Using R: Seed health interventions and risk-based surveillance and mitigation strategies

An international workshop on using R packages for Seed Health was held on 18 March at the IITA headquarters in Ibadan, Nigeria. Prof Karen Garrett of the University of Florida, Gainesville, organized the workshop as part of the RTB Seed System Cluster CC2.1., which had in attendance 20 participants representing eight countries, and was co-anchored by PhD students Kelsey Andersen and James Fulton.

Meeting participants in a group photo

After Andersen introduced the use of R, the team demonstrated the R seed Health package, which provides scenario analysis for evaluating outcomes for integrated seed health strategies. This program was built on the analyses and code from a study, “Risk assessment framework for seed degeneration: Informing an integrated seed health strategy for vegetatively-propagated crops” (Open access link for paper at https://apsjournals.apsnet.org/doi/10.1094/PHYTO-09-16-0340-R).

The second package was for impact network analysis (INA), designed to address multiple aspects of linked socioeconomic networks (spread of ideas, money, influence, etc.) and biophysical networks (spread of new varieties, certified seed, pathogens, pests, etc.). (Open access publications at https://apsjournals.apsnet.org/doi/full/10.1094/PHYTO-03-17-0108-FI and https://apsjournals.apsnet.org/doi/10.1094/PHYTO-03-18-0072-R).

Risk-based surveillance strategies was used as an example to use INA to identify the best locations in a network for sampling to quickly detect a spreading pathogen or spreading new variety or technology. “A node is better for sampling if the pathogen is likely to be detected at that node before the pathogen has spread very far through the network,” said Prof Garrett. For example, an isolated node would be a poor sampling choice because the pathogen could spread widely before it reaches the isolated node.

The functions for this analysis can also consider information about where the pathogen is more likely to enter the network to predict disease outbreaks. For example, nodes with little information available through communication networks may be more likely to be vulnerable to being entry points for pathogens.

Lava Kumar, Head of Virology and Germplasm Health Units, thanked Prof Garrett and team for exposing workshop participants, many of whom are PhD students, to the R packages and their significance for ongoing research on emerging virus disease control, disease surveillance programs, and seed system interventions for mitigating the impact of seedborne diseases. 

The workshop was supported by the CGIAR Research Program on Roots, Tubers and Bananas (CRP-RTB).

CRP-RTBIITA News no 2481INALava Kumar

Communications • 12th April 2019

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