ABSTRACT
Invasive nonnative plant pests can cause extensive environmental and economic damage and are very difficult to eradicate once established. Phytosanitary inspections that aim to prevent biological invasions by limiting movement of nonnative plant pests across borders are a critical component of the biosecurity continuum. Inspections can also provide valuable information about when and where plant pests are crossing national boundaries. However, only a limited portion of the massive volume of goods imported daily can be inspected, necessitating a highly targeted, risk-based strategy. Furthermore, since inspections must prioritize detection and efficiency, their outcomes generally cannot be used to make inferences about risk for cargo pathways as a whole. Phytosanitary agencies need better tools for quantifying pests going undetected and designing risk-based inspection strategies appropriate for changing operational conditions. In this research, we present PoPS (Pest or Pathogen Spread) Border, an open-source consignment inspection simulator for measuring inspection outcomes under various cargo contamination scenarios to support recommendations for inspection protocols and estimate pest slippage rates. We used the tool to estimate contamination rates of historical interception data, quantify tradeoffs in effectiveness and workload for inspection strategies, and identify vulnerabilities in sampling protocols as changes in cargo configurations and contamination occur. These use cases demonstrate how this simulation approach permits testing inspection strategies and measuring quantities that would otherwise be impossible in a field-based setting. This work represents the first steps toward a decision support tool for creating dynamic inspection protocols that respond to changes in available resources, workload, and commerce trends.
ABSTRACT
The present study investigates U.S. Department of Agriculture inspection records in the Agricultural Quarantine Activity System database to estimate the probability of quarantine pests on propagative plant materials imported from various countries of origin and to develop a methodology ranking the risk of country-commodity combinations based on quarantine pest interceptions. Data collected from October 2014 to January 2016 were used for developing predictive models and validation study. A generalized linear model with Bayesian inference and a generalized linear mixed effects model were used to compare the interception rates of quarantine pests on different country-commodity combinations. Prediction ability of generalized linear mixed effects models was greater than that of generalized linear models. The estimated pest interception probability and confidence interval for each country-commodity combination was categorized into one of four compliance levels: "High," "Medium," "Low," and "Poor/Unacceptable," Using K-means clustering analysis. This study presents risk-based categorization for each country-commodity combination based on the probability of quarantine pest interceptions and the uncertainty in that assessment.
ABSTRACT
Chromosomal regions of sorghum, Sorghum bicolor (L.) Moench, conferring resistance to greenbug, Schizaphis graminum (Rondani), biotypes C, E, I, and K from four resistance sources were evaluated by restriction fragment-length polymorphism (RFLP) analysis. At least nine loci, dispersed on eight linkage groups, were implicated in affecting sorghum resistance to greenbug. The nine loci were named according to the genus of the host plant (Sorghum) and greenbug (Schizaphis graminum). Most resistance loci were additive or incompletely dominant. Several digenic interactions were identified, and in each case, these nonadditive interactions accounted for a greater portion of the resistance phenotype than did independently acting loci. One locus in three of the four sorghum crosses appeared responsible for a large portion of resistance to greenbug biotypes C and E. None of the loci identified were effective against all biotypes studied. Correspondingly, the RFLP results indicated resistance from disparate sorghums may be a consequence of allelic variation at particular loci. To prove this, it will be necessary to fine map and clone genes for resistance to greenbug from various sorghum sources.
