A novel plant pathogen management tool for vector management. Issue 11 (9th June 2020)

• Record Type: Journal Article
• Authors: Stillson, Patrick T; Bloom, Elias H; Illán, Javier G; Szendrei, Zsofia
• Is Part Of: Pest management science. Volume 76:Issue 11(2020)
• Page Start: 3729
• Page End: 3737
• Publication Date: 2020-06-09
• Subjects: aster leafhopper -- aster yellows phytoplasma -- decision support systems -- insect vectors -- disease management; Pests -- Control -- Periodicals; Pesticides -- Periodicals; 632.9
• DOI: 10.1002/ps.5922
• Languages: English
• ISSNs: 1526-498X

Abstract

Abstract: BACKGROUND: Decision support systems often focus on insect control due to direct damage. However, when insects vector plant pathogens, these decision support systems must be tailored to disease management. However, a decision system that links diagnosticians to vector management is lacking and complicated by patterns of insect abundance over space and time. Here, we describe an approach that integrated monitoring of an insect pest (aster leafhopper; Macrosteles quadrilineatus, Forbes) that vectors aster yellows phytoplasma ( Candidatus Phytoplasma spp.), with rapid disease diagnostics and web‐based text messaging in two crops, carrots and celery. RESULTS: From 2014–2019, a total of 8, 343 aster leafhoppers were collected, 99 of these were infected with phytoplasma. Text messaging reduced the number of infected leafhoppers. When we compared infected leafhopper density across crops, their temporal patterns were most similar at a 2‐week delay. Comparisons within crop indicated that in celery uninfected and infected leafhopper density was most similar at a 2‐week delay, but there was no similar pattern in carrots. Leafhopper density and infectivity were not similar beyond individual farms. CONCLUSION: Our results suggest that farmers should account for these temporal and spatial patterns when managing leafhoppers infected with aster yellows phytoplasma to improve pest management. By combining extensive monitoring, with rapid disease diagnostics, and text messaging, we demonstrate the value of our decision support tool. © 2020 Society of Chemical Industry Abstract : Here we implemented a decision support tool that integrated disease diagnostics and web‐based text messaging to improve vector management by farmers at a county‐level and identify phenological patterns of vectors in agroecosystems. © 2020 Society of Chemical Industry