Islam Mir Shariful, Kabir K M Ariful, Tanimoto Jun, Saha Bidyut Baran
Mechanical Engineering Department, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan.
International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan.
Heliyon. 2021 Oct 16;7(10):e08185. doi: 10.1016/j.heliyon.2021.e08185. eCollection 2021 Oct.
has been considered a promising source of food supplement to combat malnutrition worldwide. Numerous investigations have stated its immune activity, ability to absorb CO during the growth period, and antioxidant potential. Well-known theoretical biomass kinetic model sheds are capable of qualitative analysis of the fast microalgae growth. In this regard, we considered eight popular biomass models: Monod, Haldane, Andrews & Noack, Teissier, Hinshelwood, Yano & Koga, Webb and, Aiba model comprising analytical investigation within the numerical simulation. Besides, in this study, we establish a new mathematical biomass growth model by merging the well-known Hinshelwood and Yano & Koga models. We explored the most suitable growth model to minimize the overstated and understated growth trends in the assorted eight biomass kinetic models. Our findings show microalgae biomass growth and substrate diminishes along with time, and these results were compared with available experimental data. Results present a high value of R(0.9862), a low value of RSS (0.0813), AIC (-9.7277), and BIC (-8.2148) implied significantly fitted with the investigated data for the growth of compared with popular eight studied models.
已被视为全球对抗营养不良的一种有前景的食物补充剂来源。众多研究表明了其免疫活性、生长期间吸收一氧化碳的能力以及抗氧化潜力。著名的理论生物质动力学模型能够对微藻的快速生长进行定性分析。在这方面,我们考虑了八个流行的生物质模型:莫诺德模型、霍尔丹模型、安德鲁斯与诺阿克模型、泰西埃模型、欣谢尔伍德模型、矢野与古贺模型、韦伯模型以及相iba模型,包括在数值模拟中的分析研究。此外,在本研究中,我们通过合并著名的欣谢尔伍德模型和矢野与古贺模型建立了一个新的数学生物质生长模型。我们探索了最合适的生长模型,以最小化八种不同生物质动力学模型中高估和低估的生长趋势。我们的研究结果表明微藻生物质生长和底物随时间减少,并且将这些结果与现有的实验数据进行了比较。结果显示R值较高(0.9862),残差平方和较低(0.0813),赤池信息准则为(-9.7277),贝叶斯信息准则为(-8.2148),这意味着与八个研究的流行模型相比,该模型与所研究的微藻生长数据拟合度显著更高。