Environmental Monitoring and Assessment, ( ISI ), Volume (192), No (4), Year (2020-3)

Title : ( Modeling oxygen and organic matter concentration in the intensive rainbow trout (Oncorhynchus mykiss) rearing system )

Authors: firouzeh hosseini , Mohammad Reza Bayati , Omid Safari , Abbas Rohani ,

Citation: BibTeX | EndNote


Dissolved oxygen (DO) as one of the most fundamental parameters of water quality plays a vital role in aquatic life. This study was conducted to predict DO, biological oxygen demand (BOD), and chemical oxygen demand (COD) in an intensive rainbow trout rearing system with different biomass (B). The multilayer perceptron (MLP) and the radial basis function (RBF) neural networks were employed for evaluating the impacts of food parameters (crude protein (CP), consumed feed (CF)), fish parameters (different values of B, and weight gain (WG)), and water quality parameters including temperature (T) and flow rate (Q) on variation of DO, BOD, and COD concentrations. This study’s results showed that although both MLP and RBF neural networks are capable to estimate DO, BOD, and COD concentrations, RBF neural network showed better performance compared to MLP neural network. The results of sensitivity analysis indicated that the parameter CF has the highest effect on DO concentration estimation. Independent variables CF, CP, WG, and B showed the highest to the lowest rank of impacts on BOD estimation, respectively. The results also illustrated a decreasing trend of the effects on the estimation error of COD changes simulation by all independent variables, including B, T, WG, CF, CP, and Q, respectively. RBF neural network based on better stability and generalization ability with average root mean square error (RMSE) and mean absolute percentage error (MAPE) values of less than 0.12 and 3% was superior to MLP in DO, BOD, and COD concentration prediction. Moreover, CF was identified as the most effective factor in estima12tion process. Based on the present study results, there are direct relationships between DO, BOD, and COD concentrations and water quality parameters, fish parameters, and food parameters. Food parameters relative to fish and water quality parameters imposed the greatest effects. Improvement in feeding process such as application of intelligence feeding methods and change in fish diet and feeding time can considerably reduce losses in production system.


, Artificial neural networks, Different biomass, Fish culture, Prediction
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

author = {Hosseini, Firouzeh and Bayati, Mohammad Reza and Safari, Omid and Rohani, Abbas},
title = {Modeling oxygen and organic matter concentration in the intensive rainbow trout (Oncorhynchus mykiss) rearing system},
journal = {Environmental Monitoring and Assessment},
year = {2020},
volume = {192},
number = {4},
month = {March},
issn = {0167-6369},
keywords = {Artificial neural networks; Different biomass; Fish culture; Prediction},


%0 Journal Article
%T Modeling oxygen and organic matter concentration in the intensive rainbow trout (Oncorhynchus mykiss) rearing system
%A Hosseini, Firouzeh
%A Bayati, Mohammad Reza
%A Safari, Omid
%A Rohani, Abbas
%J Environmental Monitoring and Assessment
%@ 0167-6369
%D 2020