One of the main objectives of the Mauritius Sugarcane Industry Research Institute (MSIRI)
is to develop new and more productive sugarcane varieties through its breeding and
selection programme. It relies heavily on its computer systems for its operations and in
handling voluminous data generated during its breeding and selection programme. It can
take up to fifteen years for a new variety to be released from the time it is produced after
crossing two parents and its selection. Annual data related to crosses, selection trials, and
variety performance stored at MSIRI goes back to the mid-1960. As climate is a key driver
of crop production systems and has a major influence on crop productivity, climate-related
data is also stored. However, the current MSIRI computer system is obsolete and
incompatible with latest technologies and is not portable. Moreover, the risks of losing
critical data are high, especially with no failover alternative. The main purpose of this
project is to take advantage of the cloud computing cost effective solutions to safeguard
the sugarcane hybridization and selection as well as the climate database. The objective is
to build a climate and crop database in order to provide ubiquitous access to information,
user-friendly data analytics and reporting tools through the development of innovative
business intelligence (BI) dashboards on the cloud. It is proposed that information on
climate and crop status would be made available on-line to different categories of cane
growers through a web-based application for better crop monitoring. The cloud platform
would also help in promoting exchange of genetic information among sugarcane research
centres worldwide. In future, local and international institutions could make use of this
platform to store and share information against payment of an access fee to ensure and
this would allow for sustainability of the cloud system. Eventually this platform could
evolve into a fully functional agricultural knowledge-based system with the integration of
other components on cane research:
1. Build cloud environment
2. Initial data migration
3. Data cleansing, preparation and validation
4. Incremental data synchronization
5. Implementing data analytics and reporting dashboards
Keywords
Cloud,data analytics,synchronization,reporting,sugarcane breeding and selection,database,climate
Language
English
Publisher
Mauritius Research and Innovation Council
Content Classification
Brief
Funding Agency(ies)
Mauritius Research and Innovation Council; Mauritius Sugarcane Industry Research Institute,MCIA