A Decision Tree Approach to Estimate the Microalgae Production in Open Raceway Pond

3rd International Conference on Biomass: Accelerating the Technical Development and Commercialization for Sustainable Bio-based Products and Energy

生物科学;能源学;经济学

Supriyanto^1,2 ; Noguchi, Ryozo^1 ; Ahamed, Tofael^1 ; Mikihide, Demura^3 ; Watanabe, Makoto M.^3

Faculty of Life and Environmental Sciences, University of Tsukuba, Japan^1

Department of Mechanical and Biosystem Engineering, Bogor Agricultural University, Bogor, Indonesia^2

Algae Biomass and Energy System Research and Development Centre, University of Tsukuba, Japan^3

关键词: Correlation coefficient;    Decision tree modeling;    Decision-tree algorithm;    Environmental parameter;    Micro-algae;    Raceway pond;    Research and development;    University of Tsukuba;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/209/1/012050/pdf
DOI  :  10.1088/1755-1315/209/1/012050

学科分类：生物科学（综合）

来源: IOP

【 摘 要 】

Microalgae are one of the potential biomass to produce biofuel energy. The popular cultivation method of microalgae is using open raceway pond. The open raceway pond is waterway included with paddlewheel. Cultivation microalgae in open raceway pond using water, nutrient, CO2, and maintaining the pH condition. To avoid the contamination from unwanted microalgae, the Algae Biomass and Energy System Research and Development (ABES), University of Tsukuba cultivated the polyculture microalgae to minimize the contamination that make unstable ecosystem in culture. The disadvantages of microalgae culture in open raceway pond is difficult to control the environmental parameter such as temperature and solar radiation. However, the environmental parameter is important in growing microalgae and potential to use as parameter to estimate the growth of microalgae. In This research, we proposed the growth estimation model of microalgae in Open Raceway Pond using the temperature and solar radiation parameter. The growth estimation model developed to estimate the production rate (g/m2/day) using the decision tree model using previous dataset from Minamisoma microalgae pilot plant. The result of this study indicated that decision tree algorithm able to estimate the microalgae production using the temperature and solar irradiance parameter with correlation coefficient 0.89 and RMSE 0.085.