Potatoes are the world’s most produced non-grain crops and an important food source for billions of people. Potatoes are susceptible to numerous pathogens that reduce yield, including Potato virus Y (PVY). Genetic resistance to PVY is a sustainable way to limit yield and quality losses due to PVY infection. Potato cultivars vary in their susceptibility to PVY and include susceptible varieties such as Russet Burbank, and resistant varieties such as Payette Russet. Although the loci and genes associated with PVY-resistance have been identified, the genes and mechanisms involved in limiting PVY during the development of systemic infections have yet to be fully elucidated. To increase our understanding of PVY infection, potato antiviral responses, and resistance, we utilized RNA sequencing to characterize the transcriptomes of two potato cultivars. Since transcriptional responses associated with the extreme resistance response occur soon after PVY contact, we analyzed the transcriptome and small RNA profile of both the PVY-resistant Payette Russet cultivar and PVY-susceptible Russet Burbank cultivar 24 hours post-inoculation. While hundreds of genes, including terpene synthase and protein kinase encoding genes, exhibited increased expression, the majority, including numerous genes involved in plant pathogen interactions, were downregulated. To gain greater understanding of the transcriptional changes that occur during the development of systemic PVY-infection, we analyzed Russet Burbank leaf samples one week and four weeks post-inoculation and identified similarities and differences, including higher expression of genes involved in chloroplast function, photosynthesis, and secondary metabolite production, and lower expression of defense response genes at those time points. Small RNA sequencing identified different populations of 21- and 24-nucleotide RNAs and revealed that the miRNA profiles in PVY-infected Russet Burbank plants were similar to those observed in other PVY-tolerant cultivars and that during systemic infection ~32% of the NLR-type disease resistance genes were targeted by 21-nt small RNAs. Analysis of alternative splicing in PVY-infected potato plants identified splice variants of several hundred genes, including isoforms that were more dominant in PVY-infected plants. The description of the PVY^N-Wi-associated transcriptome and small RNA profiles of two potato cultivars described herein adds to the body of knowledge regarding differential outcomes of infection for specific PVY strain and host cultivar pairs, which will help further understanding of the mechanisms governing genetic resistance and/or virus-limiting responses in potato plants.

We examine the economic costs of potato virus Y (PVY) and benefits to commercial potato growers from using screened seed. To do so, we use a quantile regression model to explore disease spread. We use this model to predict disease prevalence and corresponding losses in commercial potato operations with and without a screening and certification program in place. Our analysis suggests that this screening is very important; the amount of PVY in seed in the summer test is the strongest predictor of PVY in the winter test of the variables in our model. The amount of PVY in the seed can have major effects on commercial potato grower revenues and profitability. Using data and models from Idaho, a major purchaser of Montana seed, we estimate the annual benefit from Montana’s program to Idaho to average $205 per acre or $22 million for the state. [ ] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The potato is the third most important crop in the world, and more than 375 million metric tonnes of potatoes are produced globally on an annual basis. Potato Virus Y (PVY) poses a significant threat to the production of seed potatoes, resulting in economic losses and risks to food security. Current detection methods for PVY typically rely on serological assays for leaves and PCR for tubers; however, these processes are labor-intensive, time-consuming, and not scalable. In this proof-of-concept study, we propose the use of unmanned aerial vehicles (UAVs) integrated with hyperspectral cameras, including a downwelling irradiance sensor, to detect the PVY in commercial growers’ fields. We used a 400–1000 nm visible and near-infrared (Vis-NIR) hyperspectral camera and trained several standard machine learning and deep learning models with optimized hyperparameters on a curated dataset. The performance of the models is promising, with the convolutional neural network (CNN) achieving a recall of 0.831, reliably identifying the PVY-infected plants. Notably, UAV-based imaging maintained performance levels comparable to ground-based methods, supporting its practical viability. The hyperspectral camera captures a wide range of spectral bands, many of which are redundant in identifying the PVY. Our analysis identified five key spectral regions that are informative in identifying the PVY. Two of them are in the visible spectrum, two are in the near-infrared spectrum, and one is in the red-edge spectrum. This research shows that early-season PVY detection is feasible using UAV hyperspectral imaging, offering the potential to minimize economic and yield losses. It also highlights the most relevant spectral regions that carry the distinctive signatures of PVY. This research demonstrates the feasibility of early-season PVY detection using UAV hyperspectral imaging and provides guidance for developing cost-effective multispectral sensors tailored to this task.

Potato virus Y (PVY) infection is one of the greatest challenges to seed potato production in the United States. To determine how cultivar and seed type affect the development of systemic PVY infection, Russet Burbank and Russet Norkotah Colorado 3 cultivars were grown from two types of pre-nuclear seed (i.e., plantlets and minitubers) and Generation 3 (G3) tubers and challenged with PVY strain Wilga (PVY^N-Wi). Systemic PVY infection was measured by assaying spread of virus from the inoculation site to upper non-inoculated leaves. The Burbank cultivar had a lower incidence of systemic PVY infection compared to the incidence of systemic PVY that developed in the Colorado 3 cultivar. Furthermore, Burbank plants grown from G3 tubers had a lower incidence of systemic PVY infection, as compared to Burbank plants grown from plantlets. Together our results indicate that both cultivar and seed type affect the development of systemic PVY^N-Wi infections post-inoculation. La infección por virus Y (PVY) es uno de los mayores retos en la producción de semilla de papa en los Estados Unidos. Para determinar cómo afecta la variedad y el tipo de semilla al desarrollo de la infección sistémica de PVY, se cultivaron las variedades Russet Burbank y Russet Norkotah Colorado 3 de dos tipos de semilla pre-nuclear (p. e., plántulas y minitubérculos) y de tubérculos de la Generación 3 (G3), y se inocularon con PVY variante Wilga (PVYN-Wi). La infección sistémica de PVY se midió mediante la detección de la dispersión del virus desde el sitio de inoculación hacia las hojas superiores no inoculadas. La variedad Burbank tuvo la incidencia más baja de infección sistémica de PVY en comparación con la incidencia de PVY sistémico que se desarrolló en la variedad Colorado 3. Aún más, las plantas de Burbank originadas de los tubérculos de G3 tuvieron la incidencia más baja de infección sistémica de PVY, en comparación con las plantas de Burbank originadas de plántulas. Juntos, nuestros resultados indican que tanto la variedad como el tipo de semilla afectan el desarrollo de infecciones sistémicas de PVYN-Wi después de la inoculación.

Potato is the third major crop in the world and more than 375 million metric tonnes of potatoes are produced globally on an annual basis. Potato Virus Y (PVY) poses a significant threat to the production of seed potatoes thus resulting in a substantial economic loss and a threat to food security. The traditional approach uses serological assays to detect PVY in potato leaves and PCR is used to detect PVY in tubers, however, the processes are sophisticated, labor-intensive, and time-consuming. We propose to use Unmanned Aerial Vehicles (UAVs) integrated with hyperspectral cameras included with a downwelling irradiance spectrometer, to detect the PVY virus in commercial growers’ fields. We have used a 400-1000 nm visible and near-infrared (Vis-NIR) hyperspectral camera. We have trained several machine learning and deep learning models with optimized hyperparameters on the curated dataset. The performance of the models are very promising, and we found the convolutional neural network (CNN) is reliable in identifying the healthy plants (precision 0.980), and the feedforward neural neural network (FNN) is reliable in identifying the PVY-infected plants (recall 0.988). The hyperspectral camera provides a wide spectrum and most of them are redundant in identifying PVY. According to our analysis, five spectra regions are impactful in identifying the PVY. Two of them are in the visible spectrum, two in the near-infrared spectrum, and one in the red-edge spectrum. This research shows that PVY detection is possible in the early growing season minimizing the economic and yield losses, and identifies the most relevant spectra carrying the signatures of PVY.