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Open AccessArticle

Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato

1
Plant Pathology and Plant Microbe Biology Section, Cornell University, 15 Castle Creek Drive, Geneva, NY 14456, USA
2
Department of Forestry and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, USA
3
The Robert H. Smith Institute for Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 7610001, Israel
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Departments of Entomology and Forestry and Natural Resources and Center for Plant Biology, Purdue University, 224 Whistler Hall, West Lafayette, IN 47907, USA
5
Department of Plant Pathology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI 53706, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(2), 286; https://doi.org/10.3390/rs12020286
Received: 4 December 2019 / Revised: 7 January 2020 / Accepted: 13 January 2020 / Published: 15 January 2020
(This article belongs to the Special Issue Remote Sensing for Plant Pathology)
In-vivo foliar spectroscopy, also known as contact hyperspectral reflectance, enables rapid and non-destructive characterization of plant physiological status. This can be used to assess pathogen impact on plant condition both prior to and after visual symptoms appear. Challenging this capacity is the fact that dead tissue yields relatively consistent changes in leaf optical properties, negatively impacting our ability to distinguish causal pathogen identity. Here, we used in-situ spectroscopy to detect and differentiate Phytophthora infestans (late blight) and Alternaria solani (early blight) on potato foliage over the course of disease development and explored non-destructive characterization of contrasting disease physiology. Phytophthora infestans, a hemibiotrophic pathogen, undergoes an obligate latent period of two–seven days before disease symptoms appear. In contrast, A. solani, a necrotrophic pathogen, causes symptoms to appear almost immediately when environmental conditions are conducive. We found that respective patterns of spectral change can be related to these differences in underlying disease physiology and their contrasting pathogen lifestyles. Hyperspectral measurements could distinguish both P. infestans-infected and A. solani-infected plants with greater than 80% accuracy two–four days before visible symptoms appeared. Individual disease development stages for each pathogen could be differentiated from respective controls with 89–95% accuracy. Notably, we could distinguish latent P. infestans infection from both latent and symptomatic A. solani infection with greater than 75% accuracy. Spectral features important for late blight detection shifted over the course of infection, whereas spectral features important for early blight detection remained consistent, reflecting their different respective pathogen biologies. Shortwave infrared wavelengths were important for differentiation between healthy and diseased, and between pathogen infections, both pre- and post-symptomatically. This proof-of-concept work supports the use of spectroscopic systems as precision agriculture tools for rapid and early disease detection and differentiation tools, and highlights the importance of careful consideration of underlying pathogen biology and disease physiology for crop disease remote sensing. View Full-Text
Keywords: field spectroscopy; pathogen; plant disease; agriculture; shortwave infrared; hyperspectral field spectroscopy; pathogen; plant disease; agriculture; shortwave infrared; hyperspectral
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MDPI and ACS Style

Gold, K.M.; Townsend, P.A.; Chlus, A.; Herrmann, I.; Couture, J.J.; Larson, E.R.; Gevens, A.J. Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato. Remote Sens. 2020, 12, 286.

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