Current Status and Future Prospects of Next-Generation Data Management and Analytical Decision Support Tools for Enhancing Genetic Gains in Crops

Rathore, A and Singh, V K and Pandey, S K and Rao, C S and Thakur, V and Pandey, M K and Anil Kumar, V and Das, R R (2018) Current Status and Future Prospects of Next-Generation Data Management and Analytical Decision Support Tools for Enhancing Genetic Gains in Crops. In: Advances in Biochemical Engineering/Biotechnology. Advances in Biochemical Engineering/Biotechnology book series . Springer, Berlin, Heidelberg, pp. 1-16.

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Abstract

Agricultural disciplines are becoming data intensive and the agricultural research data generation technologies are becoming sophisticated and high throughput. On the one hand, high-throughput genotyping is generating petabytes of data; on the other hand, high-throughput phenotyping platforms are also generating data of similar magnitude. Under modern integrated crop breeding, scientists are working together by integrating genomic and phenomic data sets of huge data volumes on a routine basis. To manage such huge research data sets and use them appropriately in decision making, Data Management Analysis & Decision Support Tools (DMASTs) are a prerequisite. DMASTs are required for a range of operations including generating the correct breeding experiments, maintaining pedigrees, managing phenotypic data, storing and retrieving high-throughput genotypic data, performing analytics, including trial analysis, spatial adjustments, identifications of MTAs, predicting Genomic Breeding Values (GEBVs), and various selection indices. DMASTs are also a prerequisite for understanding trait dynamics, gene action, interactions, biology, GxE, and various other factors contributing to crop improvement programs by integrating data generated from various science streams. These tools have simplified scientists’ lives and empowered them in terms of data storage, data retrieval, data analytics, data visualization, and sharing with other researchers and collaborators. This chapter focuses on availability, uses, and gaps in present-day DMASTs.

Item Type: Book Section
Divisions: Research Program : Genetic Gains
CRP: UNSPECIFIED
Series Name: Advances in Biochemical Engineering/Biotechnology book series
Uncontrolled Keywords: Analytical Decision Support Tool, Data management, Genetic gains, Plant breeding, GEBVs Data Management Analysis & Decision Support Tools (DMASTs), Genomic Breeding Values, data storage, data retrieval, data analytics, data visualization, DMASTs
Subjects: Others > Data Management
Others > Statistical Models
Others > Agricultural Research
Others > Genetics and Genomics
Depositing User: Mr Ramesh K
Date Deposited: 18 Apr 2018 08:21
Last Modified: 04 Sep 2018 06:59
URI: http://oar.icrisat.org/id/eprint/10593
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