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.

Early blight, caused by Alternaria solani, along with brown spot, caused by A. alternata, have the potential to reduce quality and yield in potato production globally. Prior to this study, the incidence, disease impact, and fungicide resistance attributes of A. alternata in Wisconsin were poorly understood. Potato pathogens were isolated from foliar lesions at three commercial locations in Wisconsin in 2012 and 2017 and were initially morphologically identified as A. solani (n = 33) and A. alternata (n = 40). Identifications were further corroborated with the phylogenetic analysis of the internal transcribed spacer (ITS), translation elongation factor 1 (TEF1), gapdh, Alt a 1, and OPA10-2. A multigene phylogeny of ITS, TEF1, gapdh, and Alt a 1 showed five genotypes of A. alternata and one single genotype of A. solani. We demonstrated that the A. alternata isolates were virulent on potato cultivars Russet Burbank (P < 0.013) and Atlantic (P < 0.0073), though they caused less disease than A. solani (P < 0.0001 and P < 0.0001, respectively). A. alternata caused little disease on the breeding line 24-24-12 (P = 0.9929), and A. solani caused fewer disease symptoms on 24-24-12 than on Russet Burbank (P < 0.0001) or Atlantic (P < 0.0001). Breeding line 24-24-12 may be a promising source of potential resistance for the two diseases. There was no significant difference in virulence of different A. alternata genotypes, and no significant difference in virulence or genotype clustering among isolates from the three locations. Isolates of A. alternata that induced chlorosis caused larger lesion areas than isolates that did not in Russet Burbank (P < 0.0001), Atlantic (P < 0.0001), and 24-24-12 (P = 0.0365). There was no significant difference in virulence between quinone outside inhibitor (QoI)-sensitive and QoI-resistant isolates of A. alternata. This study enhanced our understanding of potato early blight and brown spot in Wisconsin, and suggested that A. alternata in addition to A. solani should be carefully monitored and possibly uniquely managed in order to achieve overall disease control.

Common scab, caused by Streptomyces scabies and related species, is a potato tuber blemish disease that causes reductions in marketable yield worldwide. Evidence of suppression of common scab by indigenous soil microbial populations has been found in several studies. However, we lack a comprehensive understanding of how common scab severity relates functionally to potato varieties, farming systems, soil physical and chemical properties, and soil microbial communities. These factors may affect disease directly or indirectly by affecting one of the other variables. We performed a survey of 30 sampling locations across 12 fields in Wisconsin and used structural equation modeling to disentangle the direct effects of potato market classes, farm management (conventional versus organic), and soil physiochemical properties on common scab severity from their indirect effects mediated through soil bacterial and fungal communities. We found that, although potato market classes affected disease severity directly, the effects of farm management and soil physiochemistry were best explained as indirect, mediated by their impacts on soil bacterial communities. This suggests that evaluating the consequences of specific management practices for soil microbial communities may be useful for understanding disease pressure across fields.

Populations of Phytophthora infestans, the oomycete causal agent of potato late blight in the United States, are predominantly asexual, and isolates are characterized by clonal lineage or asexual descendants of a single genotype. Current tools for clonal lineage identification are time consuming and require laboratory equipment. We previously found that foliar spectroscopy can be used for high-accuracy pre- and postsymptomatic detection of P. infestans infections caused by clonal lineages US-08 and US-23. In this work, we found subtle but distinct differences in spectral responses of potato foliage infected by these clonal lineages in both growth-chamber time-course experiments (12- to 24-h intervals over 5 days) and naturally infected samples from commercial production fields. In both settings, we measured continuous visible to shortwave infrared reflectance (400 to 2,500 nm) on leaves using a portable spectrometer with contact probe. We consistently discriminated between infections caused by the two clonal lineages across all stages of disease progression using partial least squares (PLS) discriminant analysis, with total accuracies ranging from 88 to 98%. Three-class random forest differentiation between control, US-08, and US-23 yielded total discrimination accuracy ranging from 68 to 76%. Differences were greatest during presymptomatic infection stages and progressed toward uniformity as symptoms advanced. Using PLS-regression trait models, we found that total phenolics, sugar, and leaf mass per area were different between lineages. Shortwave infrared wavelengths (>1,100 nm) were important for clonal lineage differentiation. This work provides a foundation for future use of hyperspectral sensing as a nondestructive tool for pathovar differentiation.

Quinone outside inhibitor (QoI) fungicides have been an important class in managing potato early blight caused by Alternaria solani and brown spot caused by A. alternata. Because of the single-site mode of action character of QoI fungicides, which are relied on for management of diseases in Wisconsin, and the abundant asexual conidia production of the Alternaria species, pathogen isolates with QoI resistance have been detected after just a few years of QoI fungicide usage in commercial production fields. Resistance to QoIs has been attributed to amino acid substitutions F129L and G143A in cytochrome b of A. solani and A. alternata, respectively, as a result of point mutations. The aim of this study was to assess Alternaria populations in Wisconsin for QoI resistance before and after fungicide applications in order to evaluate resistance stability. A TaqMan single nucleotide polymorphism genotyping assay was designed based on the sequences of the cytochrome b gene from Alternaria isolates collected in Wisconsin to profile QoI resistance in Alternaria populations as well as to explore factors that may influence frequency of QoI resistance in the pathogen populations. This assay successfully identified the mutations conferring QoI resistance in isolates collected from four locations each year from 2015 to 2017. During the course of this study, the frequency of A. solani isolates with the F129L mutation was consistently high and showed primarily the TTA mutation type. The frequency of A. alternata isolates with the G143A mutation started relatively low and increased at the end of the production season in each year (P = 0.0109, P = 0.2083, and P = 0.0159). A potato field managed without use of QoI fungicides showed a significantly lower (P < 0.05) frequency of A. alternata isolates carrying G143A than conventionally managed potato fields. The overall frequency of A. alternata isolates carrying G143A in the four locations was similar over the 3 years (P = 0.2971). The QoI resistance characteristics of the isolates were stable even when QoI selection pressure was removed for at least five subculture transfers, and the mutation types of codons 129 and 143 in the cytochrome b gene in A. solani and A. alternata, respectively, remained the same. This indicated that the application of QoIs in the field is not the sole factor responsible for the variation of the frequency of QoI resistance in the pathogen populations.