Spatiotemporal Relationships Between Disease Development and Airborne Inoculum in Unmanaged and Managed Botrytis Leaf Blight Epidemics

Abstract

Comparatively little quantitative information is available on both the spatial and temporal relationships that develop between airborne inoculum and disease intensity during the course of aerially spread epidemics. Botrytis leaf blight and Botrytis squamosa airborne inoculum were analyzed over space and time during 2 years (2002 and 2004) in a nonprotected experimental field, using a 6 x 8 lattice of quadrats of 10 x 10 m each. A similar experiment was conducted in 2004 and 2006 in a commercial field managed for Botrytis leaf blight using a 5 x 5 lattice of quadrats of 25 x 25 m each. Each quadrat was monitored weekly for lesion density (LD) and aerial conidium concentration (ACC). The adjustment of the Taylor's power law showed that heterogeneity in both LD and ACC generally increased with increasing mean. Unmanaged epidemics were characterized in either year, with aggregation indices derived from SADIE (Spatial Analysis by Distance Indices). For LD, the aggregation indices suggested a random pattern of disease early in the season, followed by an aggregated pattern in the second part of the epidemic. The index of aggregation for ACC in 2002 was significantly greater than 1 at only one date, while it was significantly greater than 1 at most sampling dates in 2004. In both years and for both variables, positive trends in partial autocorrelation were observed mainly for a spatial lag of 1. In 2002, the overall pattern of partial autocorrelations over sampling dates was similar for LD and ACC with no significant partial autocorrelation during the first part of the epidemic, followed by a period with significant positive autocorrelation, and again no autocorrelation on the last three sampling dates. In 2004, there was no significant positive autocorrelation for LD at most sampling dates while for ACC, there was a fluctuation between significant and non-significant positive correlation over sampling dates. There was a significant spatial correlation between ACC at given date (t(i)) and LD 1 week later (t(i + 1)) on most sampling dates in both 2002 and 2004 for the unmanaged and managed sites. It was concluded that LD and ACC were not aggregated in the early stage of epidemics, when both disease intensity and airborne conidia concentration were low. This was supported by the analysis of LD and ACC from a commercial field, where managed levels of disease were low, and where no aggregation of both variables was detected. It was further concluded that a reliable monitoring of airborne inoculum for management of Botrytis leaf blight is achievable in managed fields using few spore samplers per field.

Spatial and Temporal Dynamics of Botrytis Blight of Gladiolus (Gladiolus grandiflorus L.) Caused by Botrytis gladiolorum in Susceptible and Resistant Varieties

“…This was supported by the findings of Johnson and Powelson [9] who analyzed spore dispersal in grey mold of snap beans and found that disease incidence was 70% at a distance of 0.9 m from the inoculum source but it was less than 25% at a distance of 4 m. Further, it was observed that there was increase of disease intensity as well as spread of the infection with the increase in time intervals. The airborne inoculum of Botrytis leaf blight caused by Botrytis squamosa was analyzed over space and time by Carisse et al [10] who observed that lesion density varied from 0.00 to 15. The association of airborne conidia of B. cinerea with disease has been recorded in other crops, too, such as strawberry [11,12], raspberry [13], grapes [14,15] and gerbera [16].…”

Spatial Pattern of Strawberry Powdery Mildew (Podosphaera aphanis) and Airborne Inoculum

“…After exposure, the rods were kept at 4°C and the number of conidia was counted under a microscope at x250 magnification within 1 week. The counts were transformed into conidia per cubic meter of air sampled (4,7). Data analysis.…”

“…When A or Aj¡ is greater than 1 and b is equal to 1, the spatial pattern is aggregated, but the level of aggregation is not directly influenced by the mean. If A or A., and b are both greater than 1, the spatial pattern is considered to be aggregated, and the aggregation is directly related to the mean (7,13,14,18,24,25). The significance of the estimated parameters was determined with a t test, and goodness-of-fit was evaluated using the coefficient of determination (R^).…”

“…The overall association index (X) was estimated under the null hypothesis of lack of association; the procedure investigates the arrangement of the counts of both paired variables. A value of X greater than 0 is an indication of spafial association (7,24). A •£ test was used to determine whether /" was significantly different from 1, and Dutilleuladjusted randomizations (10) were used to test whether X was significantly higher than 0.…”

Botrytis squamosa: The Pathogen of Market Disease of Garlic Sprouts

“…Allium crops, such as onion [15][16][17][18][19][20] , garlic and chives 21) . There are many reports about this pathogen infecting garlic sprouts in storage periods 1,2,5) , but fewer about the disease symptoms and damage in markets.…”