2020 Plant science symposium
DEADline extended:
general registration open until january 22
During this symposium we will explore i) how large datasets are collected, stored, curated, and analyzed, and ii) how results are utilized to answer meaningful research questions in both basic and applied fields.
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The symposium will feature several presentations by invited experts in phenomics, genomics, and big data analytics, as well as invited graduate students from other institutions.
speakers
Nadia Shakoor
Dr. Nadia Shakoor works at the intersection of plant genetics and breeding, high-throughput phenotyping, and computational analytics. As Senior Research Scientist at the Donald Danforth Plant Science Center, she serves as associate director of the DOE ARPA-E funded TERRA-REF project. Their team has successfully deployed the Lemnatec Field Scanalyzer—the world’s largest field crop analytics robot. Dr. Shakoor is also co-inventor of PheNode, a platform for collecting environmental and phenotypic data in the field. She now leads efforts to bring this technology to the market as co-founder and CEO of Agrela Ecosystems.
Donald Danforth Plant Science Center
Gustavo de los Campos
Dr. Gustavo de los Campos is a professor at Michigan State University, where he is Associate Chair and Director of Biostatistics. An expert in quantitative and statistical genetics, he has developed new models for the prediction of phenotypes using statistical learning methods. His contributions to this field include software for the analysis of complex traits using high-dimensional data including pedigree information and environmental variables as well as SNPs and other -omic data (R packages BLR and BGLR).
Michigan State University
Dr. Aline Zare is an Associate Professor of Electrical and Computer Engineering at the University of Florida. Her research interests include pattern recognition and machine learning, and their application to problems in agriculture, ecology, military defense, and other fields. Recent work includes the development of algorithms to analyze large plant phenotypic datasets. Valuable biological insights have been gleaned from diverse inputs including X-ray images of switchgrass roots, volatile compounds released by peanuts, and data captured using UAVs.
Alina Zare
University of Florida
Dr. Hannah Schneider is a postdoctoral scholar studying root architecture at Penn State University. She holds a PhD in Horticulture from Penn State and a B.S. in Applied Plant Science from the University of Minnesota. She has experience in MRI imaging, simulation modeling, phenotyping platform development, and field, greenhouse, and laboratory work to understand the function of root phenes and their relation to plant performance. Recent work includes understanding the functional role and genetic control of root plasticity in response to water stress.
Hannah Schneider
Pennsylvania State University
Ryan McCormick
Dr. Ryan McCormick is a Research Scientist in Predictive Ag at Corteva Agriscience focusing on the design and optimization of prediction methods in agriculture. After completing a Ph.D. in Genetics from Texas A&M University and a postdoc in Computational Biology at Oak Ridge National Laboratory, Ryan now works at the intersection of agriculture, computing, and modeling to improve the productivity and sustainability of growers. His research interests include statistical learning of dynamical systems, hybridization of knowledge-based and data-driven modeling approaches, and reinforcement learning.
Corteva Agriscience
Dr. Matt Hufford is an assistant professor in the Ecology, Evolution, and Organismal Biology Department at Iowa State University. Prior to joining the ISU faculty in 2013, he earned a PhD in Ecology with Dr. Paul Gepts, and later worked as a postdoctoral scholar with Dr. Jeffrey Ross-Ibarra, both at UC Davis. Hufford’s team at Iowa State now leverages genomic data to explore the ecology and evolution of crops and their wild relatives, specializing in the genus Zea (i.e. maize, teosintes).
Iowa State University
Matthew Hufford
Big data workshop
Decades of genomic data collection have resulted in robust software tools, methodologies, and analysis pipelines to and interpret large datasets, resulting in scientific discoveries (cloned genes, QTL, genetic markers, etc.). The rapid upsurge in sensor based phenomic technologies and broad scientific adoption has led to a demand for open-source data processing pipelines and FAIR (Findable, Accessible, Interoperable, and Re-usable) metadata. To date, most open-source image processing pipelines are custom scripts unique to each research objective. In this workshop we will discuss approaches to developing a data extraction pipeline for plant height from UAS image-based point clouds of maize.
Topics will cover ground control points, UAS image collection, image processing, data extraction, and application of UAS phenotypes within areas of statistical modeling and genetic mapping. The focus of the workshop will be to walk through how one may critically identify and combine the necessary processing steps within their own pipeline, past the image processing stage, to extract your phenotypes of interest. Having hands on experience extracting the meaningful information from a large dataset will give participants skills necessary to develop their own pipelines, create publicly available processing tools, and provide FAIR data to the research community.
During this symposium we will have a hands-on workshop where participants will learn about utilizing big data in their own research!
Workshop leaders
Matthew Gitzendanner
Dr. Matt Gitzendanner is a Scientist in the Biology Department at the University of Florida. His research focuses on plant evolutionary genomics and big data. In addition to managing the lab for Pam and Doug Soltis, he works ¼ time for Research computing where he manages the training program and supports researchers across campus in their use of HiPerGator.
University of Florida
Steven Anderson
Dr. Steve Anderson is a Postdoctoral Researcher in the Environmental Horticulture Department at the University of Florida. His research focuses on novel plant breeding approaches, high-throughput phenotyping, quantitative genetics, and statistical modeling. He currently leads the Industrial Hemp Pilot Project Research at MREC developing best management practices for upcoming hemp cultivation in Florida diverse environment. Dr. Anderson strives to be an innovative, dynamic leader advocating for improved support/funding of advancements in agricultural production and sustainability through implementation of new technologies, multi-disciplinary collaboration, and educational resources.
University of Florida
Apply now for a $500 graduate student travel award. Awardees will give an oral presentation at the Big Data in Plant Science Symposium!
Applications Closed.
Register now to participate in our poster competition at the Big Data in Plant Science Symposium!
Applications Closed.
