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Öğe A comprehensive study on the quality characteristics of sweet red pepper paste and the evaluation of near-infrared spectroscopy as a rapid alternative tool(Springer Science and Business Media Deutschland GmbH, 2023) Ayvaz, Hüseyin; Temizkan, Rıza; Menevşeoğlu, Ahmed; Doğan, Muhammed Ali; Nazlım, Burak Alptuğ; Günay, Ezgi; Pala, Ciğdem UysalRed pepper (Capsicum annuum L. cv. Capia) is an important vegetable obtained from a 1-year cultivated plant belonging to the Solanaceae family. Among the products of red pepper, its paste is very similar to tomato paste in appearance; however, it differs in terms of flavor properties. The wide-ranging quality parameters (dry matter, soluble solids, pH, titration acidity, salt, insoluble ash, total reducing sugars, color values, total carotenoid, antioxidant properties, browning index, and 5-hydroxymethylfurfural) of commercial sweet pepper pastes (n = 52) were determined. To the best of our knowledge, this study is the most comprehensive study on determining the quality parameters of red pepper paste, and its in-depth results will help food authorities issue registrations related to commercial pepper paste in countries such as Türkiye. Additionally, near-infrared (NIR) spectroscopy-based machine-learning algorithms were evaluated for the first time in paste samples as a rapid alternative or complementary to the conventional analytical methods. Regarding the conditional entropy-based models, successful predictions with high accuracy were developed for all the quality parameters of pepper paste. Except for the coefficient of determination value of 0.69 and 0.85 in the prediction of HMF and a/b color values in the developed models, respectively, 0.96 or higher coefficients of determination were obtained for all other parameters. Therefore, NIR spectroscopy, along with the conditional entropy-based predictions, enables simple, fast, multiparametric and accurate quantitative prediction of the numerous quality parameters for commercial sweet pepper pastes and has the potential to be used in routine quality control analyses by pepper paste producers.Öğe Anthocyanins from Agro-Industrial Food Waste: Geographical Approach and Methods of Recovery-A Review(MDPI, 2023) Diaconeasa, Zorita; Iuhas, Cristian I.; Ayvaz, Hüseyin; Mortaş, Mustafa; Farcas, Anca; Mihai, Mihaela; Danciu, Corina; Stanila, AndreeaDrastic growth in the amount of global food waste produced is observed every year, not only due to incessant population growth but also economic growth, lifestyle, and diet changes. As a result of their increasing health awareness, people are focusing more on healthy diets rich in fruits and vegetables. Thus, following worldwide fruit and vegetable consumption and their processing in various industries (juice, jams, wines, preserves), significant quantities of agro-industrial waste are produced (pomace, peels, seeds) that still contain high concentrations of bioactive compounds. Among bioactive compounds, anthocyanins have an important place, with their multiple beneficial effects on health; therefore, their extraction and recovery from food waste have become a topic of interest in recent years. Accordingly, this review aims to summarize the primary sources of anthocyanins from food waste and the novel eco-friendly extraction methods, such as pulsed electric field extraction, enzyme-assisted extraction, supercritical fluid extraction, pressurized liquid extraction, microwave-assisted extraction, and ultrasonic-assisted extraction. The advantages and disadvantages of these techniques will also be covered to encourage future studies and opportunities focusing on improving these extraction techniques.Öğe Anthocyanins: Metabolic Digestion, Bioavailability, Therapeutic Effects, Current Pharmaceutical/Industrial Use, and Innovation Potential(MDPI, 2023) Ayvaz, Hüseyin; Cabaroğlu, Turgut; Akyıldız, Asiye; Uysal Pala, Çiğdem; Temizkan, Rıza; Ağcam, Erdal; Ayvaz, ZaydeIn this work, various concepts and features of anthocyanins have been comprehensively reviewed, taking the benefits of the scientific publications released mainly within the last five years. Within the paper, common topics such as anthocyanin chemistry and occurrence, including the biosynthesis of anthocyanins emphasizing the anthocyanin formation pathway, anthocyanin chemistry, and factors influencing the anthocyanins’ stability, are covered in detail. By evaluating the recent in vitro and human experimental studies on the absorption and bioavailability of anthocyanins present in typical food and beverages, this review elucidates the significant variations in biokinetic parameters based on the model, anthocyanin source, and dose, allowing us to make basic assumptions about their bioavailability. Additionally, special attention is paid to other topics, such as the therapeutic effects of anthocyanins. Reviewing the recent in vitro, in vivo, and epidemiological studies on the therapeutic potential of anthocyanins against various diseases permits a demonstration of the promising efficacy of different anthocyanin sources at various levels, including the neuroprotective, cardioprotective, antidiabetic, antiobesity, and anticancer effects. Additionally, the studies on using plant-based anthocyanins as coloring food mediums are extensively investigated in this paper, revealing the successful use of anthocyanins in coloring various products, such as dietary and bakery products, mixes, juices, candies, beverages, ice cream, and jams. Lastly, the successful application of anthocyanins as prebiotic ingredients, the innovation potential of anthocyanins in industry, and sustainable sources of anthocyanins, including a quantitative research literature and database analysis, is performed.Öğe Detecting carob powder adulteration in cocoa using near and mid-infrared spectroscopy: A comprehensive classification and regression analysis(Elsevier, 2025) Turgut, Sebahattin Serhat; Ayvaz, Hüseyin; Doğan, Muhammed Ali; Marin, Dolores Perez; Menevşeoğlu, AhmedCocoa powder is a globally traded food product, primarily produced in developing nations, with substantial economic importance. However, it is susceptible to adulteration with inexpensive materials such as carob flour, particularly in low concentrations too low to be detected by sensory methods. To address this issue, rapid analytical techniques such as vibrational spectroscopy combined with multivariate analysis could be beneficial for rapid and reliable detection of adulteration. In this study, spectral data were collected using four different infrared spectrometers: a benchtop FT-NIR system, two portable NIR instruments, and a benchtop FT-MIR-ATR. Samples included pure cocoa, pure carob, and their mixtures with carob concentrations ranging from 0 % to 60 %. Both classification and regression models were developed to detect and quantify the presence of carobs in cocoa powder. Classification models, including Random Forest (RF), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), k-Nearest Neighbors (kNN), Linear Discriminant Analysis (LDA), and Soft Voting Classifiers, demonstrated superior performance for discriminating between cocoa powder, carob powder, and cocoa-carob mixtures with the area under the receiver operating characteristic curve (AUC) scores achieving the level of higher than 0.99, particularly using the benchtop FT-NIR, one of the cost-effective portable NIR and FT-MIR-ATR devices. Similarly, regression models - RF, SVM, MLP, kNN, Partial Least Squares Regression, and Voting Regressor- exhibited robust predictive capabilities. Particularly, FT-MIR and portable NIR based models showed exceptional accuracy with RPD values exceeding 16 and 13, respectively, signifying their applicability in quality and process control. Key wavelength driving model predictions were identified using permutation feature importance for both regressors and classifiers. Overall, these findings highlight and prove the potential of NIR and MIR spectroscopy as rapid, robust, and non-destructive tools for screening and quality control in food authentication.Öğe Detection of einkorn flour adulteration in flour and bread samples using Computer-Based Image Analysis and Near-Infrared Spectroscopy(Elsevier Ltd, 2021) Ayvaz, Hüseyin; Korkmaz, Fatma; Polat, Havva; Ayvaz, Zayde; Tuncel, Necati BarışEinkorn (Triticum monocum L.) is an old variety of wheat and is considered an ancient grain. Currently, limited amounts of einkorn are produced within a few regions of Europe and the US, and therefore it is sold at higher prices than common wheat. Either for unfair economic gain (adulteration) or to compensate its weaker gluten structure, einkorn flour tends to be adulterated with bread wheat flour, which is frequently encountered in commercial einkorn flour or einkorn baked products. In this study, einkorn and bread wheat flours were initially analyzed for their common quality properties following the traditional analytical methods. Then, two rapid methods, Computer-Based Image (CBI) Analysis and Near-Infrared Spectroscopy (NIRS), were evaluated to rapidly estimate the % level of bread wheat flour in both einkorn-wheat flour mixtures and the bread made of those mixtures. For this purpose, binary mixtures of einkorn flour and the adulterating bread wheat flour were prepared for calibration (46 samples) and external validation (18 samples) sets, with wheat flour content in the mixtures ranging between 5 and 95% (w/w). Then, for each binary mixture, a loaf of conventional bread was produced. Flour mixtures and loaves of bread samples produced were analyzed by both CBI and NIRS. Our results suggested that CBI could only yield high correlation levels between the wheat flour content and some color properties in bread samples (>0.96), while no sufficient correlations were observed in flour mixtures. Regarding the NIRS, highly accurate models were developed for both flour mixtures (correlation coefficients > 0.99, standard errors < 1.39% and RPD level of 19.3) and bread samples (correlation coefficients > 0.94, standard errors < 2.64% and RPD level of 10.1). Our results indicate that both NIRS and CBI may be implemented in the rapid and easy screening of wheat flour adulteration in einkorn bread, while only NIRS is suggested to be used for the same purpose in flour mixtures.Öğe Determination of the production process and some quality properties of Biga cheese dessert(Volkan OKATAN, 2020) Aslan, Aynur; Tiryaki, Gulgun; Ayvaz, Zayde; Ayvaz, HüseyinBiga cheese dessert, a traditional dessert in Biga county of Çanakkale province in Turkey, is a semi-finished product prepared by kneading daily fresh salt-free cheese produced using the milk obtained from Biga, eggs, flour, a small amount of high-quality semolina (optional), baking powder and water properly and shaping the dough and baking it in the oven until its top surface turns to golden brown. Sugar syrup is added to the dessert before serving for consumption. Up until today, there has been no study conducted on Biga cheese dessert. Accordingly, this study aimed to determine the dessert’s production process and its quality properties. In this study, non-syruped Biga cheese dessert dough formulation and production flow chart were revealed via personal communications and on-site examination of the commercial processes. Various physico-chemical analyses (color, dimensions, weight, moisture, ash, protein, total fat, acidity in extracted fat, peroxide number, water activity, pH) and sensory evaluation were also performed in 27 packages produced in different months by three different manufacturers of double-baked Biga cheese dessert. Based on the results, statistically significant differences were observed among the productions of different manufacturers for all parameters examined except for acidity (%), water activity, and sensory evaluation. Scores received in consumer testing with untrained panelists indicate that Biga cheese dessert has the potential to be consumed by a wider population, particularly in Turkey. This study may also contribute to receiving a geographical indication certificate for this dessert.Öğe Machine Learning-Assisted Near- and Mid-Infrared spectroscopy for rapid discrimination of wild and farmed Mediterranean mussels (Mytilus galloprovincialis)(Elsevier Inc., 2024) Ayvaz, Hüseyin; Temizkan, Rıza; Kaya, Burcu; Salman, Merve; Menevşeoğlu, Ahmed; Ayvaz, Zayde; Güneş, Nurhan; Doğan, Muhammed Ali; Mortaş, MustafaThe objective of this study was to investigate the ability to discriminate between wild and farmed Mediterranean mussels (Mytilus galloprovincialis) using machine learning-assisted near-infrared (NIR) and mid-infrared (MIR) spectroscopy. Mussels are of significant global importance in aquaculture due to their nutritional characteristics, encompassing a rich source of protein, essential fatty acids, various vitamins, and abundant minerals. Additionally, their ease of farming adds to their value as a desirable aquaculture species. The mussels' capacity to reflect environmental quality attributes makes them valuable as biomonitoring agents. However, differences in nutritional composition may arise between wild mussels harvested from natural marine hard-bottoms and those farmed in open artificial systems in the sea. In this study aimed at distinguishing between the two types of mussels, the classification models were created, and the most accurate results were achieved using the FT-MIR spectral data extracted from the interior part of the mussels, while the performance of FT-MIR data obtained from the mussels' shells was slightly lower, with the accuracy of 92% and R2 of 0.87. Still, the accuracies of all the classification models were over 90%. The Ensemble model, trained using FT-MIR spectra from the interior part of the mussel, achieved an accuracy of 98.4%, surpassing the performance of other variable sets. In both NIR and MIR models, spectra from the mussels' interior provide better discrimination than spectra from the outer shell.Öğe Near- and mid-infrared determination of some quality parameters of cheese manufactured from the mixture of different milk species(Springer, 2021) Ayvaz, Hüseyin; Mortas, Mustafa; Doğan, Muhammed Ali; Atan, Mustafa; Yıldız Tiryaki, Gülgün; Karagül Yüceer, YoncaThis study aimed to evaluate the performance of both near-infrared (NIR) diffuse reflectance and mid-infrared-attenuated total reflectance (MIR-ATR) in determining some quality parameters of a commercial white cheese made of unknown ratios of various milk species. For this purpose, 81 commercial Ezine cheese samples, a special ripened cheese produced in Turkey, containing unknown ratios of bovine, caprine, and ovine milk, were used. Reference analyses, including textural properties, protein content, nitrogen fractions, ripening index coefficients, fat, salt, dry matter-moisture, and ash contents as well as pH and titratable acidity levels, were conducted in the samples following the traditional gold standards. For NIR applications, the spectra of both intact cubes and hand-crushed cheese samples were collected, whereas the spectra of only hand-crushed cheese samples were collected for MIR-ATR. PLSR (Partial Least Squares Regression) calibration models were developed for each parameter (n = 61) and then validated using both cross-validation (leave-one-out approach) and an external validation set (n = 20). Overall, PLSR models developed for total protein, fat, salt, dry matter, moisture, and ash content, as well as pH and titratable acidity, yielded satisfactory performance statistics in the complementary use of NIR and MIR spectroscopy. However, PLSR models of the other parameters, including textural properties, nitrogen fractions, and the ripening index, could only separate high and low values and were not able to make accurate quantitative predictions. NIR spectroscopy was found to be more accurate than that of MIR-ATR spectroscopy for almost all the parameters except for pH and titratable acidity, for which MIR-ATR spectroscopy was superior.Öğe Quality Control of Honey Using New Generation Infrared Spectrometers(2017) Ayvaz, HüseyinThe objective of this study was to develop a rapid infrared technique to determine 10 keyquality parameters (sucrose, glucose, fructose, reducing sugar, 5-HMF, °Brix, moisturecontent, water activity, pH and free acidity) in honey by using new generation portableand handheld devices. The composition of honey samples (n=59) collected from differentparts of Turkey was analyzed by using established reference methods, giving wide rangeof concentrations for each parameter. The levels of sucrose and 5-HMF in some sampleswere above the established regulatory limits (Codex Alimentarius and European Unionstandards), indicating possible adulteration or process and storage abuse. Spectra werecollected by using portable Fourier-Transformed infrared (FTIR) and handheld NIR(Near Infrared) spectrometers. Partial least squares regression (PLSR) approach was usedto correlate the spectral features with compositional reference values, giving strong linearcorrelation coefficients and standard errors of prediction. Although both systemsperformed similarly, portable FTIR system was superior in predictions of sucrose, 5-HMF and free acidity while portable NIR system performed noticeably better for °Brixand moisture content. The data indicates that all of the 10 parameters can be measuredwithin the minutes using both systems, providing reliable screening capabilities,flexibility and the potential for in-field applications.Öğe Rapid detection of green pea adulteration in ground pistachio nuts using near and mid-infrared spectroscopy(Volkan OKATAN, 2020) Temizkan, Riza; Doğan, Muhammed Ali; Atakan, Orhan; Nazlım, Burak Alptuğ; Ayvaz, HüseyinNear-infrared (NIR) diffuse reflectance and Mid-infrared-attenuated total reflectance (MIR-ATR) spectroscopy were evaluated to determine the dried green pea seed adulteration in ground pistachio nuts. Sixty-three samples (51 for calibration and 12 for external validation sets) of ground pistachio nuts were deliberately adulterated with varying levels of dried green pea seeds (ranging from 0 to 50% (w/w)). Subsequently, both NIR and MIR-ATR spectra of the samples were collected separately. The quantitative predictions of green pea ratio in the samples were achieved using PLSR (Partial Least Squares Regression). Based on the PLSR models, SEP (Standard error of prediction) values of the models were 2.55 and 9.14% for NIR and MIR-ATR, respectively. The rPred (Correlation coefficient of prediction) values of the models were 0.99 and 0.80 for NIR and MIR-ATR, respectively. Additionally, the nondimensional values of RPD (Residual Predictive Deviation) for NIR and MIR-ATR spectra were calculated as 5.7 and 1.6, respectively. These results showed that the NIR-based models provided a distinct advantage over MIR-ATR-based models in accurately estimating the ratio of the dried green pea seeds in binary mixtures. Therefore, NIR spectroscopy has the potential and could be implemented in the routine applications of green pea detection in ground pistachio nuts.
