A new risk indicator for botrytis leaf blight of onion caused by Botrytis squamosa based on infection efficiency of airborne inoculum

Abstract

Botrytis leaf blight (BLB) caused by Botrytis squamosa is a major leaf disease of onion. Various forecasting systems have been developed to help growers manage the disease. To improve forecasting reliability, the influence of temperature and wetness duration on B. squamosa infection was quantified by inoculating onion leaves with a conidial suspension and incubating them under various combinations of temperature (10-30°C) and leaf wetness duration (0-84 h). Infection was measured as the number of lesions per cm 2 of leaf and converted to the proportion of maximum infection (PMI). Regardless of leaf wetness duration, only a few lesions developed at 30°C and the number of lesions increased as the temperature rose from 10 to 20°C but decreased at 25°C. Between 10 and 25°C the number of lesions per cm 2 of leaf area increased gradually with increasing leaf wetness duration from 12 to 72 h. Relative infection was modelled as a function of both temperature and wetness duration using a modified version of the Weibull equation, which provided a precise description of the response of B. squamosa (R 2 = 0AE88). To facilitate field validation, receiving operating characteristic curve analysis was performed to determine the accuracy of various sets of criteria for establishing the length of an infection event based on field weather data. The total number of leaf wetness and RH >90% hours over a 72 h period was the best criterion, regardless of the wetness interruption pattern (sensitivity = 90AE91, specificity = 84AE62, area under the receiving operating curve = 0AE878). The model describing the relationship of PMI to temperature and leaf wetness duration, and field observations on airborne conidium concentration (ACC) were used to calculate the risk of infection (RI BLB ) as RI BLB = PMI · ACC. In 2009 and 2010, this risk index was compared to the observed rate of BLB progress (Rate BLB+5 days ) during the following 5 days. There was a linear relationship between RI BLB and Rate BLB+5 days indicating that this new risk indicator was reliable for predicting the risk of BLB development. These findings will help to improve the timing of fungicide applications for BLB management.

Development of a grower‐conducted inoculum detection assay for management of grape powdery mildew

“…However, the LAMP assay does not require expensive technology or formal training for DNA extraction and the detection of inoculum (Notomi et al ., ), making it suitable for commercial use with grapevine growers conducting the detection analyses. This study, in conjunction with other studies (Falacy et al ., ; Carisse et al ., , ; Van der Heyden et al ., ), also demonstrates that there may be benefit to managing polycyclic diseases, at least those caused by other Erysiphales, using airborne inoculum detection assays. In both sampling years, the L‐LAMP detection results were not significantly different from that of the qPCR detection results, indicating that the extraction assay was sufficient for detection (Table ).…”

Innovations in air sampling to detect plant pathogens

“…Only in a relatively few cases, have thresholds been identified that indicate a particular disease risk, e.g. 50 conidia m −3 d −1 of Erysiphe necator was identified in Quebec, but this was for a specific grape variety (cv Chancellor) (Carisse et al , 2009b ) and often the spore concentration or area under a spore curve needs to be combined with an infection model to indicate actual disease risk (Carisse et al , 2012 ).…”

Comparison of Botrytis cinerea airborne inoculum progress curves from raspberry, strawberry and grape plantings

“…Plant disease surveillance can be defined as the ongoing collection and analysis of data for making decisions regarding disease prediction and management. Detection and quantification of airborne inoculum contribute to fungal disease management by guiding decisions regarding control measures (Carisse et al ., ; Van der Heyden et al ., ). With recent advances in fungal molecular quantification techniques (Carisse et al ., ), aerobiological data are expected to play a critical role in plant disease surveillance.…”

“…Since then, several researchers have studied the correlation or association between disease or yield losses and airborne inoculum occurring on the same day or some days earlier (Carisse et al ., , ). Airborne spore monitoring in disease control management programmes has proven to be of practical use for pathogens such as Phytophthora infestans and Botrytis squamosa , the causal agents of tomato late blight and onion leaf blight respectively (Bugiani et al ., ; Carisse et al ., ; Van der Heyden et al ., ).…”