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Antioxidant radical scavenging capacity and total carotenoid content of narrow-clawed crayfish (Pontastacus leptodactylus, Eschscholtz, 1823) in Atikhisar Reservoir (Çanakkale, Türkiye)

Acarlı Sefa, Kızılkaya Bayram, Vural Pervin, Barber Selçuk, Kale Semih, Acarlı Deniz

Oceanological and Hydrobiological Studies

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2023

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Vol. 52, No. 4

471--483

EN

n this study, antioxidant radical scavenging capacity and total carotenoid content in the meat and shells of Pontastacus leptodactylus were investigated. Concerning the antioxidant scavenging effect, the highest IC50 values were found to be 388.77 mg g-1 and 155.53 mg g-1 for females and males in July and March, respectively. The mean IC50 values of the meat were calculated as 239.83 mg g-1 and 105.21 mg g-1 for females and males, respectively. The mean total carotenoid content in the meat was found to be 14.35 and 12.78 μg g-1 for females and males, respectively. The results indicated that crayfish meat had antioxidant radical scavenging capacity and was rich in carotenoid content.

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Trend analysis and forecasting of the Gökırmak River streamflow (Turkey)

Arslan Gökhan, Kale Semih, Yavuz Sönmez Adem

Oceanological and Hydrobiological Studies

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2020

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Vol. 49, No. 3

230--246

EN

The objective of this paper is to determine the trend and to estimate the streamflow of the Gökırmak River. The possible trend of the streamflow was forecasted using an autoregressive integrated moving average (ARIMA) model. Time series and trend analyses were performed using monthly streamflow data for the period between 1999 and 2014. Pettitt's change point analysis was employed to detect the time of change for historical streamflow time series. Kendall's tau and Spearman's rho tests were also conducted. The results of the change point analysis determined the change point as 2008. The time series analysis showed that the streamflow of the river had a decreasing trend from the past to the present. Results of the trend analysis forecasted a decreasing trend for the streamflow in the future. The decreasing trend in the streamflow may be related to climate change. This paper provides preliminary knowledge of the streamflow trend for the Gökırmak River.

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Development of an adaptive neuro-fuzzy inference system (ANFIS) model to predict sea surface temperature (SST)

Kale Semih

Oceanological and Hydrobiological Studies

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2020

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Vol. 49, No. 4

354--373

EN

An accurate estimation of the sea surface temperature (SST) is of great importance. Therefore, the objective of this work was to develop an adaptive neuro-fuzzy inference system (ANFIS) model to predict SST in the Çanakkale Strait. The observed monthly air temperature, evaporation and precipitation data from the Çanakkale meteorological observation station were used as input data. The Takagi–Sugeno fuzzy inference system was applied. The grid partition method (ANFIS-GP) and the subtractive clustering partitioning method (ANFIS-SC) were used with Gaussian membership functions to generate the fuzzy inference system. Six performance evaluation criteria were used to evaluate the developed SST prediction models, including mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE) and correlation of determination (R2). The dataset was randomly divided into training and testing datasets for the machine learning process. Training data accounted for 75% of the dataset, while 25% of the dataset was allocated for testing in ANFIS. The hybrid algorithm was selected as a training algorithm for the ANFIS. Simulation results revealed that the ANFIS-SC4 model provided a higher correlation coefficient of 0.96 between the observed and predicted SST values. The results of this study suggest that the developed ANFIS model can be applied for predicting sea surface temperature around the world.