Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleYalnız künye2023Scopus SJRQ2Phenolic Components, Mineral Composition, Physicochemical, and Bioactive Properties of Opuntia ficus-indica with Different Drying Methods
Capar, Tugba Dursun; Dedebas, Tugba; Kavuncuoglu, Hatice; Karatas, Seyda Merve; Ekici, Lutfiye; Yalcin, Hasan
Cactus pear fruit (Opuntia ficus-indica) have nutritional and antioxidant properties due to the presence of vitamins, fibers, minerals, and polyphenols. The present paper aims to examine the effects of drying methods (sun, oven, vacuum, and freeze) on the bioactivity and antimicrobial quality of prickly pear fruit. Total phenolic content (TPC), antioxidant (DPPH) and antimicrobial activity, mineral content, phenolic compounds, and color values were investigated. The highest antioxidant activity (DPPH) and color values were observed in the freeze-dried samples, which were very close to the values for fresh samples. The total phenolic content (TPC) of the freeze-dried sample was 503.53 mg GAE/100 g. The most abundant phenolic compound was p-hydroxybenzoic acid (210 ppm) identified in fresh and freeze-dried fruit extract, which may be more effective antimicrobials than the rest. The mineral content of freeze- and vacuum-dried samples was very close to that of fresh fruit. This study indicates that freeze-drying of prickly pear fruit improved the bioactive and antimicrobial properties without leading to nutritional loss.
AtıfScopus5WoS4OpenAlex3İncele - MakaleYalnız künye2018Scopus SJRQ3Prediction of the antimicrobial activity of walnut (Juglans regia L.) kernel aqueous extracts using artificial neural network and multiple linear regression
Kavuncuoglu, Hatice; Kavuncuoglu, Erhan; Karatas, Seyda Merve; Benli, Büsra; Sagdic, Osman; Yalcin, Hasan
The mathematical model was established to determine the diameter of inhibition zone of the walnut extract on the twelve bacterial species. Type of extraction, concentration, and pathogens were taken as input variables. Two models were used with the aim of designing this system. One of them was developed with artificial neural networks (ANN), and the other was formed with multiple linear regression (MLR). Four common training algorithms were used. Levenberg–Marquardt (LM), Bayesian regulation (BR), scaled conjugate gradient (SCG) and resilient back propagation (RP) were investigated, and the algorithms were compared. Root mean squared error and correlation coefficient were evaluated as performance criteria. When these criteria were analyzed, ANN showed high prediction performance, while MLR showed low prediction performance. As a result, it is seen that when the different input values are provided to the system developed with ANN, the most accurate inhibition zone (IZ) estimates were obtained. The results of this study could offer new perspectives, particularly in the field of microbiology, because these could be applied to other type of extraction, concentrations, and pathogens, without resorting to experiments.
AtıfScopus39WoS33OpenAlex46İncele