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

Abstract

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.

Potato Late Blight Detection at the Leaf and Canopy Levels Based in the Red and Red-Edge Spectral Regions

“…In this study, we analyzed the changes in the raw and first-order derivative reflectance spectra in the red and red-edge regions induced by late blight disease on potato leaves and plants. In our experiment, the pre-symptomatology period has the same length as the one of Gold et al [22] but a shorter length than those observed by Schumann [30]. Our study and Gold et al [22] used data acquired in a growth chamber that provides optimal conditions for disease development.…”

“…In our experiment, the pre-symptomatology period has the same length as the one of Gold et al [22] but a shorter length than those observed by Schumann [30]. Our study and Gold et al [22] used data acquired in a growth chamber that provides optimal conditions for disease development. By contrast, Schumann [30] reported field results, where the development of the disease depends on weather conditions and can take more time to be developed.…”

“…Fernández et al [21] Potato late blight NDSI between 400 and 2400 nm. Gold et al [22,41] Pear fire blight…”

“…In the literature, there are several studies that related band reflectances or vegetation indices to late blight occurrence in potato or tomato crops [16][17][18][19][20][21][22], but none of them tested the use of RWP and REP to detect the disease. All of them but Fernández et al [21] and Gold et al [22] were based on one or two dates of experimentations without reporting the moment of inoculation, and thus they were not able to determine the time after inoculation when the disease could be detected with spectral information. This study aims to improve the understanding of the spectral changes of RWP and REP at the leaf and canopy levels due to late blight disease on potato plants from the moment of inoculation.…”

Leaf hyperspectral reflectance as a potential tool to detect diseases associated with vineyard decline

“…Many vineyards show mixed infections by GTDs and GLRaV, making it challenging to inspect visually all acreage within the optimal period for disease expression (Mac Donald et al 2016). The photosynthetic process and the plant tissue cell structures attacked by pathogens suffer alterations that modify the vegetation and electromagnetic radiation interaction and, consequently, leaf and canopy reflectances in the visible (VIS), near-infrared (NIR), and shortwave infrared wavelengths (SWIR) (Prabhakar et al 2012;Calcante et al 2012;Martinelli et al 2015;Mahlein 2016;Heim et al 2018;Zarco-Tejada et al 2018;Gold et al 2019Gold et al , 2020Fallon et al 2020). Light reflection in the VIS, NIR, and SWIR provides a comprehensive assessment of plant responses to diseases due to changing in biochemical (e.g., leaf pigments, nutrient composition, and secondary metabolism) and physiological (e.g., photosynthetic activity and water) aspects (Couture et al 2018).…”