A duplex droplet digital PCR assay for quantification of Alternaria spp. and Botrytis cinerea on sweet cherry at different growth stages
Sweet cherries (Prunus avium) are an economically important crop in British Columbia, Canada. Cherries are harvested and distributed locally and overseas, where seemingly healthy fruit can succumb to postharvest diseases if disease conditions are met. Disease mitigation includes pre-harvest controls...
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Published in | Canadian journal of plant pathology Vol. 43; no. 5; pp. 734 - 748 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Philadelphia
Taylor & Francis
03.09.2021
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | Sweet cherries (Prunus avium) are an economically important crop in British Columbia, Canada. Cherries are harvested and distributed locally and overseas, where seemingly healthy fruit can succumb to postharvest diseases if disease conditions are met. Disease mitigation includes pre-harvest controls such as disease prediction models, disease monitoring, and fungicide applications. Development of disease-prediction models requires an understanding of how host and environmental conditions can affect the quantity of pathogens; therefore, quick, sensitive and accurate methods for pathogen quantification are required. This study has identified Alternaria spp. and Botrytis cinerea as major contributors to sweet cherry rot in Kelowna, British Columbia, in 2016 and developed a novel duplex droplet digital PCR assay for the rapid, concurrent quantification of the two pathogens. The assay involves the amplification of two abundant target regions, the internal transcribed spacer, and the intergenic spacer, in Alternaria spp. and B. cinerea, respectively. The detection limit was 0.1 pg of DNA for each target. The assay was validated during the 2016 and 2017 growing seasons at the bud break (2017 only), full bloom, petal fall, onset of straw colour and harvest stages of sweet cherry. In general, pathogen quantities were lowest at petal fall and highest during late season. The method can be used in future studies to evaluate pathogen quantities during the growing season and to facilitate the development of disease-prediction models and mitigation practices for growers. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0706-0661 1715-2992 1715-2992 |
DOI: | 10.1080/07060661.2021.1913646 |