Abstract

The detection of plant diseases, including fungi, is a major challenge for reducing yield gaps of crops across the world. We explored the potential of the PROCOSINE radiative transfer model to assess the effect of the fungus Pseudocercospora fijiensis on leaf tissues using laboratory-acquired submillimetre-scale hyperspectral images in the visible and near-infrared spectral range. The objectives were (i) to assess the dynamics of leaf biochemical and biophysical parameters estimated using PROCOSINE inversion as a function of the disease stages, and (ii) to discriminate the disease stages by using a Linear Discriminant Analysis model built from the inversion results. The inversion results show that most of the parameter dynamics are consistent with expectations: for example, the chlorophyll content progressively decreased as the disease spreads, and the brown pigments content increased. An overall accuracy of 78.7% was obtained for the discrimination of the six disease stages, with errors mainly occurring between asymptomatic samples and first visible disease stages. PROCOSINE inversion provides relevant ecophysiological information to better understand how P. fijiensis affects the leaf at each disease stage. More particularly, the results suggest that monitoring anthocyanins may be critical for the early detection of this disease.

Published in

Scientific Reports
2018, Volume: 8, article number: 15933
Publisher: NATURE PUBLISHING GROUP

SLU Authors

• Morel, Julien

  • Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences
    
  • National research institute of science and technology for environment and agriculture (IRSTEA)

UKÄ Subject classification

Agricultural Science


Publication identifier

DOI: https://doi.org/10.1038/s41598-018-34429-0

Permanent link to this page (URI)

https://res.slu.se/id/publ/97050