A Framework for Optimizing Phytosanitary Thresholds in Seed Systems Article Swipe
Robin A. Choudhury
,
Karen A. Garrett
,
Steven J. Klosterman
,
Krishna V. Subbarao
,
N. McRoberts
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1094/phyto-04-17-0131-fi
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1094/phyto-04-17-0131-fi
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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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1094/phyto-04-17-0131-fi
- https://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-04-17-0131-FI
- OA Status
- hybrid
- Cited By
- 25
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2736441553
All OpenAlex metadata
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https://openalex.org/W2736441553Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1094/phyto-04-17-0131-fiDigital Object Identifier
- Title
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A Framework for Optimizing Phytosanitary Thresholds in Seed SystemsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
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2017-07-20Full publication date if available
- Authors
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Robin A. Choudhury, Karen A. Garrett, Steven J. Klosterman, Krishna V. Subbarao, N. McRobertsList of authors in order
- Landing page
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https://doi.org/10.1094/phyto-04-17-0131-fiPublisher landing page
- PDF URL
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https://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-04-17-0131-FIDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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-
hybridOpen access status per OpenAlex
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https://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-04-17-0131-FIDirect OA link when available
- Concepts
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Phytosanitary certification, Biology, Downy mildew, Quarantine, Oospore, Polyembryony, Biotechnology, Agronomy, Agroforestry, Horticulture, Ecology, Embryo, Cell biologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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25Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 6, 2023: 3, 2022: 4, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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52Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.testing. | 116 |
| abstract_inverted_index.Seedborne | 0 |
| abstract_inverted_index.approach. | 198 |
| abstract_inverted_index.balancing | 79 |
| abstract_inverted_index.efficacy. | 188 |
| abstract_inverted_index.framework | 72 |
| abstract_inverted_index.pathogens | 1, 18 |
| abstract_inverted_index.prospects | 194 |
| abstract_inverted_index.seedborne | 77, 130 |
| abstract_inverted_index.threshold | 145 |
| abstract_inverted_index.uncertain | 187 |
| abstract_inverted_index.voluntary | 61 |
| abstract_inverted_index.Quarantine | 10 |
| abstract_inverted_index.accumulate | 113 |
| abstract_inverted_index.associated | 52 |
| abstract_inverted_index.challenges | 192 |
| abstract_inverted_index.illustrate | 123 |
| abstract_inverted_index.mitigation | 174 |
| abstract_inverted_index.pathogens, | 78 |
| abstract_inverted_index.pathogens. | 35 |
| abstract_inverted_index.producers, | 184 |
| abstract_inverted_index.production | 5, 160 |
| abstract_inverted_index.relatively | 95 |
| abstract_inverted_index.robustness | 104 |
| abstract_inverted_index.strategies | 175 |
| abstract_inverted_index.thresholds | 39, 75 |
| abstract_inverted_index.Alternative | 173 |
| abstract_inverted_index.Peronospora | 133 |
| abstract_inverted_index.demonstrate | 118 |
| abstract_inverted_index.prohibitive | 59 |
| abstract_inverted_index.regulations | 24 |
| abstract_inverted_index.thresholds. | 65 |
| abstract_inverted_index.agricultural | 8 |
| abstract_inverted_index.implementing | 196 |
| abstract_inverted_index.introduction | 15 |
| abstract_inverted_index.distribution. | 172 |
| abstract_inverted_index.phytosanitary | 38, 64 |
| abstract_inverted_index.implementation | 62 |
| abstract_inverted_index.reintroduction | 30 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.93194323 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |