Artigo Acesso aberto

General guidelines for statistically sound and risk‐based surveys of plant pests

2020; European Food Safety Authority; Volume: 17; Issue: 9 Linguagem: Inglês

10.2903/sp.efsa.2020.en-1919

ISSN

2397-8325

Autores

Elena Lázaro, Stephen Parnell, Antonio Vicent Civera, J. Schans, Martijn Schenk, José Cortiñas Abrahantes, Gabriele Zancanaro, Sybren Vos,

Tópico(s)

Plant Pathogens and Resistance

Resumo

EFSA Supporting PublicationsVolume 17, Issue 9 1919E Technical reportOpen Access General guidelines for statistically sound and risk-based surveys of plant pests European Food Safety Authority (EFSA), Corresponding Author European Food Safety Authority (EFSA) ALPHA@efsa.europa.eu Correspondence: ALPHA@efsa.europa.euSearch for more papers by this authorElena Lázaro, Elena LázaroSearch for more papers by this authorStephen Parnell, Stephen ParnellSearch for more papers by this authorAntonio Vicent Civera, Antonio Vicent CiveraSearch for more papers by this authorJan Schans, Jan SchansSearch for more papers by this authorMartijn Schenk, Martijn SchenkSearch for more papers by this authorJose Cortiñas Abrahantes, Jose Cortiñas AbrahantesSearch for more papers by this authorGabriele Zancanaro, Gabriele ZancanaroSearch for more papers by this authorSybren Vos, Sybren VosSearch for more papers by this author European Food Safety Authority (EFSA), Corresponding Author European Food Safety Authority (EFSA) ALPHA@efsa.europa.eu Correspondence: ALPHA@efsa.europa.euSearch for more papers by this authorElena Lázaro, Elena LázaroSearch for more papers by this authorStephen Parnell, Stephen ParnellSearch for more papers by this authorAntonio Vicent Civera, Antonio Vicent CiveraSearch for more papers by this authorJan Schans, Jan SchansSearch for more papers by this authorMartijn Schenk, Martijn SchenkSearch for more papers by this authorJose Cortiñas Abrahantes, Jose Cortiñas AbrahantesSearch for more papers by this authorGabriele Zancanaro, Gabriele ZancanaroSearch for more papers by this authorSybren Vos, Sybren VosSearch for more papers by this author First published: 08 September 2020 https://doi.org/10.2903/sp.efsa.2020.EN-1919Citations: 2 Requestor:Directorate-General for Health and Food Safety,European Commission Question number:EFSA-Q-2019-00286 AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract At the request of the European Commission, EFSA prepared the general guidelines for surveys of plant pests, describing the legal, international and scientific context in which the surveys are designed, the basic principles implemented for surveillance of quarantine pests and introducing the concepts needed for the design of statistically sound and risk-based surveys. Three types of specific surveys are addressed: detection surveys for substantiation of pest freedom, delimiting surveys for determining the boundaries of an infested zone, and monitoring surveys for prevalence estimation when measuring the progress of eradication measures or for confirming a low pest prevalence area. For each survey, the survey parameters are introduced and their interactions analysed showing the importance of the assumptions that are taken for each one of them: (i) the aims of the survey are defined as the confidence of detectinga given pest prevalence(design prevalence), this reflects the trade-off between the acceptable level of the risk and availability of resources that determine the strength of the evidence to support the conclusion of the survey;(ii) the target populationis addressed in terms of its structure and size,including the risk factors;and (iii) the method sensitivityis defined as the combination of the sampling effectiveness and the diagnostic sensitivity. EFSA's RiBESS+ tool is introduced for calculating the sample size using the survey parameters as input values for a statistically sound and risk-based survey design. The mathematical principles behind the tool are in line with the International Standards for Phytosanitary Measures. The survey design is flexible and can be tailored to each pest and specific situation in the Member States. Once the survey is implemented following this approach, the conclusions allow surveys to be compared across time and space, contributing to the harmonisation of surveillance activities across the EU Member States. References Binns M, Nyrop J and van der Werf W, 2000. Sampling and Monitoring in Crop Protection: The Theoretical Basis for Designing Practical Decision Guides.CABI publishing. 304 pp.. Bosso L, Luchi N, Maresi G, Cristinzio G, Smeraldo S and Russo D, 2017. Predicting current and future disease outbreaks of Diplodia sapinea shoot blight in Italy: species distribution models as a tool for forest management planning. Forest Ecology and Management, 400, 655– 664. Bourhis Y, Gottwald TR, Lopez-Ruiz FJ, Patarapuwadol S and van den Bosch F, 2019. Sampling for disease absence—deriving informed monitoring from epidemic traits. Journal of Theoretical Biology, 461, 8– 16. Bouwmeester H, Heuvelink GBM, Legg JP and Stoorvogel JJ, 2012. Comparison of disease patterns assessed by three independent surveys of cassava mosaic virus disease in Rwanda and Burundi. Plant Pathology, 61, 399– 412. Cannon R, 2002. Demonstrating disease freedom – combining confidence levels. Preventive veterinary medicine, 52, 227– 249. doi: 10.1016/s0167-5877(01)00262-8. Charest J, Dewdney M, Paulitz T, Philion V and Carisse O, 2002. Spatial distribution of Venturiainaequalis airborne ascospores in orchards. Phytopathology, 92, 769– 79. EFSA (European Food Safety Authority), online. Toolkit for plant pest surveillance in the EU. Available online: https://efsa.onlinelibrary.wiley.com/doi/toc/10.1002/(ISSN)1831-4732.toolkit-plant-pest-surveillance EFSA (European Food Safety Authority), 2012. A framework to substantiate absence of disease: the risk-based estimate of system sensitivity tool (RiBESS) using data collated according to the EFSA Standard Sample Description. Supporting Publications 2012: EN-366, 44pp. doi: 10.2903/sp.efsa.2012.en-366 EFSA (European Food Safety Authority), Ciubotaru RM, Cortiñas Abrahantes J, Oyedele J, Parnell S, Schrader G, Zancanaro G and Vos S, 2018. Technical report of the methodology and work-plan for developing plant pest survey guidelines. EFSA supporting publication 2018: EN-1399. 36pp. doi: 10.2903/sp.efsa.2018.en-1399 EFSA (European Food Safety Authority), Lázaro E, Parnell S, Vicent Civera A, Schans J, Schenk M, Schrader G, Cortiñas Abrahantes J, Zancanaro G and Vos S, 2020a. Guidelines for statistically sound and risk-based surveys of Xylella fastidiosa. EFSA Supporting publications, 17 (6), 1873. doi.org/10.2903/sp.efsa.2020.EN-1873 EFSA (European Food Safety Authority), Lázaro E, Parnell S, Vicent Civera A, Schans J, Schenk M, Schrader G, Cortiñas Abrahantes J, Zancanaro G and Vos S, 2020b. Guidelines for statistically sound and risk-based surveys of Phyllosticta citricarpa. EFSA supporting publications, 17 (7), 1893. doi: 10.2903/sp.efsa.2020.en-1893 EFSA (European Food Safety Authority), Parnell S, Schenk M, Schrader G, Vicent A, Delbianco A and Vos S, 2020c. Pest survey card on Phyllosticta citricarpa. EFSA supporting publication 2020:EN-1863. 35pp. doi: 10.2903/sp.efsa.2020.en-1863 EFSA (European Food Safety Authority), Schenk M, Dijkstra E, Delbianco A and Vos S, 2020d. Pest survey card on Rhagoletis pomonella. EFSA supporting publication 2020:EN-1908. 26pp. doi: 10.2903/sp.efsa.2020.en-1908 EFSA (European Food Safety Authority), Lázaro E, Parnell S, Schans J, Schenk M, Vincent Civera A, Cortiñas Abrahantes J, Zancanaro G and Vos S, in preparation. Guidelines for statistically sound and risk-based surveys of Agrilus planipennis. EFSA PLH Panel (EFSA Panel on Plant Health), 2017a. Scientific Opinion on the pest risk assessment of Eotetranychus lewisifor the EU territory. EFSA Journal 2017; 15(10):4878, 122pp.doi: 10.2903/j.efsa.2017.4878 EFSA PLH Panel (EFSA Panel on Plant Health), 2017b. Scientific Opinion on the pest risk assessment of Diaporthe vaccinii for the EU territory. EFSA Journal 2017; 15(9):4924, 185pp. doi:org/10.2903/j.efsa.2017.4924 EFSA PLH Panel (EFSA Panel on Plant Health), 2019. Update of the Scientific Opinion on the risks to plant health posed by Xylella fastidiosa in the EU territory. EFSA Journal 2019; 17(5):5665, 200pp. doi: 10.2903/j.efsa.2019.5665 Eurostat, 2008. Survey sampling reference guidelines. Introduction to sample design and estimation techniques. 2008 edition. Eurostat, Methodologies and Working papers. Available online:https://ec.europa.eu/eurostat/ramon/statmanuals/files/KS-RA-08-003-EN.pdf Eurostat, 2018. Regions in the European Union Nomenclature of territorial units for statistics - NUTS 2016/EU-28 edition 2018. Available online:https://ec.europa.eu/eurostat/documents/3859598/9397402/KS-GQ-18-007-EN-N.pdf/68c4a909-30b0-4a90-8851-eddc400a5faf FAO (Food and Agriculture Organization of the United Nations), 1998. ISPM (International Standards for Phytosanitary Measures) 9. Guidelines for pest eradication programmes. IPPC, FAO, Rome, 14pp. Available online: https://www.ippc.int/en/publications/611/ FAO (Food and Agriculture Organization of the United Nations), 2005. ISPM (International Standards for Phytosanitary Measures) 22. Requirements for the establishment of areas of low pest prevalence. IPPC, FAO, Rome, 12pp. Available online:https://www.ippc.int/en/publications/599/ FAO (Food and Agriculture Organization of the United Nations), 2014. Risk-based disease surveillance - A manual for veterinarians on the design and analysis for demonstration of freedom from disease. FAO Animal Production and Health Manual No. 17. Rome, Italy. FAO (Food and Agriculture Organization of the United Nations), 2016. Plant Pest Surveillance: A guide to understand the principal requirements of surveillance programmes for national plant protection organizations. Version 1.1. FAO, Rome. FAO (Food and Agriculture Organization of the United Nations), 2017a. ISPM (International Standards for Phytosanitary Measures) 8. Determination of pest status in an area. FAO, Rome, 16pp. Available online:https://www.ippc.int/en/publications/612/ FAO (Food and Agriculture Organization of the United Nations), 2017b. ISPM (International Standards for Phytosanitary Measures) 4. Requirements for the establishment of pest free areas. IPPC, FAO, Rome, 12pp. Available online:https://www.ippc.int/en/publications/614/ FAO (Food and Agriculture Organization of the United Nations), 2018. ISPM (International Standard for Phytosanitary Measures) 6. Surveillance. FAO, Rome. Available online: https://www.ippc.int/static/media/files/publication/en/2019/02/ISPM_06_2018_En_Surveillance_2018-05-20_PostCPM13.pdf FAO (Food and Agriculture Organization of the United Nations), 2019. Glossary of phytosanitary terms. International Standard for Phytosanitary Measures No. 5. Rome. Published by FAO on behalf of the Secretariat of the International Plant Protection Convention (IPPC). 35 pp. Franke J, Gebhardt S, Menz G and Helfrich HP, 2009. Geostatistical Analysis of the Spatiotemporal Dynamics of Powdery Mildew and Leaf Rust in Wheat. Phytopathology, 99, 974– 84. Hester S, Sergeant E and Robinson AP and Schultz G, 2015. Animal, vegetable, or…? A case study in using animal-health monitoring design tools to solve a plant-health surveillance problem. Biosecurity Surveillance: Quantitative Approaches. F. Jarrad, S. Low-Choy and K. Mengersen. 6: 313. Hornero A, Hernandez-Clemente R, North PRJ, Beck PSA, Boscia D, Navas-Cortes JA and Zarco-Tejada PJ, 2020. Monitoring the incidence of Xylella fastidiosa infection in olive orchards using ground-based evaluations, airborne imaging spectroscopy and Sentinel-2 time series through 3-D radiative transfer modelling. Remote Sensing of Environment, 236, 111480. Hyatt-Twynam SR, Parnell S, Stutt ROJH, Gottwald TR, Gilligan CA and Cunniffe NJ, 2017. Risk-based management of invading plant disease. New Phytologist, 214(3), 1317– 1329. doi: 10.1111/nph.14488. Janse JD, Bergsma-Vlami M, Av Beuningen, Derks H, Hendriks H, Horn N, Janssen F, Kavelaars J, Roenhorst A, Schoeman M, Steeghs M, Tjou-Tam-Sin NNS, Verdel M and Wenneker M, 2009. Brown rot in potato. Gewasbescherming, 40, 176– 187. IPPC (International Plant protection Convention), 1999. The New Revised Text of the International Plant Protection Convention. FAO, Rome. Available online: https://www.ippc.int/en/publications/131/ Madden LV, Hughes G and van den Bosch F, 2007. The Study of Plant Disease Epidemics. APS Publications, 421 pp. doi: 10.1094/9780890545058. Mastin AJ, van den Bosch F, Gottwald TR, Alonso-Chavez V and Parnell SR, 2017. A method of determining where to target surveillance efforts in heterogeneous epidemiological systems. PLoS Computational Biology, 13, 1– 23. doi: 10.1371/journal.pcbi.1005712. Mastin AJ, van den Bosch F, van den Berg F and Parnell S, 2019. Quantifying the hidden costs of imperfect detection for early detection surveillance. Philosophical Transactions of the Royal Society B, 374, 2018261. doi: 10.1098/rstb.2018.0261. Milanzi E, Njeru Njagi E and Bruckers L and Molenberghs G, 2015. Data Representativeness: Issues and Solutions. EFSA supporting publication 2015:EN-759, 159 pp. Narouei-Khandan HA, Halbert SE, Worner SP and van Bruggen AHC, 2016. Global climate suitability of citrus huanglongbing and its vector, the Asian citrus psyllid, using two correlative species distribution modeling approaches, with emphasis on the USA. European Journal of Plant Pathology, 144, 655– 670. doi: 10.1007/s10658-015-0804-7. Nutter F Jr, Teng P and Shokes FM, 1991. Disease assessment terms and concepts. Plant disease, 75, 1187– 1188. NutterJr F, Esker PD and Coelho Netto RA, 2006. Disease Assessment Concepts and the Advancements Made in Improving the Accuracy and Precision of Plant Disease Data. European Journal of Plant Pathology, 115, 95– 103. Parnell S, van den Bosch F, Gottwald T and Gilligan CA, 2017. Surveillance to inform control of emerging plant diseases. Annual Review Phytopathology, 55, 591– 610. doi: 10.1146/annurev-phyto-080516-035334. Stonard JF, Marchant BP, Latunde-Dada AO, Liu Z, Evans N, Gladders P, Eckert MR and Fitt BDL, 2010. Geostatistical analysis of the distribution of Leptosphaeria species causing phoma stem canker on winter oilseed rape (Brassica napus) in England. Plant Pathology, 59, 200– 10. Tubajika KM, Civerolo EL, Ciomperlik MA, Luvisi DA and Hashim JM, 2004. Analysis of the spatial patterns of Pierce's disease incidence in the lower San Joaquin Valley in California. Phytopathology, 94, 1136– 44. Citing Literature Volume17, Issue9September 20201919E This article also appears in:Toolkit for plant pest surveillance in the EU ReferencesRelatedInformation

Referência(s)
Altmetric
PlumX