Anna Locke

This project aims to begin addressing the North Carolina Soybean Producers Association���s priority to help growers evaluate AgTech on their operations by first incorporating unmanned aerial vehicles (UAVs) into the breeding program to estimate maturity. Not only will UAVs increase the speed and accuracy of data collection and accelerate variety release to meet the changing needs of growers, the best practices for UAV-based maturity estimates determined from this study can form the basis for growers looking to replace more traditional scouting on their operations for harvest aid (desiccant) application. Harvest aids are often used to remove any remaining green tissue to increase harvest efficiency and maintain seed quality. As the demand for early maturing varieties increases in North Carolina, one of the biggest challenges facing growers is timely harvest needed to prevent a decline in seed quality. However, application timing, based on maturity, is key to prevent crop damage and yield loss, and UAV-based maturity scouting could help address this issue. In this proposal we will determine if using a UAV can accurately estimate maturity by beginning on a research plot level to determine how well UAV-based maturity estimates compare to ground ratings. Furthermore, the most cost-effective camera and processing pipeline will be determined so that future grower equipment and software investment will be well-informed. Using the best practices developed, the project will scale to mid-sized research fields for additional evaluation and validation. The funding will be used to purchase UAV imagery processing software as well as to fund a graduate student that will lead the project. Overall, this research will determine whether UAVs can accurately estimate maturity and the best practices for doing so, both of which lay the groundwork for growers to use them on their own operations to assist in maturity scouting to aid their desiccant application decisions that protect seed quality and profits.

Heat stress reduces soybean yield and can affect market-critical traits like protein and oil concentration. Developing new, heat tolerant soybean varieties through conventional breeding strategies is extremely difficult, because of the logistical constraints inherent in conducting heat stress experiments. In a prior project supported in part by NCSPA, we used a strategy to identify protein markers, hereafter referred as phosphomarkers, that can be used for breeding heat-tolerant soybeans. We conducted growth chamber experiments and field experiments that measured agronomically relevant traits, including yield, protein concentration, and oil concentration, upon heat stress. In addition to the identified phosphomarkers, we now aim to complement this research to identify genetic markers, giving us a holistic view of heat stress responses in soybean. To this end, we will leverage the available leaf samples and perform transcriptomics to identify genes that regulate heat stress responses in heat-tolerant and heat-sensitive soybean genotypes. Using the tissue stored from experiments conducted in 2020 and 2021, we will measure gene expression, identify genes that are central to regulating heat stress tolerance, and link those genes with agronomic outcomes using machine learning-based analytical pipelines aimed at predicting causal-effect relationships.

More than a third of crop yields are currently lost due to abiotic and biotic stressors such as drought, pests, and disease. These stressors are expected to worsen in a warmer, drier future, resulting in crop yields further declining ~25%; however, breeding is only expected to rescue 7-15% of that loss [1]. The plant microbiome is a new avenue of plant management that may help fill this gap. All plants have fungi living inside their leaves (����������������foliar fungal endophytes���������������). This is an ancient and intimate relationship in which the fungi affect plant physiology, biotic and abiotic stress tolerance, and productivity. For example, some foliar fungi prevent or delay onset of major yield-limiting diseases caused by pathogens such as Fusarium head blight [2]. Foliar endophytes also reduce plant water loss by up to half and delay wilting by several weeks [3, 4]. Endophyte effects on plants occur via diverse genes and metabolites, including genes involved in stress responses and plant defense [5]. Genes and metabolites also predict how interactions in fungal consortia affect host stress responses, which is important for developing field inoculations [6]. Because newly emergent leaves lack fungi, endophytes are also an attractive target for manipulation (particularly compared to soils, where competition with the existing microbial community inhibits microbial additives). We propose to address the role of endophytic ����������������mycobiomes��������������� in stress tolerance of five North Carolina food, fiber, and fuel crops (corn, hemp, soybean, switchgrass, wheat), and to develop tools that can push this field beyond its current limits. Our major objectives (Fig. 1) are to: 1. Identify key microbiome scales to optimally manage endophytes 2. Determine fungal mechanisms via greenhouse tests, modeling, and genetic engineering 3. Build tools for field detection of endophytes 4. Understand the regulatory environment and engage diverse stakeholders Results of these objectives will allow us to make significant progress in both understanding the basic biology of plant-fungal interactions and managing those interactions in real-world settings. Our extension efforts will also bring these ideas to the broader community. Finally, we will also be well positioned to pursue several future research endeavors supported by federal granting agencies.

North Carolina soybeans are vulnerable to wet weather and flooding, especially in the Northeastern part of the state, where elevation is low and water tables are high. Excess water, whether it saturates the soil for long periods of time or stands deep enough to partially cover some leaves, will slow growth and reduce yields. Despite the threat that excess water poses for North Carolina, the search for NC-adapted flood tolerant soybean varieties began only 2016, through a North Carolina Soybean Producers Association (NCSPA)- and United Soybean Board(USB)-funded project. In that research, flood tolerant soybeans from the Delta and Mid-South regions were evaluated under flooding conditions at the Tidewater Research Station at Plymouth, NC. The 2017 crop is still in the field at Plymouth, but preliminary indications are that some of the Delta soybean types have flood tolerant properties. The goal of this proposal is to build on this early success and start the process of developing flood tolerant soybean varieties specifically for North Carolina farmers. The premise of this work is that we will use desirable soy materials from the Delta as parents, but we must breed them with NC varieties and then evaluate progeny under NC conditions to get the local adaptation required for on farm success. This research project will achieve the goal of jump starting a soybean breeding program for flood tolerance through four objectives. Objective 1 will identify soybeans with tolerance to short-term (~one week) standing water before flowering. Objective 2 will identify soybeans with tolerance to long-term soil saturation, or waterlogging. Objective 3 will use the outcomes of Objectives 1 and 2 to establish a breeding program for North Carolina flood tolerant soybean. Objective 4 will begin to uncover the phyioslogical basis of flood tolerance, which will aid breeders in identifying and selecting the best germplasm. All experiments will be carried out at the Tidewater Research Station. Partial submergence and waterlogging will be created by building berms around experimental fields and pumping in the appropriate amount of water from the adjacent irrigation canals. Ultimately, this project will directly impact the soybean industry by generating flood tolerant soybean varieties specifically for North Carolina soybean farmers.

The overarching goal of this project is to increase soybean protein production in non-optimal environmental conditions. Soybean is grown on over 120 million ha worldwide, from which over 179 billion kg of protein-rich soybean meal per year is produced for livestock feed (FAO). Demand for soybean protein is increasing rapidly as the global population approaches 9 billion and more people can afford diversified diets that include meat. To meet this growing nutritional demand and to keep food prices stable, soybean protein production needs to be resilient to unpredictable growing-season weather, especially temperature stress. Temperature stressed soybean plants show low germination rates, growth delay, and reduced photosynthesis, yield, and seed protein production. Temperature stress-tolerant crops are difficult to develop through conventional breeding, due to the logistical difficulty of screening large numbers of plants for temperature stress response at critical developmental stages, which makes strategies such as genome-wide association studies (GWAS) and quantitative trait loci (QTL) mapping impractical or impossible. Furthermore, many temperature stress responses are regulated post-translationally and are thus difficult to detect with conventional genetic markers. To improve crop temperature stress tolerance, novel strategies are needed to identify key temperatures stress regulators and develop new biomarkers for use in crop breeding. This multidisciplinary team will use state-of-the-art phosphoproteomics analysis, genotypic data, and physiological information together with machine learning to link key post-translational regulators with the desired physiological and agronomic outcomes, i.e. stable germination and increased yield and protein production during temperature stress. These key post-translational, phosphoprotein regulators can be used in breeding programs as novel biomarkers, or phosphomarkers, to select genotypes that are primed for temperature stress tolerance.