Planning Grant: Engineering Research Center for Rapid Innovations in SystEms Engineering and Agricultural Sustainability (RiseEnAg)

工程研究中心规划拨款竞赛是ERC项目的试点征集。规划补助金不需要作为ERC竞赛的一部分，但它旨在在团队之间建立能力，以规划聚合的、中心规模的工程研究。预计到2050年全球人口将增加到90亿，这将对我们为世界人口生产足够粮食的能力构成重大挑战。阻碍我们满足世界粮食安全需求的具体挑战包括：1)我们无法以战略方式感知和量化跨尺度的环境和植物内的物理和化学变量；2)缺乏可扩展的数据分析和多尺度模型，无法将跨多个尺度的并发数据集转化为提高作物产量和减少作物损失的决策策略；3)缺乏有效集成异构数据的智能数据网络基础设施，支持复杂的多尺度生物模型的发展。该计划拨款将用于支持系统工程和农业可持续性快速创新工程研究中心提案（RiseEnAg）的发展。拟议中的工程研究中心将通过三个协同研究重点，利用融合研究来加速植物传感器开发、数据分析和数据集成方面的工程创新：1)传感器开发、校准和集成；2)数据挖掘、机器学习和多尺度建模；3)数据管理和综合网络基础设施。表型试验台将用于诱导复杂的生长条件和监测生物和化学反应。这些“发现工具”将通过将作物和土壤健康的实时知识以及对生物尺度关系的进一步了解转化为可操作的策略来解决当今种植者面临的挑战，从而提高作物田间性能，延长收获后寿命，并最大限度地减少收获后生物量损失。RiseEnAg工程研究中心的目标是针对一个复杂的重大挑战（食品安全），并定义融合了解决这一挑战所需的工程和生物科学的思想、方法和技术的研究空间。RiseEnAg融合工程研究中心的目标是建立工程系统平台，集成先进的传感器、数据分析和表型测试平台，以解决利益相关者(如种植者、研究人员和工业)挑战并加速研究，以实现21世纪增加粮食安全的目标。RiseEnAg将通过三个综合研究重点开发实现这一目标所需的工程工具。研究重点1（传感器开发，校准和集成）将开发和使用传感器来监测植物内和环境中的物理，化学，生化和分子参数，包括对植物性能至关重要的根际微生物-化学相互作用组。研究重点2（数据挖掘、机器学习和多尺度建模）将开发可扩展的建模和机器学习算法，用于制定综合植物分析和为种植者建立决策支持系统。研究重点3（数据管理和综合网络基础设施）将开发一个健壮、适应性强、可扩展的框架，用于存储、访问和分析异构生物数据集。高通量表型植物生长试验台将用于诱导复杂的生长条件，并监测植物内和土壤中的生物和化学反应。这些试验台将加速识别新的生物和环境目标，当单独或组合操作时，可以在不同的生长条件下产生期望的性能结果。通过规划拨款分配的资金将提供所需的资源：1)探索和确定所有利益相关者面临的独特和共同的挑战，如果这些挑战得到解决，将加速我们实现农业可持续发展的共同目标；2)确定有助于解决这些问题的新工程领域，并针对需要创新的潜在障碍。3)概述CERC其余三个基本组成部分（工程劳动力发展、创新生态系统和包容文化）的具体目标；4)制定CERC最终提案的工作草案。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The Planning Grants for Engineering Research Centers competition was run as a pilot solicitation within the ERC program. Planning grants are not required as part of the full ERC competition, but intended to build capacity among teams to plan for convergent, center-scale engineering research.The projected global increase to 9 billion people by the year 2050 will impose significant challenges on our ability to produce enough food for the world's population. Specific challenges that hinder our ability to meet the world's food security needs include: 1) our inability to sense and quantify, in a strategic way, physical and chemical variables in the environment and in-planta across scales; 2) the lack of scalable data analytics and multi-scale models that transform concurrent datasets across multiple scales into decision making strategies for improving crop yield and minimizing crop loss; and 3) the lack of intelligent data cyber-infrastructures that efficiently integrate heterogeneous data, supporting the development of complex multi-scale biological models. This planning grant will be used to support the development of an Engineering Research Center Proposal on Rapid Innovations in SystEms Engineering and Agricultural Sustainability (RiseEnAg). The proposed Engineering Research Center will use convergent research to accelerate engineering innovation in plant sensor development, data analytics, and data integration via three synergistic research thrusts: 1) Sensor Development, Calibration, and Integration; 2) Data Mining, Machine Learning, and Multi-scale Modeling; and 3) Data Management and Integrative Cyberinfrastructures. Phenotyping testbeds will be engineered to induce complex growth conditions and monitor biological and chemical responses. These "tools of discovery" will address the challenges of today's growers by translating real-time knowledge of crop and soil health and an increased understanding of relationships across the biological scale, into actionable strategies that advance crop field performance, increase post-harvesting longevity, and minimize post- harvest biomass loss. The RiseEnAg Engineering Research Center will aim to target a complex grand challenge (food security) and defines the convergent space of research that merges the ideas, approaches, and technologies from engineering and the biological sciences needed to address it The goal of the RiseEnAg convergent engineering research center is to establish engineered systems platforms that integrate advanced sensors, data analytics, and phenotyping testbeds that address stakeholder (e.g. growers, researchers, and industry) challenges and accelerate research towards the goal of increased food security in the 21st century. RiseEnAg will develop the engineering tools needed to achieve this goal via three integrated research thrusts. Research Thrust 1 (Sensor Development, Calibration, and Integration) will develop and employ sensors for monitoring physical, chemical, biochemical, and molecular parameters, both in-planta and in the environment, to include rhizosphere microbiota-chemical interactomes that are key to plant performance. Research Thrust 2 (Data Mining, Machine Learning, and Multiscale Modeling) will develop scalable modeling and machine learning algorithms for formulating integrative plant analytics and building decision support systems for growers. Research Thrust 3 (Data Management and Integrative Cyberinfrastructures) will develop a robust, adaptable, and scalable framework for storing, accessing, and analyzing heterogeneous biological datasets. High-throughput phenotyping plant growth testbeds will be engineered to induce complex growth conditions and monitor biological and chemical responses in-planta and in the soil. These testbeds will accelerate the identification of novel biological and environmental targets that, when manipulated individually or in combination, can produce the desired performance outcomes under diverse growth conditions. Funds allocated via this planning grant will provide the resources needed to 1) explore and identify unique and common challenges across all stakeholders that, if addressed, accelerate us toward the common goal of agricultural sustainability, 2) identify novel areas of engineering that can contribute to addressing these problems and target potential roadblocks where innovation is needed, 3) outline specific goals for the remaining three fundamental components of the CERC (Engineering Workforce Development, Innovation Ecosystem, and Culture of Inclusion), and 4) formulate working draft of the final CERC proposal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.