{"title":"Incidence of brown rot disease caused by Gnomoniopsis smithogilvyi on buds, flowers and chestnuts and rapid HRM-based detection of the disease","authors":"Eleni Topalidou , Georgios Lagiotis , Irene Bosmali , Eleni Stefanidou , Dimitrios Tsirogiannis , Anna Maria Vettraino , Panagiotis Madesis","doi":"10.1016/j.funbio.2024.06.003","DOIUrl":null,"url":null,"abstract":"<div><p>Chestnut production is considered one of the most important economic resources of rural mountainous areas in Greece. Lately, producers report a steep rise in the incidence of brown rot disease caused by the fungus <em>Gnomoniopsis smithogilvyi</em> (Gnomoniaceae, Diaporthales), which results in severe chestnut rot. The pathogen is considered an emerging pathogen in many countries worldwide (Italy, France, Switzerland, Australia, New Zealand). This study aimed at (a) exploring the incidence of the brown rot disease in Vria (Regional Unit of Pieria, Region of Central Makedonia, Greece), (b) isolating and identifying the causal agent of the disease, (c) exploring the fungus presence at different phenological stages of the chestnut trees, and (d) implementing species-specific Bar- High Resolution Melting Analysis (HRM) for the early detection of <em>G. smithogilvyi</em> in chestnuts. <em>G. smithogilvyi</em> occurrence in chestnut tissues was more severe in June (59 %), nearly disappeared in July (19 %) and August (7 %) and increased again during harvesting time in September (57 %). This result could be attributed to a sum of different factors, including climate conditions. Moreover, it was demonstrated that <em>G. smithogilvyi</em> can be identified using a Bar-HRM analysis of chestnut tissues (buds, flowers and nuts). Results of this study clearly demonstrate that Bar-HRM can be used for the accurate, rapid and reliable identification of <em>G. smithogilvyi</em> universally on infected samples from different localities.</p></div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1878614624000849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Chestnut production is considered one of the most important economic resources of rural mountainous areas in Greece. Lately, producers report a steep rise in the incidence of brown rot disease caused by the fungus Gnomoniopsis smithogilvyi (Gnomoniaceae, Diaporthales), which results in severe chestnut rot. The pathogen is considered an emerging pathogen in many countries worldwide (Italy, France, Switzerland, Australia, New Zealand). This study aimed at (a) exploring the incidence of the brown rot disease in Vria (Regional Unit of Pieria, Region of Central Makedonia, Greece), (b) isolating and identifying the causal agent of the disease, (c) exploring the fungus presence at different phenological stages of the chestnut trees, and (d) implementing species-specific Bar- High Resolution Melting Analysis (HRM) for the early detection of G. smithogilvyi in chestnuts. G. smithogilvyi occurrence in chestnut tissues was more severe in June (59 %), nearly disappeared in July (19 %) and August (7 %) and increased again during harvesting time in September (57 %). This result could be attributed to a sum of different factors, including climate conditions. Moreover, it was demonstrated that G. smithogilvyi can be identified using a Bar-HRM analysis of chestnut tissues (buds, flowers and nuts). Results of this study clearly demonstrate that Bar-HRM can be used for the accurate, rapid and reliable identification of G. smithogilvyi universally on infected samples from different localities.