Project is in support of PSI: The overarching goal of this project is to accelerate development of a scientifically-based and economically-sound cover crop seed industry. We expect this systems-oriented project will make improved cover crop varieties available to 250,000 American farmers who use cover crops to protect and improve soil on 50 million acres by 2030. Work from this project will contribute significantly to substantial growth in the U.S. cover crop seed industry, more than doubling in size to become a billion-dollar a year industry by the end of the decade. Objective 1. Accelerate cover crop germplasm improvements and seed yield potential to advance the U.S. cover crop seed industry. (S, M, L) Objective 2. Evaluate traits contributing to improved performance of cover crop cultivars (S, M) Objective 3. Establish a National Cover Crop Variety Trial Program to determine optimal regional adaptation of improved cultivars. (S, M)

The herbicide-resistant weeds epidemic is limiting U.S. chemical weed control options and increasing crop yield losses. U.S. Field crop producers need new precision technologies and nonchemical control practices to provide long-term herbicide resistant weed management. The overall goal of this project is to develop and regionally adapt precision Integrated Weed management systems for corn, soybean, and cotton producers.

building automated technologies and robotics to improve organic weed management

Cover crops are essential to the long-term sustainability of organic cropping systems because they suppress weeds, improve soil and water quality, supply nitrogen, and provide resources for beneficial organisms such as pollinators. Unlike cash crops, cover crops have not been bred for the traits that organic farmers need, and farmers have limited variety options and regional performance information. Our established team of organic and cover crop experts will expand a successful breeding and research program to include new cover crop species and address more traits of interest to organic growers. We will work with organic farmers and seed companies to breed new varieties of hairy vetch (Vicia villosa), winter pea (Pisum sativum), crimson clover (Trifolium incarnatum), and cereal rye (Secale cereale). Using classical breeding, marker-based selection, and participatory breeding, we will select varieties for agronomic traits of interest including weed suppression, early vigor, biomass production, winter hardiness, seed yield, disease and insect resistance, soft and non-shattering seed, and early flowering. Through release of new varieties and enhanced knowledge of regional cover crop adaptation, we will improve the ability of organic farmers to choose the cover crops best adapted to their region and cropping system. Our work directly addresses legislatively-defined OREI goals 1, 6, and 8 by facilitating development of organic production methods, conducting on-farm research, and developing new/improved seed varieties for organic systems. This project is unique because our network of research and farm sites ensures that our work is applicable across multiple regions, scales, and organic cropping systems.

Multiple herbicide-resistant (MHR) weeds are threatening production of key agricultural commodities (soybean, corn, cotton, etc.) by rendering valuable herbicides ineffective and increasing management costs. Due to MHR, farmers are increasingly relying on herbicide-tank mixes and reverting back to tillage as an important weed management method, jeopardizing the soil conservation gains made over the past couple of decades. MHR weeds represent one of the biggest threats to recent soil health gains. To effectively manage MHR weeds, farmers need to employ multiple control tactics in an integrated weed management (IWM) approach. Two such tactics that could aid in managing MHR weeds include cover crops (CCs) and site-specific control (SSC). Ground-based and aerial sensors as well as sophisticated computational image analyses are also proving to be a crucial precision control practice used to spot spray initial patches of resistant-weed biotypes. Our goal is to use these recent advancements to supplement CCs and SSCs for building precision IWM solutions and to further reduce unnecessary use of herbicides and tillage in farms. The objectives of this research are to 1) refine an algorithm that uses real-time RGB video to generate a 3-dimensional image of vegetation, 2) calibrate the system to quantify cover crop biomass and weed biomass based on volume, and 3) develop a risk-assessment model for excessive herbicide use and cultivation for weed control based on aerial and ground-based quantifications of cover crops and weed population at field, and watershed level.

Cover crops are capable of mitigating many of the destabilizing factors influencing food and water security including climate change, pesticide resistance, depleted soils, competition among users for water, and decoupled nutrient cycles. Despite the myriad potential landscape-level benefits, cover crop adoption rates remain low. Cover crop use is a knowledge-intensive activity; farmers repeatedly cite management complexity and the lack of site- and system-specific information as barriers to adoption. This is further complicated by inconsistent management recommendations, and at times misinformation, resulting from a lack of coordination, communication, and awareness. Complex interactions in food production among intrinsic factors (climate and soil), management, and genetics exacerbate the issue. Social and political forces also add complexity via regulation and market forces. While there has been considerable research devoted to cover crops, there has been a failure to link impacts of climate, soil, genetics, and management decisions on cover crop performance. There is also a lack of transdisciplinarity and integration in research, education, and extension activities. We propose a transformation of US cropping systems through an information ecology to integrate cover crops and precision agriculture. An information ecology for precision sustainable agriculture would include, at minimum, open source software to reduce the cognitive overload of cover crop use by farmers; low cost hardware to crowdsource farm-scale data to inform cover crop research; and a knowledge commons for data sharing among transdisciplinary and cross-sector teams. An information ecology therefore has the potential to support long-term sustainability of US agricultural systems through the integration of cover crop research and practice.

Brassica carinata A. Braun. (Abyssinian cabbage, Ethiopian mustard) is an oilseed crop with recognized potential as an advanced biofuel. The overall project evaluates specific aspects of its feasibility in several southeastern U.S. states (FL, AL, MS, GA, SC, and NC). North Carolina will conduct variety trial research during years 1 to 3 of the project, greenhouse growth studies during years 1 to 2 of the project, and field research evaluating nutrient critical levels during years 4 to 5 of the project. This work should identify the most promising genotypes, as well as specific nutrient needs for successful production.

The overall objective is to evaluate various tactics targeted outside of the traditional weed management window in cotton (planting to layby) to minimize seedbank addition potential and impact long-term population sizes. Given the regional-level importance in the US Cotton Belt, Palmer amaranth is the weed species targeted in this research.

This is an Extension Implementation Project (EIP). Our Program Priority Areas are IPM Implementation in: Agronomic Crops (28%), Communities (40%), Specialty Crops (24%), and Pollinator Health (8%). The person who will be responsible for grant coordination and budget management, and participation in the SERA3 meetings is Dr. Danesha Seth Carley, Director for the NSF Center for IPM and the Administrative contact is Dr. Rich Bonanno, Director of NC State Extension, and Associate Dean College of Agriculture and Life Sciences. Through NC Cooperative Extension programs and diverse transdisciplinary team collaboration, we work to sustain and enhance environmental stewardship, reduce economic risks for growers and consumers, and protect human health by applying integrated pest management (IPM) in all suitable situations. Our goal is to increase coordination and improve efficiency of translating IPM research to the scientific community and stakeholders; as well as the residents of NC through extension and outreach programs. By working to synergize efforts and leverage resources, we are better able to promote development and adoption of IPM through collaborative programs and broad-based stakeholder participation. With a strong team of experts and close association with our Evaluation Specialist, we are able to document the value of IPM strategies and programs, and provide comprehensive success stories of IPM integration across NC. Through the outputs and outcomes from this program, NC Extension agents and stakeholders will become more knowledgeable about IPM and develop the skills necessary to implement IPM strategies in Agronomic Crops, Specialty Crops, Pollinator Health, and IPM in the Communities.

Weed interference is the most important biotic problem in crop production. Despite major advances in weed management, growers continue to face substantial weed problems. Weeds have numerous undesirable effects, such as (a) lowering yield, (b) raising production costs, (c) lowering irrigation performance, and (d) acting as hosts and reservoirs for insect pests and pathogens. In recent years, ���������������omics' methods have been used to look for new targets for insecticides and fungicides. Genomics holds the potential for providing the information needed to develop RNA interference (RNAi) technology for weed management. Our long-term goal is to provide NC cotton growers with a robust, cost-effective, and sustainable integrated weed control system that combines conventional with innovative tools based on biotechnology and weed population dynamics. Towards this end, we propose three objectives: 1) to identify genetic targets for RNAi using sequencing analysis to reduce weed growth and fitness in cotton, 2) to design RNAi systems to silence target genes in Palmer amaranth, 3) to characterize the safety of those RNAi systems on cotton growth.