SBIR Phase I: CAS: Tree Root Quality Inspection System with Noninvasive Evaluation

SBIR 第一阶段：CAS：带无创评估的树根质量检测系统

• 批准号: 2333948
• 负责人: Marie Ambusk
• 金额: $ 27.5万
• 依托单位: TREES ROI LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2333948&HistoricalAwards=false
• 关键词: SBIR; Phase; CAS; Tree; Root

This Small Business Innovation Research (SBIR) Phase I project improves the quality, value, benefits, and life span of nursery stock trees, so they will grow and thrive in the landscape where people live. Trees, with their myriad benefits for human health, ecosystem services, and climate mitigation achieve their full potential when they thrive long term. Current methods fail to adequately address tree root quality. By modernizing root inspection, this technology will not only improve industry standards and boost economic competitiveness, but also promote environmental stewardship on a global scale. With this technology, arborists and growers may be able to identify above-ground tree root defects and take corrective action to promote good quality root systems that are needed for these important tree assets to grow to maturity. This SBIR Phase I project focuses on the development of a 3-dimensional, non-destructive, ground penetrating radar (GPR) computed tomography (CT) system with cutting-edge software analytics to inspect and assess the quality of container-grown root systems in nursery stock trees. This innovation is based on the understanding that the GPR signals are generated by the large differentials between live tissues and the surrounding soil. The technology detects serious root system defects that could cause early tree mortality if not corrected before the tree is planted. The data will be collected with the help of an innovative apparatus designed to seamlessly capture 3D root data from container-grown trees using a commercial GPR system with a wireless antenna that works as a secondary layer around the container, emulating the precision of an X-ray CT scanner. A novel root quality classification model will inform the development of a root analysis software program to build an initial GPR dataset for the machine learning model and subsequently to adopt an active learning approach. Initial experiments will focus on a sufficiently large number of one or two species of trees.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.

这个小型企业创新研究 (SBIR) 第一阶段项目提高了苗木的质量、价值、效益和寿命，使它们能够在人们居住的景观中生长和繁盛。树木对人类健康、生态系统服务和减缓气候变化有着无数的好处，当它们长期繁衍生息时，它们就能充分发挥其潜力。当前的方法无法充分解决树根质量问题。通过使根部检查现代化，该技术不仅可以提高行业标准并提高经济竞争力，还可以在全球范围内促进环境管理。借助这项技术，树艺家和种植者可以识别地上树根缺陷并采取纠正措施，以促进这些重要的树木资产生长成熟所需的优质根系。 该 SBIR 第一阶段项目的重点是开发 3 维、无损、探地雷达 (GPR) 计算机断层扫描 (CT) 系统，该系统具有尖端的软件分析功能，可检查和评估容器种植根系的质量苗木树木。这项创新基于这样的理解：探地雷达信号是由活体组织与周围土壤之间的巨大差异产生的。该技术可以检测严重的根系缺陷，如果在种植树木之前不加以纠正，可能会导致树木早期死亡。数据将在创新设备的帮助下收集，该设备旨在使用商业 GPR 系统从容器种植的树木无缝捕获 3D 根数据，该系统带有无线天线，作为容器周围的第二层，模拟 X- 的精度。射线 CT 扫描仪。一种新颖的根质量分类模型将为根分析软件程序的开发提供信息，以便为机器学习模型构建初始 GPR 数据集，并随后采用主动学习方法。最初的实验将集中在足够数量的一种或两种树木上。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。