Spatiotemporal variation in airborne sporangia of Phytophthora infestans: characterization and initiatives towards improving potato late blight risk estimation |
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| Authors: | M L Fall H Van der Heyden L Brodeur Y Leclerc G Moreau O Carisse |
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| Institution: | 1. Biology Department, University of Sherbrooke, Sherbrooke, QC, Canada;2. Compagnie de recherche Phytodata Inc., Sherrington, QC, Canada;3. McCain Foods Ltd., Florenceville, NB, Canada;4. Horticulture Research and Development Centre, Agriculture and Agri‐Food Canada, Saint‐Jean‐sur‐Richelieu, QC, Canada |
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| Abstract: | This study investigated the value of using real‐time monitoring of Phytophthora infestans airborne inoculum as a complement to decision support systems (DSS). The experiment was conducted during the 2010, 2011 and 2012 potato production seasons in two locations in New Brunswick, Canada. Airborne sporangia concentrations (ASC) of P. infestans were monitored using 16 rotating‐arm spore samplers placed 3 m above the ground. The first cases of late blight (2010 and 2011) were detected 6–7 days after the first ASC peak, and all samplers captured their first sporangia within the same week (at 3‐ and 9‐day periods). The cumulative ASC curve and the risk curves from two DSS (PLANT‐Plus and Pameseb Late Blight) had the same shape but different magnitudes. In both locations, the negative binomial distribution fitted the data better than the Poisson distribution, which is indicative of heterogeneity, and based on Taylor's power law, the heterogeneity increased with increasing ASC. Therefore, the present results suggest that spore‐sampling network devices may be a suitable approach for early detection of incoming inoculum and, when combined with DSS, represent a potential aid for targeting the optimal time to apply a disease‐control product. In this context, cumulative ASC can be a counterweight to the DSS risk estimate: a high risk combined with significant ASC will trigger fungicide spraying. Moreover, spore sampling can be used to assess the efficiency of management strategies by means of examining the area under the inoculum progress curve. |
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| Keywords: | airborne sporangia area under the inoculum progress curve decision support system spatial variation spore‐sampling network |
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