A highly efficient two-stage cultivation strategy for lutein production using heterotrophic culture of Chlorella sorokiniana MB-1-M12

2018 ◽  
Vol 253 ◽  
pp. 141-147 ◽  
Author(s):  
Chun-Yen Chen ◽  
I-Chia Lu ◽  
Dillirani Nagarajan ◽  
Chien-Hsiang Chang ◽  
I-Son Ng ◽  
...  
Keyword(s):  
Chlorella Sorokiniana ◽  
Heterotrophic Culture ◽  
Two Stage ◽  
Highly Efficient ◽  
Cultivation Strategy ◽  
Lutein Production

Pilot-scale cultivation of Chlorella sorokiniana FZU60 with a mixotrophy/photoautotrophy two-stage strategy for efficient lutein production

2020 ◽  
Vol 314 ◽  
pp. 123767
Author(s):  
Youping Xie ◽  
Jun Li ◽  
Shih-Hsin Ho ◽  
Ruijuan Ma ◽  
Xinguo Shi ◽  
...  
Keyword(s):  
Pilot Scale ◽  
Chlorella Sorokiniana ◽  
Two Stage ◽  
Lutein Production

Synergistic bioconversion of lipids and carotenoids from food waste by Dunaliella salina with fulvic acid via a two-stage cultivation strategy

2021 ◽  
Vol 234 ◽  
pp. 113908
Author(s):  
Xiang Wang ◽  
Man-Man Zhang ◽  
Si-Fen Liu ◽  
Rui-Lan Xu ◽  
Jin-Hua Mou ◽  
...  
Keyword(s):  
Fulvic Acid ◽  
Food Waste ◽  
Dunaliella Salina ◽  
Two Stage ◽  
Cultivation Strategy

scholarly journals Development of a Highly Efficient SOFC Module Using Two-stage Stacks and a Fuel Regeneration Process

Fuel Cells ◽  
2017 ◽  
Vol 17 (4) ◽  
pp. 535-540 ◽  
Author(s):  
K. Nakamura ◽  
T. Ide ◽  
S. Taku ◽  
T. Nakajima ◽  
M. Shirai ◽  
...  
Keyword(s):  
Regeneration Process ◽  
Two Stage ◽  
Highly Efficient

The Two-Stage Recognition Method Based on Texture Signals of the Heterogeneous Unsteady Iris

2021 ◽  
Author(s):  
Shuai Liu ◽  
Yuanning Liu ◽  
Xiaodong Zhu ◽  
Jing Liu ◽  
Guang Huo ◽  
...  
Keyword(s):  
Iris Recognition ◽  
Recognition Accuracy ◽  
Texture Features ◽  
Unsteady State ◽  
Recognition Method ◽  
Two Stage ◽  
Second Stage ◽  
Highly Efficient ◽  
Training Samples ◽  
Gray Values

In this paper, a two-stage multi-category recognition structure based on texture features is proposed. This method can solve the problem of the decline in recognition accuracy in the scene of lightweight training samples. Besides, the problem of recognition effect different in the same recognition structure caused by the unsteady iris can also be solved. In this paper’s structure, digitized values of the edge shape in the iris texture of the image are set as the texture trend feature, while the differences between the gray values of the image obtained by convolution are set as the grayscale difference feature. Furthermore, the texture trend feature is used in the first-stage recognition. The template category that does not match the tested iris is the elimination category, and the remaining categories are uncertain categories. Whereas, in the second-stage recognition, uncertain categories are adopted to determine the iris recognition conclusion through the grayscale difference feature. Then, the experiment results using the JLU iris library show that the method in this paper can be highly efficient in multi-category heterogeneous iris recognition under lightweight training samples and unsteady state.

Central composite design for simultaneously optimizing biomass and lutein production by a mixotrophic Chlorella sorokiniana TH01

2021 ◽  
pp. 108231
Author(s):  
Cam Van T. Do ◽  
Nham Tuat T. Nguyen ◽  
Mai Huong T. Pham ◽  
Thanh Yen T. Pham ◽  
Van Gioi Ngo ◽  
...  
Keyword(s):  
Central Composite Design ◽  
Chlorella Sorokiniana ◽  
Central Composite ◽  
Lutein Production

Highly efficient production of FAMEs and β-farnesene from a two-stage biotransformation of waste cooking oils

2019 ◽  
Vol 199 ◽  
pp. 112001 ◽  
Author(s):  
Jiajia Lv ◽  
Yuefei Wang ◽  
Chengyu Zhang ◽  
Shengping You ◽  
Wei Qi ◽  
...  
Keyword(s):  
Efficient Production ◽  
Two Stage ◽  
Highly Efficient ◽  
Waste Cooking Oils ◽  
Cooking Oils
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