Peter Ojiambo

The objective of this research is to phenotype advanced wheat and barley lines and cultivars from the eastern U.S. for resistance to several diseases of economic importance. The experiments are conducted to further development and release of cultivars with resistance to these diseases, which include Fusarium head blight (FHB), Septoria nodorum blotch (SNB), Cereal yellow dwarf virus (CYDV), and Pythium root rot.

Quantitative disease resistance (QDR) is the most important form of resistance used in maize and by crops in general. Prior work by our research team and many others has shown that QDR is based on a large variety of genes and mechanisms, most of which are still poorly understood (if at all). We have identified and characterized a number of QTL and genes associated with resistance to multiple maize diseases. We have also developed and characterized two large maize populations that are ideal for the genetic dissection of quantitative traits, QDR in particular. This proposal is aimed at exploiting these these resources and data to extend our knowledge of QDR, focusing on (a) underlying mechanisms of QDR and (b) QDR associations with and effects on other traits. we will focus on four fungal diseases that are among the most important diseases of maize in the US and worldwide; the foliar blights, southern leaf blight (SLB) and northern leaf blight (NLB) and the ear rots Fusarium ear rot (FER) and Gibberella ear rot (GER). Both ear rots additionally produce mycotoxins that harm livestock and human health and cause seedling blights that lead to significant crop losses.

This Research project will assess the effectiveness of risk models in scheduling fungicides for disease control and conduct an economic analysis of the benefits of using models in fungicide application. The outcome will the development of a decision support system to manage cucurbit downy mildew and develop improved IPM practices that will prolong the efficacy of available fungicides. The United States grows 283,000 acres of cucurbits valued at $1.3 billion. In 2004-2005, a resurgence of cucurbit downy mildew in the United States devastated cucurbit crops nationwide. Since then, disease control has relied heavily on fungicides. However, fungicides that seemed effective a few years ago are now less effective. Growers are now using fewer active ingredients more frequently, which increases selection pressure on the cucurbit downy mildew pathogen P. cubensis, to develop resistance. In this project, we will: 1. Assess the effectiveness of within-season risk models in tailoring fungicide application against downy mildew, 2. Link disease risk to fungicide mode of action, post infection activity and fungicide decay to improve fungicide efficacy against downy mildew and 3. Conduct an economic analyses of within-season risk models to establish their usefulness in downy mildew control. The proposed research will be conducted using cucumber, muskmelon and zucchini in field and lab experiments in North Carolina, South Carolina and Oregon. The project outcomes will be a thorough assessment of fungicide resistance management programs and characterization of the pathogen population and an assessment of production of oospores on disease initiation and impact on fungicide resistance. Rational fungicide programs will be developed and disseminated through the CDM ipmPIPE, to manage the disease and fungicide resistance simultaneously. The impacts of this project will be improved environmental and economic management of cucurbit downy mildew and increased adoption of IPM practices by cucurbit growers.

OFSP is the most widely disseminated vitamin-A rich biofortified crop. A consistent, year-round supply of quality roots is critical to expanding availability of OFSP and derived products, especially to urban consumers. NC State will work identify a sustainable, economically advantageous, solar powered, cold storage system to handle two commodities that can be used for OFSP roots (for processing into puree and fresh root use), and onions. The cold storage will be flexible to handle both local and imported agricultural products. The intention is to determine and establish the economic viability of small solar-powered containers to facilitate a year-round supply of root crops. NC State will work in collaboration with the USDA/FAS, the International Potato Center (CIP) and other Kenyan partners, such as the Kenyan government and other stakeholders in the Kenya Home Grown School Meals Program (HGSMP). NC State will obtain, install, and instruct Kenyan partners (i.e. the Ministry of Agriculture and a farmers organization) in their operation, analysis of pertinent value chains, and interpretation of findings. The solar cold storage containers are expected to help strengthen local market systems (including producers, processors and traders) for root crops by reducing losses from decay, reducing energy costs, and improving nutrition by increasing access to and the use of various high quality, nutritious, and culturally appropriate foods in school meals.

The objectives of the cooperative research between North Carolina State University and the USDA Agricultural Research Service is to screen advanced wheat and barley breeding materials for resistance to diseases such as Fusarium head blight (FHB) and Septoria nodorum blothc (SNB), provide data to breeding eastern-U.S. cereal breeding programs, and produce data on efficacy and timing of fungicides for reduction of Fusarium head blight in wheat and barley, comparing new fungicide products with proven standard products at various cereal growth stages.

Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world and in the US. Climate change is exacerbating weather events that affect crop production and food access for vulnerable areas. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover and evolution of new pathogen genetic lineages. Prediction of plant disease pandemics is unreliable due to the lack of real-time detection, surveillance and data analytics to inform decisions and prevent spread. In order to tackle these grand challenges, a new set of predictive tools are needed. In the PIPP Phase I project, our multidisciplinary team will develop a pandemic prediction system called ????????????????Plant Aid Database (PAdb)??????????????? that links pathogen transmission biology, disease detection by in-situ and remote sensing, genomics of emerging pathogen strains and real-time spatial and temporal data analytics and predictive simulations to prevent pandemics. We plan to validate the PAdb using several model pathogens including novel and host resistance breaking strains of lineages of two Phytophthora species, Phytophthora infestans and P. ramorum and the cucurbit downy mildew pathogen Pseudoperonspora cubensis Adoption of new technologies and mitigation interventions to stop pandemics require acceptance by society. In our work, we will also characterize how human attitudes and social behavior impact disease transmission and adoption of surveillance and sensor technologies by engaging a broad group of stakeholders including growers, extension specialist, the USDA APHIS, Department of Homeland Security and the National Plant Diagnostic Network in a Biosecurity Preparedness workshop. This convergence science team will develop tools that help mitigate future plant disease pandemics using predictive intelligence. The tools and data can help stakeholders prevent spread from initial source populations before pandemics occur and are broadly applicable to animal and human pandemic research.

Epidemic invasions have substantial impacts on both ecosystem function and human welfare (1,16,31,67,91), and may become more frequent owing to globalization (116). Understanding the establishment and spread of such diseases can contribute significantly to identifying appropriate disease control strategies (35,96,115). Pathogens demonstrating long-distance dispersal (LDD) are of particular concern, owing to their potential to rapidly spread over large spatial scales. This includes pathogens with propagules that have the potential for long-distance transport through air, such as foot-and-mouth disease (FMD) (60), West Nile Virus (90), avian influenza (62), white-nose syndrome of bats (4) and many diseases of plants (8), through water, such as Aspergillosis of coral (134), and perhaps also pathogens spread through human transport systems, such as influenza (66) and Ebola virus (40). Bird migration can result in fat-tailed, LDD dispersal patterns, with dispersal over hundreds or thousands of kilometers (95,130). Similarly, "anomalous diffusion" has been suggested to result in fat-tailed distributions and superdiffusive spread of a range of organisms (6,131). Developing effective models for such large-scale processes remains a challenge, and will likely require a range of approaches and comparative studies encompassing a diversity of pathogens and hosts.

The United States (U.S.) is the second largest producer of pome fruit [apples (Malus x domestica) and pears (Pyrus communis)] globally. Producing 11 billion pounds of apples and 1.5 billion pounds of pears (NASS 2018), the US apple and pear crop is estimated at more than $4 billion (NASS 2017) with more than $7.5 billion in economic impact. With more than 18,815 apple and 10,246 pear farms nationally (NASS 2012) and 39,340 direct jobs (orchard to packing) in Washington alone, the apple and pear industry is an important contributor to jobs as well as the economy. Fire blight is the most devastating disease of pome fruit, and other fruit and ornamental plants of the Rosaceae family, and causes significant economic losses nationally. The actual costs incurred by growers and nurseries from fire blight losses and management efforts is difficult to estimate, due to costs of multiple sprays, tree losses, labor for pruning, removal of infected branches, fruit loss due to decreased quality, and the multi-year impact of lost tree productivity. In the U.S., fire blight is estimated to cause losses exceeding $100 million annually through blossom, shoot, and rootstock blight phase of the disease. In 2000, an epidemic of fire blight in Michigan led to loss of more than 600 acres of orchards (about 20% of the acreage in the region), and resulted in the death of 400,000 trees and over $50 million in economic losses to growers. The 2018 fire blight outbreak in Washington State caused an estimated 5% loss of total production of apple and pear, which translates to a loss of more than $100 million. Results of an online survey we conducted in Fall 2018 revealed that approximately 25% of 200 grower respondents had suffered significant fire blight infections in the last five years, leading to removal of more than 1,000 trees/per farm. Additionally, 23% of respondents estimated annual losses to fire blight at ~$4,000/acre and 46% of respondents lost ~$1,000/acre. Increased replanting costs of high-density blocks and losses of market accessibility due to stringent quarantine and international trade regulations associated with fire blight have resulted in financial costs and lost opportunities for many apple and pear growers. Our goal is to develop the following products through this project:1) Develop novel prescriptive approaches for blossom and shoot blight that increase precision in fire blight management; 2)Determine the impact of E. amylovora strain virulence on systemicmovement within trees, and develop detection methods for virulence typing to guide management decisions; 3)Develop apple pre-breeding lines with improved fire blight resistance and fruit quality traits using rapid cycle marker-assisted selection; 4)To develop bioeconomic models to identify profit maximizing and risk minimizing fire blight management strategies; and 5) To develop and deliver extension programming incorporating researchbased information to improve orchardist knowledge and application of effective fire blight management strategies.

We propose to develop new methods for tracking the spread of plant pathogens through agricultural landscapes using population genetic data. Because plant pathogens spread across complex landscapes, our approach will build on network models from spatial epidemiology that provide the flexibility needed to track epidemic dynamics across multiple scales and locations. Network models will be combined with phylogenetic approaches for estimating spatial spread based on the genetic relatedness of pathogens sampled at different geographic locations. These methods will then be implemented in high-performance, user-friendly software for analysis and web-based visualization. We aplan to apply our approach to study the spatial epidemic dynamics to three crop pathogens of major economic importance: Barley yellow dwarf virus, the aflatoxin-producing mold Aspergillus flavus and the downy mildew Pseudoperonospora cubensis. By synthesizing advances in spatial epidemiology and population genetics, our approach will provide next-generation software tools that will help reveal the dominant pathways by which these pathogens spread and identify major geographic sources that future control strategies can target.

Prior to registration for use on specific crops, candidate fungicide products need to undergo a series of tests to identify important efficacy parameters such as the minimum inhibitory concentration and the baseline sensitivity of the pathogen population. The minimum inhibitory concentration, defined as the lowest concentration above which no disease was observed, is important in establishing the discriminatory dosage for product testing. On the other hand, baseline sensitivity of the pathogen population not exposed to the product is useful in determining whether resistance has developed in subsequent pathogen populations. Both the minimum inhibitory concentration and the baseline sensitivity of P. cubensis populations in the US have not been established for the new OSBP product fluoxapiprolin. In addition, it would be useful to determine if any cross resistance with this product and other oomycete fungicides such as fluopicolide and propamocarb exists within the pathogen population.