ERI: Crop-FIT: Technology to Support Integrated Wearable Fitness Trackers for Plants

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。未来为人类和牲畜生产足够食物的最有希望的战略是使农场在使用不可再生资源方面更有效率、更有利可图、更可持续。研究报告称，仅干旱胁迫就分别导致全球小麦和玉米减产的21%和40%。此外，农业占全球甲烷排放量的55%至60%，二氧化碳排放量的21%至25%，因此规划不周和不可持续的农业做法在很大程度上加剧了全球变暖。缺乏实时监测作物健康的能力仍然是同时减轻生产力损失和农业做法对环境的不利影响的主要限制因素之一。可穿戴医疗设备的发展一直是一个重要的推动力。然而，它们在植物中的应用仍大量未被探索。为此，该项目将开发新的可穿戴作物技术，可以监测植物激素水平(表示植物对环境的第一反应)，以及记录在环境胁迫(例如，干旱、高温和盐分胁迫)下植物组织的重塑。这项技术可能成为精准农业的关键工具，能够实时跟踪植物的适合性，直接造福于农业社会。从长远来看，该项目的发现将有助于设计出表现更好、耐受压力的作物品种，并制定按需灌溉计划，从而在提高产量的同时防止过度使用不可再生的农用化学品。该项目还将培训来自少数族裔背景的学生和生产者社区，了解传感器驱动的精准耕作的生产率优势。这项研究旨在设计、制造和验证集成的、原位的植物传感器，用于催化下一代作物工程和精准农业。实时监测作物参数对于实施即时干预措施以减轻生产力损失和不利环境影响至关重要。用于精准农业应用的传感器仅限于从天气条件、土壤属性或航空图像间接估计作物需求和健康问题，这些图像不能提供植物的化学特征，因此缺乏关于作物健康状况发生和发展的信息。因此，在精确和直接量化植物需求及其对环境条件的反应方面，存在着显著的知识差距。这项研究提出了一种整体解决方案，通过开发一种集成的、多路复用的茎传感器来原位和定量地分析四种关键的植物激素/次生代谢物，这表明植物对环境的第一反应。该装置由一组电化学传感器、集成的微流体和嵌入式平台中的数据处理组成，用于在线收集和监测汁液中的植物激素。该传感器将通过在非生物胁迫条件下生长的玉米进行验证，以(1)分析传感器的敏感性、选择性、稳健性以及对植物生长的影响，(2)通过多路传感阐明环境胁迫条件下植物激素之间的动态相关性，以及(3)利用这些数据流来区分热/干旱/盐分胁迫对植物的影响。这项研究的第二个重点是设计和模拟一种基于光子晶体的光纤束，用于活植物的实时根部内窥镜和光谱检查。这种首创的纤维束将在成像根区和实时监测根分泌物代谢物方面发挥关键作用。结合对特定组织(地上部和根部)代谢物的分析和破译动态组织重塑，将增强我们对整个植物代谢物梯度的基本了解，增强对根对应激源的实时适应(先前研究中仍未探索的问题)，并为新的作物育种战略指明道路。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The most promising strategy for producing enough food for humans and livestock in the future is to make farms more efficient, profitable, and sustainable in their use of nonrenewable resources. Studies report that drought stress alone yields up to 21% and 40% of global reductions in wheat and maize productions, respectively. In addition, agriculture accounts for 55 to 60% of methane emissions and 21 to 25% of carbon-di-oxide emissions globally, thus poorly planned and unsustainable agriculture practices contribute substantially to global warming. Lack of real-time monitoring capabilities of crop health remains one of the central limiting factors for simultaneously mitigating productivity losses and adverse environmental impacts of agriculture practices. There has been a significant thrust in the development of wearable medical devices. However, their applications remain heavily unexplored in plants. Toward this end, this project will develop new crop-wearable technologies that can monitor the levels of plant hormones (which denote a plant’s first response to its environment), as well as record plant tissue remodeling under environmental stressors (e.g., drought, heat, and salinity stresses). This technology could be a pivotal tool in precision farming enabling real-time tracking of the fitness of plants, with direct benefit to the agricultural society. The findings from this project will aid in engineering higher-performing, stress-tolerant crop cultivars and setting up on-demand irrigation schedules in the long run, thus preventing the over-application of nonrenewable agrochemicals while simultaneously increasing the production. This project will also train students from minority backgrounds and the producer community on the productivity advantages of sensors-driven precision farming.This research aims to design, fabricate, and validate integrated, in-situ plant sensors for catalyzing the next generation of crop engineering and precision farming. Real-time monitoring of crop parameters is crucial for implementing immediate interventions to mitigate productivity losses and adverse environmental impacts. Sensors for precision farming applications are limited to indirectly estimating crop needs and health issues from weather conditions, soil properties, or aerial imagery that do not provide chemical profiling in plants, thereby lacking information on the onset and progression of crop health conditions. Hence, there is a significant gap in knowledge regarding precisely and directly quantifying plant needs and their responses to environmental conditions. This research proposes a holistic solution to this problem by developing an integrated, multiplexed stem sensor for in-situ and quantitative profiling of four key phytohormones/secondary metabolites, which denote a plant’s first response to its environment. The device is comprised of an array of electrochemical sensors, integral microfluidics, and data processing in an embedded platform for in-situ collection and monitoring of phytohormones in sap. The sensor will be validated with maize grown under abiotic stress conditions to (1) analyze the sensor’s sensitivity, selectivity, robustness, and impact on plant growth, (2) elucidate the dynamic correlations between the phytohormones under environmental stress conditions through multiplexed sensing, and (3) harness these data streams to differentiate the impact of heat/drought/salinity stresses on plants. The second thrust of this research is to design and simulate a photonic crystal-based fiber-optic bundle for use in real-time root endoscopy and spectroscopy in living plants. This first-of-its-kind fiber bundle will be pivotal in imaging root zone and monitoring root exudate metabolites in real-time. The combined analysis of tissue-specific (shoot versus root) metabolites and deciphering the dynamic tissue remodeling will enhance our fundamental understanding of metabolite gradients across the whole plant, real-time adaptation of roots to stressors (questions that remain unexplored in previous studies) and illuminate a pathway for new crop breeding strategies.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.