Image-based time series analysis to establish differential disease progression for two Fusarium head blight pathogens in oat spikelets with variable resistance

Mirko Pavicic; Katriina Mouhu; Juho Hautsalo; Daniel Jacobson; Marja Jalli; Kristiina Himanen

doi:10.3389/fpls.2023.1126717

Image-based time series analysis to establish differential disease progression for two Fusarium head blight pathogens in oat spikelets with variable resistance

Front Plant Sci. 2023 Mar 14:14:1126717. doi: 10.3389/fpls.2023.1126717. eCollection 2023.

Authors

Mirko Pavicic^{1

2

3}, Katriina Mouhu^{1

2}, Juho Hautsalo⁴, Daniel Jacobson^{3

5}, Marja Jalli⁴, Kristiina Himanen^{1

2

6}

Affiliations

¹ National Plant Phenotyping Infrastructure, Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland.
² Department of Agricultural Sciences, Viikki Plant Science Centre, Helsinki, Finland.
³ Computational and Predictive Biology, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.
⁴ Natural Resources Institute Finland (Luke), Management and Production of Renewable Resources Planta, Jokioinen, Finland.
⁵ Bredesen Center, University of Tennessee Knoxville, Knoxville, TN, United States.
⁶ Organismal and Evolutionary Biology Research Programme, Biocenter Finland, University of Helsinki, Helsinki, Finland.

Abstract

Oat-based value-added products have increased their value as healthy foodstuff. Fusarium head blight (FHB) infections and the mycotoxins accumulated to the oat seeds, however, pose a challenge to oat production. The FHB infections are predicted to become more prevalent in the future changing climates and under more limited use of fungicides. Both these factors increase the pressure for breeding new resistant cultivars. Until now, however, genetic links in oats against FHB infection have been difficult to identify. Therefore, there is a great need for more effective breeding efforts, including improved phenotyping methods allowing time series analysis and the identification of molecular markers during disease progression. To these ends, dissected spikelets of several oat genotypes with different resistance profiles were studied by image-based methods during disease progression by Fusarium culmorum or F. langsethiae species. The chlorophyll fluorescence of each pixel in the spikelets was recorded after inoculation by the two Fusarium spp., and the progression of the infections was analyzed by calculating the mean maximum quantum yield of PSII (F_v/F_m) values for each spikelet. The recorded values were (i) the change in the photosynthetically active area of the spikelet as percentage of its initial size, and (ii) the mean of F_v/F_m values of all fluorescent pixels per spikelet post inoculation, both indicative of the progression of the FHB disease. The disease progression was successfully monitored, and different stages of the infection could be defined along the time series. The data also confirmed the differential rate of disease progression by the two FHB causal agents. In addition, oat varieties with variable responses to the infections were indicated.

Keywords: Fusarium head blight; cereals; chlorophyll fluorescence; image based phenotyping; oats; time series analysis.

Grants and funding

This work was supported by Becas Chile from the Chilean National Agency for Research and Development (ANID), MP (investigation); Agronomiliitto, Oiva Kuusisto grant 31.10.2017, JH and MJ (methodology); Makera grant # 533/03.01.2018, MJ and KH (project funding); NordForsk University HUB NordPlant grant # 84597, KH (project funding); HiLIFE-RIA2020 KH (facility management and coordination of research); and UH institutional open access publication in Frontiers KH.