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Öğe Biological and Nutritional Applications of Microalgae(Mdpi, 2025) Saritas, Sumeyye; Kalkan, Arda Erkan; Yilmaz, Kadir; Gurdal, Savas; Goksan, Tolga; Witkowska, Anna Maria; Lombardo, MauroMicroalgae are photosynthetic microorganisms that have a rapid growth cycle and carbon fixation ability. They have diverse cellular structures, ranging from prokaryotic cyanobacteria to more complex eukaryotic forms, which enable them to thrive in a variety of environments and support biomass production. They utilize both photosynthesis and heterotrophic pathways, indicating their ecological importance and potential for biotechnological applications. Reproducing primarily through asexual means, microalgae have complex cell cycles that are crucial for their growth and ability to adapt to changing conditions. Additionally, microalgae possess bioactive compounds that make them both nutritious and functional. Thanks to their content of proteins, lipids, carbohydrates, vitamins, and minerals, they play an important role in the development of functional food products, particularly by enhancing nutritional content and product quality. Furthermore, studies have demonstrated that algae and algal bioactive compounds support cardiovascular health, immune function, and gut health, especially in relation to obesity and other metabolic diseases. They also contribute to skin health and cognitive functions, including memory. This review article explores the biological, nutritional, and functional properties of microalgae based on the studies conducted.Öğe Optimization of bioethanol production from sugar beet processing by-product molasses using response surface methodology(Springer Heidelberg, 2024) Altinisik, Sinem; Nigiz, Filiz Ugur; Gurdal, Savas; Yilmaz, Kadir; Tuncel, Necati Baris; Koyuncu, SermetBioethanol production from renewable biomass sources has garnered significant interest due to its potential as a sustainable alternative to fossil fuels. In this study, we investigated the optimization of bioethanol production from molasses, a by-product of the sugar production process using Saccharomyces cerevisiae through Response Surface Methodology (RSM). Initially, the fermentation process was optimized using RSM, considering four independent variables: substrate concentration, pH, temperature, and fermentation time. Subsequently, the effects of these variables on bioethanol yield were evaluated, and a quadratic model was developed to predict the optimum conditions. Analysis of variance (ANOVA) indicated a high coefficient of determination (R2) for the model, suggesting its adequacy for prediction. The optimized conditions for bioethanol production were determined as follows: substrate concentration of 200 g L-1, pH of 5.0, temperature of 30 degrees C and fermentation time of 72 h. Under these conditions, the predicted bioethanol yield was 84%. Overall, this study demonstrates the successful application of RSM for optimizing bioethanol production from molasses using S. cerevisiae, highlighting its potential as a promising feedstock for biofuel production.