Spatio-temporal patterns of pre-harvest brown rot epidemics within individual peach tree canopies
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Spatio-temporal patterns of pre-harvest brown rot epidemics within individual peach tree canopies S. E. Everhart & A. Askew & L. Seymour & H. Scherm
Accepted: 8 October 2012 / Published online: 24 October 2012 # KNPV 2012
Abstract Tree canopies are architecturally complex and pose several challenges for measuring and characterizing spatial patterns of disease. Recently developed methods for fine-scale canopy mapping and three-dimensional spatial pattern analysis were applied in a 3-year study to characterize spatio-temporal development of pre-harvest brown rot of peach, caused by Monilinia fructicola, in 13 trees of different maturity classes. We observed a negative correlation between an index of disease aggregation and disease incidence in the same tree (r0−0.653, P10 blossom blight symptoms per tree showed a significant positive spatial association of pre-harvest fruit rot to blossom blight within the same canopy. Spatial association analyses further revealed one of S. E. Everhart : H. Scherm (*) Department of Plant Pathology, University of Georgia, Athens, GA 30602, USA e-mail: [email protected] A. Askew : L. Seymour Department of Statistics, University of Georgia, Athens, GA 30602, USA
two outcomes for the association of new fruit rot symptoms with previous fruit rot symptoms in the same tree, whereby the relationship was either not significant or exhibited a significant negative association. In the latter scenario, the newly diseased fruit were farther apart from previously symptomatic fruit than expected by random chance. This unexpected result could have been due to uneven fruit ripening in different sectors of the canopy, which could have affected the timing of symptom development and thus led to negative spatial associations among symptoms developing over time in a tree. Keywords Canopy . Monilinia fructicola . Peach . Prunus persica . Spatial analysis . Spatial pattern
Introduction Analysis of spatial patterns of plant disease as a means of quantifying spatial structure and inferring processes has come of age during the past two decades (Jeger 1999; Madden et al. 2007; Waggoner and Aylor 2000). In recent years, emphasis has begun to broaden from the traditional focus of characterizing disease patterns at the field scale toward analyzing spatial patterns at larger (landscape) or smaller (within-plant) scales, or across hierarchies from plants to landscapes (Moslonka-Lefebvre et al. 2010; Plantegenest et al. 2007; Vereijssen et al. 2007). Nevertheless, there is a paucity of research addressing plant disease aggregation and association patterns in individual
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plant canopies, especially in trees which possess complex canopies. Such within-canopy patterns may arise due to the non-random arrangement of susceptible plant parts (such as fruit, blossoms, or leaves) in the tree canopy, and/or the proximity of within-tree inoculum sources (such as cankers). Disease patterns in tree canopies may also be influenced by abiotic factors such as within-tree variability in microclimate (e.g., wetness duration) or fun
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