This paper is published in Volume-7, Issue-3, 2021
Area
Computer Science
Author
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe
Org/Univ
University of Nigeria, Nsukka, Nigeria, Nigeria
Keywords
Plant Tissue Culture; simulation; E-Infrastructure, Prediction, Auxins, Science Gateway
Citations
IEEE
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe. Deploying Plant Tissue Culture Simulation use case for E-Infrastructures, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe (2021). Deploying Plant Tissue Culture Simulation use case for E-Infrastructures. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe. "Deploying Plant Tissue Culture Simulation use case for E-Infrastructures." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe. Deploying Plant Tissue Culture Simulation use case for E-Infrastructures, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe (2021). Deploying Plant Tissue Culture Simulation use case for E-Infrastructures. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe. "Deploying Plant Tissue Culture Simulation use case for E-Infrastructures." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Abstract
E-Infrastructures can be defined as networked tools, data, and resources that support a community of practice (CoP), broadly including all those who participate in and benefit from research. During the UNESCO-HP BGI project (2009-2012), the University of Nigeria team conducted experiments on plant tissue culture under the theme, “sustaining the plant tissue culture component of grid computing”. Plant Tissue culture is a method for plant propagation under in vitro conditions. Different types and parts of plants (known as explants) may be cultivated in vitro. Because plant tissue culture is still in its empirical stage, it is time-consuming, cost-intensive, and manpower demanding. These necessitated the design and development of a plant tissue culture simulation application that predicts explant yields using multiple regression models. The initial version that was developed during the BGI project with a prediction accuracy of about 67%, unfortunately, was not deployable on an e-infrastructure like the grid or the cloud. Hence, during the Sci-GaIA project (2014-2017), a use case for the development of a newer version, Plantisc2, that is deployable on e-infrastructure was proposed. The outcome of which is reported in this paper.