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.

Plant disease threatens the environmental and financial sustainability of crop production, causing $220 billion in annual losses. The dire threat disease poses to modern agriculture demands tools for better detection and monitoring to prevent crop loss and input waste.

The U.S. wine and grape industry loses $3B annually due to viral diseases including grapevine leafroll-associated virus complex 3 (GLRaV-3). Current detection methods are labor-intensive and expensive. GLRaV-3 has a latent period in which the vines are infected but do not display visible symptoms, making it an ideal model to evaluate the scalability of imaging spectroscopy-based disease detection. The NASA Airborne Visible and Infrared Imaging Spectrometer Next Generation was deployed to detect GLRaV-3 in Cabernet Sauvignon grapevines in Lodi, CA in September 2020. Foliage was removed from the vines as part of mechanical harvest soon after image acquisition. In September of both 2020 and 2021, industry collaborators scouted 317 hectares on a vine-by-vine basis for visible viral symptoms and collected a subset for molecular confirmation testing. Symptomatic grapevines identified in 2021 were assumed to have been latently infected at the time of image acquisition. Random forest models were trained on a spectroscopic signal of noninfected and GLRaV-3 infected grapevines balanced with synthetic minority oversampling of noninfected and GLRaV-3 infected grapevines. The models were able to differentiate between noninfected and GLRaV-3 infected vines both pre- and postsymptomatically at 1 to 5 m resolution. The best-performing models had 87% accuracy distinguishing between noninfected and asymptomatic vines, and 85% accuracy distinguishing between noninfected and asymptomatic + symptomatic vines. The importance of nonvisible wavelengths suggests that this capacity is driven by disease-induced changes to plant physiology. The results lay a foundation for using the forthcoming hyperspectral satellite Surface Biology and Geology for regional disease monitoring in grapevine and other crop species. [ ] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

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.

Nighttime applications of germicidal ultraviolet were evaluated as a means to suppress three diseases of grapevine. In laboratory studies, UV-C light (peak 254 nm, FWHM 5 nm) applied during darkness strongly inhibited the germination of conidia of Erysiphe necator, and at a dose of 200 J/m², germination was zero. Reciprocity of irradiance and duration of exposure with respect to conidial germination was confirmed for UV-C doses between 0 and 200 J/m² applied at 4 or 400 s. When detached grapevine leaves were exposed during darkness to UV-C at 100 J/m² up to 7 days before they were inoculated with zoospores of Plasmopara viticola, infection and subsequent sporulation was reduced by over 70% compared to untreated control leaves, indicating an indirect suppression of the pathogen exerted through the host. A hemicylindrical array of low-pressure discharge UV-C lamps configured for trellised grapevines was designed and fitted to both a tractor-drawn carriage and a fully autonomous robotic carriage for vineyard applications. In 2019, in a Chardonnay research vineyard with a history of high inoculum and severe disease, weekly nighttime applications of UV-C suppressed E. necator on leaves and fruit at doses of 100 and 200 J/m². In the same vineyard in 2020, UV-C was applied once or twice weekly at doses of 70, 100, or 200 J/m², and severity of E. necator on both leaves and fruit was significantly reduced compared to untreated controls; twice-weekly applications at 200 J/m² provided suppression equivalent to a standard fungicide program. None of the foregoing UV-C treatments significantly reduced the severity of P. viticola on Chardonnay vines compared to the untreated control in 2020. However, twice-weekly applications of UV-C at 200 J/m² to the more downy mildew-resistant Vitis interspecific hybrid cultivar Vignoles in 2021 significantly suppressed foliar disease severity. In commercial Chardonnay vineyards with histories of excellent disease control in Dresden, NY, E. necator remained at trace levels on foliage and was zero on fruit following weekly nighttime applications of UV-C at 200 J/m² in 2020 and after weekly or twice-weekly application of UV-C at 100 or 200 J/m² in 2021. In 2019, weekly nighttime applications of UV-C at 200 J/m² also significantly reduced the severity of sour rot, a decay syndrome of complex etiology, on fruit of ‘Vignoles’ but not the severity of bunch rot caused by Botrytis cinerea. A similar level of suppression of sour rot was observed on ‘Vignoles’ vines treated twice-weekly with UV-C at 200 J/m² in 2021. Nighttime UV-C applications did not produce detectable indications of metabolic abnormalities, phytotoxicity, growth reduction, or reductions of fruit yield or quality parameters, even at the highest doses and most frequent intervals employed.

Pathogenic fungi are a leading cause of crop disease and primarily spread through microscopic, durable spores adapted differentially for both persistence and dispersal via soil, animals, water, and/or the atmosphere. Computational Earth system models and air pollution models have been used to simulate atmospheric spore transport for aerial-dispersal-adapted (airborne) rust diseases, but the importance of atmospheric spore transport for soil-dispersal-adapted (soilborne) diseases remains unknown. While a few existing simulation studies have focused on intracontinental dispersion, transoceanic and intercontinental atmospheric transport of soilborne spores entrained in agricultural dust aerosols is understudied and may contribute to disease spread. This study adapts the Community Atmosphere Model, the atmospheric component of the Community Earth System Model, to simulate the global transport of the plant pathogenic soilborne fungus Fusarium oxysporum (F. oxy). Our sensitivity study assesses the model’s accuracy in long-distance aerosol transport and the impact of deposition rate on simulated long-distance spore transport in Summer 2020 during a major dust transport event from Northern Sub-Saharan Africa to the Caribbean and southeastern United States (U.S.). We find that decreasing wet and dry deposition rates by an order of magnitude improves representation of long-distance, trans-Atlantic dust transport. Simulations also suggest that a small number of spores can survive trans-Atlantic transport to be deposited in agricultural zones. This number is dependent on source spore parameterization, which we improved through a literature search to yield a global map of F. oxy spore distribution in source agricultural soils. Using this map and aerosol transport modeling, we show how potentially viable spore numbers in the atmosphere decrease with distance traveled and offer a novel danger index for modeled viable spore deposition in agricultural zones. Our work finds that intercontinental transport of viable spores to cropland is greatest between Eurasia, North Africa, and Sub-Saharan Africa, suggesting that future observational studies should concentrate on these regions.