AUTHOR=Ficke Andrea , Asalf Belachew , Norli Hans Ragnar 

TITLE=Volatile Organic Compound Profiles From Wheat Diseases Are Pathogen-Specific and Can Be Exploited for Disease Classification

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.803352

DOI=10.3389/fmicb.2021.803352

ISSN=1664-302X

ABSTRACT=Plants and fungi emit volatile organic compounds (VOCs) that are either constitutively produced or are produced in response to changes in their physio-chemical status. We hypothesized that these chemical signals could be utilized as diagnostic tools for plant diseases. VOCs from several common wheat pathogens in pure culture (Fusarium graminearum, F. culmorum. F. avenaceum, F. poae, Parastagonospora nodorum) were collected and compared among isolates of the same fungus, between pathogens from different species and between pathogens causing different disease groups (Fusarium head blight (FHB) and Septoria nodorum blotch (SNB)). In addition, we inoculated two wheat varieties plants  with either F. graminearum or,  P. nodorum, while one variety was also inoculated with or Blumeria graminis f.sp. tritici, (PM). and collected  VOCs were collected 7, 14, and 21 days after inoculation. Each fungal species in pure culture emitted a different VOC blend and each isolate could be classified into its respective disease group based on VOCs with an accuracy of 71.4 and 84.2% for FHB and SNB, respectively. When all collection times were combined, classification of the tested diseases were correct in 84 and 86% of all cases evaluated. Germacrene D and Sativene, which were associated with FHB infection, and Mellein and Heptadecanone, which were associated with SNB infection, were consistently emitted by both wheat varieties. Wheat plants infected with PM emitted significant amounts of 1-Octen-3-ol and 3,5,5-Trimethyl-2-hexene. Our study suggests that VOC blends could be used to classify wheat diseases. This is the first step towards a real-time disease detection in the field based on chemical signatures of wheat diseases.