Cranos Williams

The Science and Technologies for Phosphorus Sustainability (STEPS) Center is a convergence research hub for addressing the fundamental challenges associated with phosphorus sustainability. The vision of STEPS is to develop new scientific and technological solutions to regulating, recovering and reusing phosphorus that can readily be adopted by society through fundamental research conducted by a broad, highly interdisciplinary team. Key outcomes include new atomic-level knowledge of phosphorus interactions with engineered and natural materials, new understanding of phosphorus mobility at industrial, farm, and landscape scales, and prioritization of best management practices and strategies drawn from diverse stakeholder perspectives. Ultimately, STEPS will provide new scientific understanding, enabling new technologies, and transformative improvements in phosphorus sustainability.

The Agricultural DECision Intelligence moDEling System for huMan-AI collaboRative acTion Elicitation and impRovement (DECIDE-SMARTER) project will lay the foundations of democratized access to Decision Intelligence (DI) technology for stakeholders across the agriculture value chain, filling a longstanding gap between technology and decision makers. Through a process of participatory design, the project team will work with stakeholders in the sweetpotato value chain to: 1) Create a software asset that helps growers with an otherwise difficult decision; 2) conduct experiments that inform the best software interfaces possible to support complex agricultural decision making (through characterizing, understanding, and leveraging human cognitive abilities; 3) identify potential sources of bias in the DI process that would present barriers to democratized access to the technology; and 4) develop a reference architecture and prototype implementation of a modeling, simulation, and visualization framework for implementing multiple DI models with agriculture stakeholders. The project will leverage the ongoing research, data acquisition, and stakeholder efforts by the Sweetpotato Analytics for Produce Provenance and Scanning (Sweet-APPS) team, a multi-disciplinary endeavor that aims to reduce agricultural waste and maximize yield for North Carolina������������������s sweet potato growers.

A Pipeline of a Resilient Workforce that integrates Advanced Analytics to the Agriculture, Food and Energy Supply Chain

At peanut buying stations across the U.S. South East, peanut grading is currently implemented using labor-intensive equipment. Many of the steps related to grading have been unchanged for decades. A critical reason for this involves political pressures against updating or expediting the grading process. However, like many other economic sectors, new labor-force pressures are requiring that more be done with fewer people. Given that (1) labor is more challenging to come by; and (2) political pressure exists to maintain the status quo, we propose to update key steps in the existing process to simplify and/or expedite data collection. This project���s goal is to develop automated imaging and weighing technologies that can serve as a bridge, toward more fully automated systems, by addressing key bottlenecks in the existing grading process. We will achieve this by the following objectives: (1) Automate the weighing and grading of peanuts either traveling down or entering the rollers during pod pre-sizing; and (2) Automate the detection of splits and, if possible, sound versus unsound splits, by adding vision systems to the existing sheller.

One of the grand challenges facing humanity is to secure sufficient and healthy food for the increasing world population. This requires maintaining sustainable cultivation of crop plants under changing climate conditions. Plant roots and soil microbes have been associated since the emergence of plants on land. Nevertheless, the mechanisms that coevolved to control and regulate microbiota associations with healthy plants are largely unexplored. The photosynthetically active green leaf tissues supply assimilated carbon to roots for development and also to feed its associated microbes. To maintain balanced growth, plants have to integrate this underground demand and regulate the rate of photosynthetic CO2 fixation, and sugar allocation needs to be coordinated between root and shoot. Research on plants and their naturally associated microorganisms is therefore in a prime position to provide new perspectives and concepts for understanding plant function, plant performance and plant growth under limited input conditions with a reduced environmental footprint and could also define breeding targets and develop microbial interventions. InRoot aims to: 1. Disentangle the effects of climate and soil type from the impact of root-microbe interactions through transplantation experiments and exploit natural variation to identify the plant genetic components responsible for adaptation to the local microbiota. 2. Identify key bacterial taxa governing the establishment of host-driven microbial networks in the rhizosphere by analysing the microbe-microbe and microbe-host interactions established in tailored synthetic communities (SynComs) with direct consequences on host performance. 3. Define the plant genetic components that control infection of plant roots by ubiquitous and host-specific endophytes using advanced genetic screens and new methods for quantifying root cellular responses to microbes 4. Understand molecular mechanisms integrating root-microbe interactions into whole-plant physiology by investigating systemic physiological responses induced by SynComs using whole plant phenotyping. 5. Predict plant performance as a function of plant and microbiota genotypes by building multiscale models based on genotype, phenotype, and mechanistic data thereby providing knowledge for application. InRoot perspective: Provide knowledge and tools for science-based development of new crop varieties and associated microbial interventions that will improve productivity, reduce the need for fertilizers and pesticides, and alleviate negative environmental impact.