Volume 9, Issue 1 (2018)                   JMBS 2018, 9(1): 117-122 | Back to browse issues page

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Zahedi A, Rashvand M. M. Feasibility of Optimum Temperature for Growth of Nannochloropsis Oculata Microalga by Using Image Processing System. JMBS. 2018; 9 (1) :117-122
URL: http://biot.modares.ac.ir/article-22-24308-en.html
1- Energy SystemsDepartment, New Technologies Faculty, Iran University of Science & Technology, Tehran, Iran, Iran University of Science & Technology, Daneshgah Street, Hengam Street, Resalat Square, Tehran, Iran. Postal Code: 1684613114
2- Agricultural Machinery Department, Agricultural Engineering & Technology Faculty, Tehran University, Karaj, Iran
Abstract:   (2094 Views)
Aims: Biodiesel is considered as a clean fuel, because it is free of any aromatic compound. In recent years, in order to reduce the cost of production of Biodiesel, many studies have been conducted on the extraction of biofuels from microalgae around the world. Thus, this study was conducted with the aim of investigating the feasibility of optimum temperature for growth of Nannochloropsis Oculata microalga by using image processing system.
Materials and Methods: In this experimental study, a piece of Nannochloropsis Oculata microalga containing 100,000 cells per ml was cultured in 15°C, 20°C, and 25°C. In order to evaluate the growth rate, active microalgae were sampled at 24-hour intervals, and their growth was studied, using machine vision systems. The data were analyzed, using Matlab 2012 and Weka 3 software by multivariable analysis of variance, linear regression algorithm, multilayer perceptron, Gaussian processing and simple linear regression analysis.
Findings: The maximum cell density of Nannochloropsis Oculata on the 8th day was 286.23×104±0.38×105 cells per ml in treatment at 25°C and the minimum cell density was 168.58×104±0.48×105 cells per ml in treatment at 15°C. Specific growth rate was significantly increased at temperature of 25°C compared to the treatments at 15°C and 20°C. Linear regression algorithms (r2=0.84), multilayer perceptron (r2=0.88) and Gaussian processing (r2=0.78) showed good results, but simple linear regression indicated that the algorithm was unsuccessful (r2=0.45).
Conclusion: The image processing technique provides a successful estimation of the growth process of Nannochloropsis Oculata at different temperature levels.
Full-Text [PDF 353 kb]   (794 Downloads)    
Subject: Agricultural Biotechnology
Received: 2016/06/15 | Accepted: 2017/10/13 | Published: 2018/03/20

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