Algal Research and Biotechnology Lab, Department of Energy and Environment (DEE), National Institute of Technology (NIT), Tiruchirappalli, Tamil Nadu, India.
Environ Technol. 2020 Apr;41(10):1284-1297. doi: 10.1080/09593330.2018.1531939. Epub 2018 Oct 15.
A major constraint in the microalgal technology is the economics involved in cultivation and harvesting. This work is focussed on the optimization of nutrients for cultivation and harvesting using 'Scenedesmus sp' Response surface methodology (RSM) using 'Face centered central composite design' (FCCD) available in Design expert 10.0.4 was used to develop the regression model for optimization of nutrients and flocculation conditions. The optimum nutrient conditions were 500 ppm of urea, 250 ppm of potassium dihydrogen phosphate and 1000 ppm of potassium hydrogen carbonate under artificial light conditions and 500 ppm of urea and 2000 ppm of potassium hydrogen carbonate under sunlight conditions. The optimum conditions were predicted using the model and compared with experimental data. The model has an value of 0.9769 and 0.9798 for artificial light and sunlight conditions, respectively. In the case of harvesting studies, 98% flocculation efficiency was obtained for a combination of pH 10.4, temperature 45°C, 200 mg/l of leaf powder of . The model has an value of 0.9989. The present studies indicated that cultivation of sp with the optimized nutrients and harvesting conditions facilitate a platform for energy efficient mass cultivation.
在微藻技术中,一个主要的限制因素是与培养和收获相关的经济成本。本研究集中于使用响应面法(RSM)优化培养和收获过程中的营养物质,使用 Design expert 10.0.4 中的“面心立方中央复合设计”(FCCD)。该方法用于开发用于优化营养物质和絮凝条件的回归模型。在人工光照条件下,最佳营养条件为 500ppm 尿素、250ppm 磷酸二氢钾和 1000ppm 碳酸氢钾,而在阳光条件下,最佳营养条件为 500ppm 尿素和 2000ppm 碳酸氢钾。使用模型预测最佳条件,并将其与实验数据进行比较。该模型在人工光照和阳光条件下的 值分别为 0.9769 和 0.9798。在收获研究中,pH 值为 10.4、温度为 45°C、. 的叶粉用量为 200mg/l 时,絮凝效率达到 98%。该模型的 值为 0.9989。本研究表明,优化营养物质和收获条件培养. 有助于为高效节能的大规模培养提供平台。