Elizabeth Munch
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Associate Professor
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Recent Grants
Grant: Open
Harnessing the Data Revolution to Enable Predictive Multi-scale Modeling across STEM
Open Date: 2022-07-01
Close Date: 2027-06-30
Grant: Open
CAREER: Reeb graph learning: Classification, Clustering, and Embedding of Graphical Signatures
Open Date: 2022-05-01
Close Date: 2027-04-30
Grant: Close
Collaborative Research: AF: Medium: A Unified Framework for Geometric and Topological Signature-Based Shape Comparison
Open Date: 2021-06-01
Close Date: 2025-05-31
Grant: Close
AF: Small: Collaborative Research: Reeb graph flows: Metrics, Drawings, and Analysis
Open Date: 2019-10-01
Close Date: 2022-09-30
Grant: Close
Role of transport processes in formation of optimal microbial habitats and the root-microbe-soil carbon accrual continuum
Open Date: 2019-09-01
Close Date: 2024-08-31
Articles (11)
Persian walnuts ( Juglans regia L.) are the second most produced and consumed tree nut, with over 2.6 million metric tons produced in the 2022–2023 harvest cycle alone. The United States is the second largest producer, accounting for 25% of the total global supply. Nonetheless, producers face an ever‐growing demand in a more uncertain climate landscape, which requires effective and efficient walnut selection and breeding of new cultivars with increased kernel content and easy‐to‐open shells. Past and current efforts select for these traits using hand‐held calipers and eye‐based evaluations. Yet there is plenty of morphology that meets the eye but goes unmeasured, such as the volume of inner air or the convexity of the kernel. Here, we study the shape of walnut fruits based on X‐ray computed tomography three‐dimensional reconstructions. We compute 49 different morphological phenotypes for 1264 individual nuts comprising 149 accessions. These phenotypes are complemented by traits of breeding interest such as ease of kernel removal and kernel‐to‐nut weight ratio. Through allometric relationships, relative growth of one tissue to another, we identify possible biophysical constraints at play during development. We explore multiple correlations between all morphological and commercial traits and identify which morphological traits can explain the most variability of commercial traits. We show that using only volume‐ and thickness‐based traits, especially inner air content, we can successfully encode several of the commercial traits.
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2024
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2023
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2023
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2023
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2023
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2022
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2022
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2022
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2020
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2020
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2020
Collaborators (7)
Maike Buchin
Professor
Ruhr-Universität Bochum
Brittany Terese Fasy
Assistant Professor
Montana State University
Sarah Tymochko
Hedrick Assistant Adjunct Professor
University of California, Los Angeles
Michelle Quigley
Assistant Research Professor
Pennsylvania State University
Firas Khasawneh
Assistant Professor
Michigan State University
Daniel H. Chitwood
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Erin Chambers
Professor
Saint Louis University
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