Browsing by Author "Khaliq, Ihsanul"

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    Epidemiology of boxwood blight in western North Carolina and Virginia and evaluation of the boxwood blight infection risk model
    Khaliq, Ihsanul; Avenot, Herve F.; Baudoin, Anton; Coop, Leonard; Hong, Chuanxue (Nature Portfolio, 2024-11-05)
    Boxwood blight, caused by Calonectria pseudonaviculata, is a highly invasive emerging disease. Since the first US report in North Carolina and Connecticut in 2011, boxwood blight has spread to over 30 US states, risking more than 90% of boxwood production. Our study investigated the disease field epidemiology and evaluated the boxwood blight infection risk model’s prediction by analysing weekly blight monitoring data collected on detector plants exposed to the prevailing environmental conditions at two different locations (western Virginia and North Carolina) from spring through fall of 2014 to 2017. Boxwood blight was recorded in 61 of 86 weeks, with the highest infected leaf counts recorded in late summer or early fall. Rainfall, high relative humidity outside rainy periods and optimal temperatures (13.6–22.7 °C) during prolonged leaf wetness (> 65 h per week) had a significant positive effect on boxwood blight development. Classification analyses showed that disease predictions from the model using leaf wetness estimated by leaf wetness sensor were more closely aligned with observations from the field than predictions based on algorithms. This study improved our understanding of disease field epidemiology, provided leads to improve the existing model, and generated essential knowledge for formulating effective strategies for blight mitigation.
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    Investigating weather variables driving boxwood blight epidemics: Insights from field trials with Buxus sempervirens 'Suffruticosa' in northern Germany between 2006 and 2020
    Khaliq, Ihsanul; Brand, Thomas; Daughtrey, Margery; Kong, Ping; Hong, Chuanxue (Wiley, 2024-10)
    Boxwood blight is a highly invasive disease, but studies on host–pathogen–environment interactions are rare because the initial research emphasis has been on developing resistant cultivars and chemical control of the disease. We used generalized additive models to investigate weather variables driving boxwood blight epidemics in field trials conducted between 2006 and 2020. Briefly, three or four replicate rows with 10 boxwood plants per row were planted in 0.75 m2 plots. Plants were artificially inoculated in 2006, while those in subsequent years were naturally infected with inoculum left over from previous trials. Disease severity was assessed by estimating the percentage of leaves blighted, including fallen leaves. There was a significant positive main effect of mean rainfall per rainy day, daily minimum temperatures and daily minimum relative humidity on disease severity observed over individual field trial periods. There was a significant negative interaction effect of mean rainfall per rainy day and daily maximum wind speed, and daily minimum relative humidity and daily minimum temperature on disease severity. Higher disease severity was associated with higher mean rainfall per rainy day and lower daily maximum wind speed. Likewise, an increase in daily minimum relative humidity at lower daily minimum temperatures was associated with a greater increase in disease severity than at higher temperatures, suggesting that higher temperatures resulted in lower humidity that led, in turn, to less disease severity. The implications of our findings for forecasting models and conservation of boxwood are discussed.