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Study of In-plant Sensing for the Precise Control of Water Use in Agriculture

dc.contributor.authorGao, Rui
dc.contributor.chairStroock, Abraham Duncan
dc.contributor.committeeMemberYou, Fengqi
dc.contributor.committeeMemberCheng, Lailiang
dc.date.accessioned2021-03-15T13:40:59Z
dc.date.available2021-03-15T13:40:59Z
dc.date.issued2020-12
dc.description134 pages
dc.description.abstractClimate change in recent years has induced extreme weather conditions that negatively impact food production and cause increased crop losses. As the world population grows, there is an emerging need to make agriculture more robust, efficient and productive. Understanding the plant dynamics becomes more important than ever for enhancing the agricultural water use efficiency (WUE), a key factor in shaping long-term agricultural development. Plant water stress is dynamic, resulting from rapid changes in evapotranspiration (ET) due to coupling to the atmosphere and slow changes in water availability due to soil dehydration. Stem water potential (SWP) integrates the water stress across the soil-plant-atmosphere-continuum (SPAC) and is therefore useful for scheduling plant-based precision irrigation. The micro-tensiometer (µTM) can provide valuable physiological information about a plant's drought response by monitoring the plant's ability to manage its water needs when facing environmental stress. With its continuous and real-time measurements, the µTM opens up a new opportunity to investigate system control strategies for improving WUE. In this thesis, we study the possibility of integrating the µTM within a water stress monitoring feedback framework for controlled water delivery to important fruit crops such as apple. We present our exploration of plants' responses to well-controlled irrigation events. We discover that the transient of root water uptake is likely to change after the growing season, resulting in increased sensitivity to daytime (more stressed state) rewatering. Additionally, we find that the plant and the soil become more decoupled as dehydration proceeds, resulting in persistent disequilibrium. The acquired data will be used to continue refining the existing hydraulic circuit models of apple under drought stress, thus finalizing a virtual representation of this speciality crop, or “digital twin”. The combination of the µTM and the model provides a valuable tool to reveal the full dynamics behind plant water stress and better agricultural water management across different phenological stages.
dc.identifier.doihttps://doi.org/10.7298/sppd-d402
dc.identifier.otherGao_cornell_0058O_11118
dc.identifier.otherhttp://dissertations.umi.com/cornell:11118
dc.identifier.urihttps://hdl.handle.net/1813/103404
dc.language.isoen
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectCircuit Model
dc.subjectControl
dc.subjectIrrigation Management
dc.subjectMicro-Tensiometer
dc.subjectPlant Water Relations
dc.subjectSoil-Plant-Atmosphere Continuum
dc.titleStudy of In-plant Sensing for the Precise Control of Water Use in Agriculture
dc.typedissertation or thesis
dcterms.licensehttps://hdl.handle.net/1813/59810
thesis.degree.disciplineChemical Engineering
thesis.degree.grantorCornell University
thesis.degree.levelMaster of Science
thesis.degree.nameM.S., Chemical Engineering

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