Author:
Nordström Ida,Sherwood Patrick,Bohman Björn,Woodward Stephen,Peterson Donnie L.,Niño-Sánchez Jonatan,Sánchez-Gómez Tamara,Díez Julio Javier,Cleary Michelle
Abstract
AbstractFusarium circinatum, a fungal pathogen deadly to many Pinus species, can cause significant economic and ecological losses, especially if it were to become more widely established in Europe. Early detection tools with high-throughput capacity can increase our readiness to implement mitigation actions against new incursions. This study sought to develop a disease detection method based on volatile organic compound (VOC) emissions to detect F. circinatum on different Pinus species. The complete pipeline applied here, entailing gas chromatography—mass spectrometry of VOCs, automated data analysis and machine learning, distinguished diseased from healthy seedlings of Pinus sylvestris and Pinus radiata. In P. radiata, this distinction was possible even before the seedlings became visibly symptomatic, suggesting the possibility for this method to identify latently infected, yet healthy looking plants. Pinus pinea, which is known to be relatively resistant to F. circinatum, remained asymptomatic and showed no changes in VOCs over 28 days. In a separate analysis of in vitro VOCs collected from different species of Fusarium, we showed that even closely related Fusarium spp. can be readily distinguished based on their VOC profiles. The results further substantiate the potential for volatilomics to be used for early disease detection and diagnostic recognition.
Funder
Svenska Forskningsrådet Formas
Crafoordska Stiftelsen
Carl Tryggers Stiftelse för Vetenskaplig Forskning
Kungl. Skogs- och Lantbruksakademien
Stiftelsen fonden för skogsvetenskaplig forskning
Erasmus+
Anna-Britta & Vadim Söderströms resestipendium
NordGen Forest SNS scholarships
Swedish University of Agricultural Sciences
Publisher
Springer Science and Business Media LLC
Cited by
2 articles.
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