe Portable infrared sensing technology for phenotyping chemical traits in fresh market tomatoes(Elsevier, 2020) Akpolat, Hacer; Barineau, Mark; Jackson, Keith A.; Aykas, Didem P.; Rodriguez-Saona, Luis E.Our objective was to develop predictive regression algorithms based on infrared spectroscopy to screen for selected quality traits directed at optimizing the selection capabilities of fresh market tomatoes. Fresh tomato (681) samples were harvested from multiple locations (Florida, Virginia, California and South Carolina) during the 2016 and 2018 seasons at various ripening stages. Spectra were collected by transmittance and attenuated total reflectance (ATR) either from the tomato surface or juice. Reference methods included soluble solid content, titratable acidity, sugars, organic acids, and lycopene. Partial least squares regression using surface spectra showed good correlation for lycopene and ascorbic acid (r(cv) > 0.9) but modest correlation coefficients (r(cv) 0.54-0.80) for all other traits, while juice spectra gave high correlation coefficients (r(cv) > 0.94) and excellent predictive performance (RPD range 3-10) for all quality traits except ascorbic acid (r(cv) > 0.79). Multiple quality traits were simultaneously determined by using a single drop of sample providing fast (< 1 min) measurements and minimal sample preparation based on unique spectral fingerprints.
