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aerial vehicle (UAV) imagery collection and processing, deep learning methods, and rangeland vegetation communities in Oregon and Idaho as part of an interdisciplinary team including researchers in plant
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architecture trait identification. The overall objectives of the project include: Deep understanding of plant water relations to extreme environmental stresses. Hands-on experience in measuring leaf gas exchange
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/moisture retention in soils, reducing soil compaction, attracting pollinators, etc., but the overall impact of cover crops on rootzone soil moisture availability and deep percolation is not well understood
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within the digital twin environment Developing deep learning architectures for time-series forecasting, anomaly detection, and predictive maintenance of the physical asset Designing and training Physics