Literature DB >> 28726578

A Framework for Optimizing Phytosanitary Thresholds in Seed Systems.

Robin Alan Choudhury1, Karen A Garrett1, Steven J Klosterman1, Krishna V Subbarao1, Neil McRoberts1.   

Abstract

Seedborne pathogens and pests limit production in many agricultural systems. Quarantine programs help prevent the introduction of exotic pathogens into a country, but few regulations directly apply to reducing the reintroduction and spread of endemic pathogens. Use of phytosanitary thresholds helps limit the movement of pathogen inoculum through seed, but the costs associated with rejected seed lots can be prohibitive for voluntary implementation of phytosanitary thresholds. In this paper, we outline a framework to optimize thresholds for seedborne pathogens, balancing the cost of rejected seed lots and benefit of reduced inoculum levels. The method requires relatively small amounts of data, and the accuracy and robustness of the analysis improves over time as data accumulate from seed testing. We demonstrate the method first and illustrate it with a case study of seedborne oospores of Peronospora effusa, the causal agent of spinach downy mildew. A seed lot threshold of 0.23 oospores per seed could reduce the overall number of oospores entering the production system by 90% while removing 8% of seed lots destined for distribution. Alternative mitigation strategies may result in lower economic losses to seed producers, but have uncertain efficacy. We discuss future challenges and prospects for implementing this approach.

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Year:  2017        PMID: 28726578     DOI: 10.1094/PHYTO-04-17-0131-FI

Source DB:  PubMed          Journal:  Phytopathology        ISSN: 0031-949X            Impact factor:   4.025


  2 in total

1.  Modeling Epidemics in Seed Systems and Landscapes To Guide Management Strategies: The Case of Sweet Potato in Northern Uganda.

Authors:  K F Andersen; C E Buddenhagen; P Rachkara; R Gibson; S Kalule; D Phillips; K A Garrett
Journal:  Phytopathology       Date:  2019-08-13       Impact factor: 4.025

2.  Detection and Quantification of Stagonosporopsis cucurbitacearum in Seeds of Cucurbita maxima Using Droplet Digital Polymerase Chain Reaction.

Authors:  Sergio Murolo; Marwa Moumni; Valeria Mancini; Mohamed Bechir Allagui; Lucia Landi; Gianfranco Romanazzi
Journal:  Front Microbiol       Date:  2022-01-11       Impact factor: 5.640

  2 in total

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