EAGER: Real-time measurement of sap-flow dynamics in sunflower via nuclear magnetic resonance
EAGER:通过核磁共振实时测量向日葵液流动力学
基本信息
- 批准号:1936376
- 负责人:
- 金额:$ 30万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-08-01 至 2022-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Water is a key component to our planet, particularly to sustain food production and support human existence. To use water judiciously at macro scales e.g., basins or watersheds, a thorough understanding of factors affecting water requirement at smaller scales e.g., individual plants, is required. At the plant scale, the main driver determining water need is transpiration from the leaves. The rate of water loss through leaves is directly linked to sap flow, defined as the rate at which water moves through the stem. The goal of this project is to develop a new technology using principles from physics, based on nuclear magnetic resonance (NMR), to accurately determine sap flow and how it changes in real-time in a plant stem under different environmental conditions. Unlike currently available equipment, the NMR tool is non-invasive and portable, which allows making in-situ measurements easy and handy. Results from the NMR tool will have broad impacts that are of societal relevance by filling a significant knowledge gap about water and nutrient transport in plants. Project personnel will be involved in on-campus activities and events to engage K-12 students and increase their knowledge regarding water management. Project PIs will work with underrepresented groups in science for the Advancement of Women in Science and Engineering (KAWSE) i.e., Girls Researching Our World (GROW) summer workshops focusing on the water use and new NMR technology. The NMR tool has the potential for commercialization and application to other food crops and plants to advance agricultural and ecosystem productivity. The sole phenomenon transporting water and nutrients from soil to leaves through roots and stem vascular tissues in plants is the highly-dynamic sap flow. Quantifying this extremely complex physiological process varying temporally and spatially has been a major challenge in crop science, due to the lack of a robust, non-invasive and portable system. Therefore, this project aims to (1) design and prototype a handy tool to accurately measure temporal variations of sap-flow dynamics in sunflower, and (2) test and validate nuclear magnetic resonance (NMR) as a useful and practical tool for characterizing sap flow in crop plants. A portable NMR tool will be designed using a combination of 3D finite-element simulation package and a non-dominated sorting genetic algorithm-II to optimize the magnets' arrays and coils. The optimally-designed NMR tool will be prototyped in the lab, and its magnetic field homogeneity and intensity will be experimentally validated. Furthermore, a narrow tube and two flow rates i.e., 1 and 100 (mg/s) will be used to fine-tune the NMR tool under steady-steady conditions. Sunflower plants will be maintained in state-of-the-art, walk-in growth chambers at 2, 3 and 4 kPa vapor pressure deficit levels. Plant water loss will be measured at high temporal frequency using a load cell and the mass-balance method. NMR velocimetry will be performed thrice daily at different growth stages until flowering to capture velocity distribution at short time intervals. Sap flow estimated via NMR will be compared with that determined by the mass-balance method.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.
水是我们星球的一个关键组成部分,特别是维持粮食生产和支持人类生存。在宏观尺度上明智地使用水,流域或集水区,彻底了解影响较小尺度水需求的因素,例如,个体植物是必需的。在植物尺度上,决定水分需求的主要驱动力是叶片的蒸腾作用。通过叶子的水分损失率与树液流直接相关,树液流被定义为水通过茎的速率。该项目的目标是开发一种基于核磁共振(NMR)的物理学原理的新技术,以准确确定树液流及其在不同环境条件下植物茎中的实时变化。与目前可用的设备不同,核磁共振工具是非侵入性的且便携式的,可以轻松便捷地进行原位测量。NMR工具的结果将产生广泛的影响,通过填补有关植物中水分和养分运输的重大知识空白,具有社会意义。项目人员将参与校园活动和活动,以吸引K-12学生,并增加他们对水资源管理的知识。PI项目将与科学界代表性不足的团体合作,促进妇女在科学和工程领域的地位,即,女孩研究我们的世界(GROW)夏季讲习班,重点是水的使用和新的核磁共振技术。NMR工具具有商业化的潜力,并可应用于其他粮食作物和植物,以提高农业和生态系统的生产力。在植物体内,通过根和茎的维管组织将水分和养分从土壤输送到叶片的唯一现象是高度动态的液流。由于缺乏一个强大的,非侵入性的和便携式的系统,量化这个极其复杂的生理过程在时间和空间上的变化一直是作物科学的一个主要挑战。因此,本项目的目的是(1)设计和原型一个方便的工具,以准确地测量向日葵液流动态的时间变化,和(2)测试和验证核磁共振(NMR)作为一个有用的和实用的工具来表征作物的液流。将三维有限元模拟软件包和非支配排序遗传算法-II相结合,设计一种便携式核磁共振仪器,以优化磁体阵列和线圈。优化设计的核磁共振仪器将在实验室中进行原型制作,其磁场均匀性和强度将通过实验验证。此外,窄管和两种流速,即,1和100(mg/s)将用于在稳态-稳态条件下微调NMR工具。将向日葵植物保持在2、3和4 kPa蒸汽压不足水平的最先进的步入式生长室中。植物水分损失将在高时间频率下使用称重传感器和质量平衡法进行测量。在开花之前的不同生长阶段,每天进行三次NMR测速,以短时间间隔捕获速度分布。通过核磁共振估计的树液流量将与质量平衡法确定的树液流量进行比较。该奖项反映了NSF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。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
On Design Challenges of Portable Nuclear Magnetic Resonance System
便携式核磁共振系统的设计挑战
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Mohsen Hosseinzadehtaher;Silvanus D'silva;Matthew Baker;Ritesh Kumar;Nathan Hein;Mohammad B. Shadmand;S.V. Krishna Jagadish;Behzad Ghanbarian
- 通讯作者:Behzad Ghanbarian
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Behzad Ghanbarian其他文献
A hybrid time series and physics-informed machine learning framework to predict soil water content
一种混合时间序列和基于物理知识的机器学习框架来预测土壤含水量
- DOI:
10.1016/j.engappai.2025.110105 - 发表时间:
2025-03-15 - 期刊:
- 影响因子:8.000
- 作者:
Amirsalar Bagheri;Andres Patrignani;Behzad Ghanbarian;Davood B. Pourkargar - 通讯作者:
Davood B. Pourkargar
Estimating the scale dependence of permeability at pore and core scales: Incorporating effects of porosity and finite size
估算孔隙和岩心尺度下渗透率的尺度依赖性:考虑孔隙度和有限尺寸的影响
- DOI:
10.1016/j.advwatres.2022.104123 - 发表时间:
2022-03-01 - 期刊:
- 影响因子:4.200
- 作者:
Behzad Ghanbarian - 通讯作者:
Behzad Ghanbarian
Refined assessment of biocrusts-induced changes in dryland soil water and heat fluxes during evaporation
蒸发过程中生物结皮诱导的旱地土壤水热通量变化的精细评估
- DOI:
10.1016/j.jhydrol.2025.133670 - 发表时间:
2025-11-01 - 期刊:
- 影响因子:6.300
- 作者:
Junru Chen;Shenglong Li;Behzad Ghanbarian;Bo Xiao - 通讯作者:
Bo Xiao
A new methodology for grouping and averaging capillary pressure curves for reservoir models
- DOI:
10.1016/j.engeos.2020.09.001 - 发表时间:
2021-01-01 - 期刊:
- 影响因子:
- 作者:
Abouzar Mirzaei-Paiaman;Behzad Ghanbarian - 通讯作者:
Behzad Ghanbarian
A new method for characterizing dynamic reservoir quality: Implications for quality maps in reservoir simulation and rock type classification
- DOI:
10.1016/j.petrol.2022.111049 - 发表时间:
2022-11-01 - 期刊:
- 影响因子:
- 作者:
Abouzar Mirzaei-Paiaman;Behzad Ghanbarian - 通讯作者:
Behzad Ghanbarian
Behzad Ghanbarian的其他文献
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