Temporal Dynamics of Botrytis cinerea and Sclerotinia sclerotiorum in Seed Alfalfa Fields of Southern Alberta, Canada

Fungicide-Resistant Botrytis in Forest Nurseries May Impact Disease Control in Norway Spruce

Gray mold, caused by Botrytis spp., is a serious problem in Norway spruce seedling production in forest nurseries. From 2013 to 2019, 125 isolates of Botrytis were obtained from eight forest nurseries in Norway: 53 from Norway spruce seedlings, 16 from indoor air, 52 from indoor surfaces, and four from weeds growing close to seedlings. The majority of isolates were identified as B. cinerea, and over 60% of these were characterized as Botrytis group S. B. pseudocinerea isolates were obtained along with isolates with DNA sequence similarities to B. prunorum. Fungicide resistance was assessed with a mycelial growth assay, and resistance was found for the following: boscalid (8.8%), fenhexamid (33.6%), fludioxonil (17.6%), pyraclostrobin (36.0%), pyrimethanil (13.6%), and thiophanate-methyl (50.4%). Many isolates (38.4%) were resistant to two to six different fungicides. A selection of isolates was analyzed for the presence of known resistance-conferring mutations in the cytb, erg27, mrr1, sdhB, and tubA genes, and mutations leading to G143A, F412S, ΔL497, H272R, and E198A/F200Y were detected, respectively. Detection of fungicide resistance in Botrytis from Norway spruce and forest nursery facilities reinforces the necessity of employing resistance management strategies to improve control and delay development of fungicide resistance in the gray mold pathogens.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Occurrence of Ascospores and White Mold Caused by Sclerotinia sclerotiorum in Dry Bean Fields in Alberta, Canada

White mold caused by the fungal pathogen Sclerotinia sclerotiorum (Lib.) de Bary is one of the most important biological constraints to dry bean (Phaseolus vulgaris L.) production in Canada. Disease forecasting is one tool that could help growers manage the disease while reducing fungicide use. However, predicting white mold epidemics has remained difficult due to their sporadic occurrence. In this study, over the course of four growing seasons (2018 to 2021), we surveyed dry bean fields in Alberta and collected daily in-field weather data and daily in-field ascospore counts. White mold levels were variable and generally high in all years, confirming that the disease is ubiquitous and a constant threat to dry bean production. Ascospores were present throughout the growing season, and mean ascospore levels varied by field, month, and year. Models based on in-field weather and ascospore levels were not highly predictive of final disease incidence in a field, suggesting that environment and pathogen presence were not limiting factors to disease development. Rather, significant effects of market class on disease were found, with pinto beans, on average, having the highest disease incidence (33%) followed by great northern (15%), black (10%), red (6%), and yellow (5%). When incidence of these market classes was modeled separately, different environmental variables were important in each model; however, average wind speed was a significant variable in all models. Taken together, these findings suggest that white mold management in dry bean should focus on fungicide use, plant genetics, irrigation management, and other agronomic factors.

Control of white mold (Sclerotinia sclerotiorum) through plant-mediated RNA interference

The causative agent of white mold, Sclerotinia sclerotiorum, is capable of infecting over 600 plant species and is responsible for significant crop losses across the globe. Control is currently dependent on broad-spectrum chemical agents that can negatively impact the agroecological environment, presenting a need to develop alternative control measures. In this study, we developed transgenic Arabidopsis thaliana (AT1703) expressing hairpin (hp)RNA to silence S. sclerotiorum ABHYDROLASE-3 and slow infection through host induced gene silencing (HIGS). Leaf infection assays show reduced S. sclerotiorum lesion size, fungal load, and ABHYDROLASE-3 transcript abundance in AT1703 compared to wild-type Col-0. To better understand how HIGS influences host-pathogen interactions, we performed global RNA sequencing on AT1703 and wild-type Col-0 directly at the site of S. sclerotiorum infection. RNA sequencing data reveals enrichment of the salicylic acid (SA)-mediated systemic acquired resistance (SAR) pathway, as well as transcription factors predicted to regulate plant immunity. Using RT-qPCR, we identified predicted interacting partners of ABHYDROLASE-3 in the polyamine synthesis pathway of S. sclerotiorum that demonstrate co-reduction with ABHYDROLASE-3 transcript levels during infection. Together, these results demonstrate the utility of HIGS technology in slowing S. sclerotiorum infection and provide insight into the role of ABHYDROLASE-3 in the A. thaliana-S. sclerotiorum pathosystem.

First Long-Time Airborne Fungal Spores Study in Dublin, Ireland (1978–1980)

Ambient fungal spores within the atmosphere can contribute to a range of negative human, animal and plant health conditions and diseases. However, trends in fungal spore seasonality, species prevalence, and geographical origin have been significantly understudied in Ireland. Previously unpublished data from the late 1970s have recently been collected and analysed to establish historical fungal spore trends/characteristics for Dublin. Historical spore concentrations were largely dominated by Alternaria, Ascospores, Basidiospores, Botrytis, Cladosporium, Erysiphe and Rusts. The main fungal spore season for Dublin commenced in April with the fructification of Scopulariopsis and Ganoderma. However, the vast majority of other spore types did not reach peak spore release until late summer. The correlation between ambient spore concentration, and meteorological parameters was examined using Multivariable Regression Tree (MRT) analysis. The notable correlations found for fungal spore concentrations tended to involve temperature-based parameters. The use of a non-parametric wind regression was also employed to determine the potential geographical origin of ambient fungal spores. The impact of wind direction, and high windspeed on fungal spores was established, ultimately highlighting the importance of studying and monitoring fungal spores within Ireland, rather than attempting to rely on data from other regions, as most fungal spores collected in Dublin appeared to originate from within the island.

Characterization of Botrytis cinerea and B. prunorum From Healthy Floral Structures and Decayed 'Hayward' Kiwifruit During Post-Harvest Storage

Gray mold is the primary postharvest disease of 'Hayward' kiwifruit (Actinidia deliciosa) in Chile, with a prevalence of 33.1% in 2016 and 7.1% in 2017. Gray mold develops during postharvest storage, which is characterized by a soft, light to brown watery decay that is caused by Botrytis cinerea and B. prunorum. However, there is no information on the role of B. prunorum during the development and storage of kiwifruit in Chile. For this purpose, asymptomatic flowers and receptacles were collected throughout fruit development and harvest from five orchards over two seasons in the Central Valley of Chile. Additionally, diseased kiwifruits were selected after storage for 100 days at 0°C and 2 days at 20°C. Colonies of Botrytis sp. with high and low conidial production were consistently obtained from apparently healthy petals, sepals, receptacles, and styles and diseased kiwifruit. Morphological and phylogenetic analysis of three partial gene sequences encoding glyceraldehyde-3-phosphate dehydrogenase, heat shock protein 60, and DNA-dependent RNA polymerase subunit II were able to identify and separate B. cinerea and B. prunorum species. Consistently, B. cinerea was predominantly isolated from all floral parts and fruit in apparently healthy tissue and diseased kiwifruit. During full bloom, the highest colonization by B. cinerea and B. prunorum was obtained from petals, followed by sepals. In storage, both Botrytis species were isolated from the diseased fruit (n = 644), of which 6.8% (n = 44) were identified as B. prunorum. All Botrytis isolates grew from 0°C to 30°C in vitro and were pathogenic on kiwifruit leaves and fruit. Notably, B. cinerea isolates were always more virulent than B. prunorum isolates. This study confirms the presence of B. cinerea and B. prunorum colonizing apparently healthy flowers and floral parts in fruit and causing gray mold during kiwifruit storage in Chile. Therefore, B. prunorum plays a secondary role in the epidemiology of gray mold developing in kiwifruit during cold storage.

Weather-Based Models for Assessing the Risk of Sclerotinia sclerotiorum Apothecial Presence in Soybean (Glycine max) Fields

Sclerotinia stem rot (SSR) epidemics in soybean, caused by Sclerotinia sclerotiorum, are currently responsible for annual yield reductions in the United States of up to 1 million metric tons. In-season disease management is largely dependent on chemical control but its efficiency and cost-effectiveness depends on both the chemistry used and the risk of apothecia formation, germination, and further dispersal of ascospores during susceptible soybean growth stages. Hence, accurate prediction of the S. sclerotiorum apothecial risk during the soybean flowering period could enable farmers to improve in-season SSR management. From 2014 to 2016, apothecial presence or absence was monitored in three irrigated (n = 1,505 plot-level observations) and six nonirrigated (n = 2,361 plot-level observations) field trials located in Iowa (n = 156), Michigan (n = 1,400), and Wisconsin (n = 2,310), for a total of 3,866 plot-level observations. Hourly air temperature, relative humidity, dew point, wind speed, leaf wetness, and rainfall were also monitored continuously, throughout the season, at each location using high-resolution gridded weather data. Logistic regression models were developed for irrigated and nonirrigated conditions using apothecial presence as a binary response variable. Agronomic variables (row width) and weather-related variables (defined as 30-day moving averages, prior to apothecial presence) were tested for their predictive ability. In irrigated soybean fields, apothecial presence was best explained by row width (r = -0.41, P < 0.0001), 30-day moving averages of daily maximum air temperature (r = 0.27, P < 0.0001), and daily maximum relative humidity (r = 0.16, P < 0.05). In nonirrigated fields, apothecial presence was best explained by using moving averages of daily maximum air temperature (r = -0.30, P < 0.0001) and wind speed (r = -0.27, P < 0.0001). These models correctly predicted (overall accuracy of 67 to 70%) apothecial presence during the soybean flowering period for four independent datasets (n = 1,102 plot-level observations or 30 daily mean observations).