Part Two of Field Phenomics: Data Analysis

Plant Breeding and Genomics November 13, 2013|Print
imageThis presentation describes how to handle data generated by a field-based sensor array.
This webinar is the second in a two part series on high throughput field phenotyping. This presentation describes how to handle data generated by a field-based sensor array. The video was recorded live as a webinar October 31, 2013.

 

Part 1

Part 2

Part 3

Full Recording

Software Links

QGIS: A Free and Open Source Geographic Information System

HTP Geoprocessor: A plugin for QGIS

ASReml: Data analysis software designed for fitting linear mixed models

PROSAIL: The combined PROSPECT leaf optical properties model and SAIL canopy bidirectional reflectance model

Presenters

Michael Gore is an associate professor of molecular breeding and genetics for nutritional quality at Cornell University in Ithaca, NY, where he is a member of the faculty in the Department of Plant Breeding and Genetics. He holds a BS and MS from Virginia Tech in Blacksburg, Virginia, and a PhD from Cornell University. Before joining the faculty at Cornell, he worked as a Research Geneticist with the USDA-ARS at the Arid-Land Agricultural Research Center in Maricopa, AZ. His expertise is in the field of quantitative genetics and genomics, especially the genetic dissection of metabolic traits. He has also contributed to the development and application of field-based, high-throughput phenotyping tools for plant breeding and genetics research. He teaches two short courses at the Tucson Winter Plant Breeding Institute in Tucson, Arizona, and serves on the editorial boards of Crop Science and Theoretical and Applied Genetics. His career accomplishments in plant breeding and genetics earned him the National Association of Plant Breeders Early Career Scientist Award in 2012 and the American Society of Plant Biologists Early Career Award in 2013. 

 

Kelly Thorp is a Research Agricultural Engineer with USDA-ARS in Maricopa, Arizona. He holds a BS and MS from the University of Illinois at Urbana-Champaign and a PhD from Iowa State University. His research focuses primarily on the development and application of informational technologies for monitoring cropping systems and understanding cropping system processes.  Areas of expertise include remote sensing, cropping system simulation modeling, and geographic information systems.  Application areas for these technologies include crop water and nitrogen status assessment, precision agriculture, management of nitrogen fertilizer, irrigation and drainage water management, field-based plant phenomics, and development of new bioenergy crops.  He serves as an associate editor for Transactions of the ASABE and Applied Engineering in Agriculture.

 

 

See Part 1: Developing and Using a Sensor Array

Related Publications

Andrade-Sanchez Pedro, Gore Michael A., Heun John T., Thorp Kelly R., Carmo-Silva A. Elizabete, French Andrew N., Salvucci Michael E., White Jeffrey W. (2013) Development and evaluation of a field-based high-throughput phenotyping platform. Functional Plant Biology.

A. Elizabete Carmo-Silva, Michael A. Gore, Pedro Andrade-Sanchez, Andrew N. French, Doug J. Hunsaker, Michael E. Salvucci (2012) Decreased CO2 availability and inactivation of Rubisco limit photosynthesis in cotton plants under heat and drought stress in the field. Environmental and Experimental Botany.83:1-11. ISSN 0098-8472, 10.1016/j.envexpbot.2012.04.001.

Jeffrey W. White, Pedro Andrade-Sanchez, Michael A. Gore, Kevin F. Bronson, Terry A. Coffelt, Matthew M. Conley, Kenneth A. Feldmann, Andrew N. French, John T. Heun, Douglas J. Hunsaker, Matthew A. Jenks, Bruce A. Kimball, Robert L. Roth, Robert J. Strand, Kelly R. Thorp, Gerard W. Wall, Guangyao Wang (2012) Field-based phenomics for plant genetics research. Field Crops Research, Volume 133: 101-112, ISSN 0378-4290, 10.1016/j.fcr.2012.04.003.

Thorp, K.R., Wang, G., West, A.L., Moran, M.S., Bronson, K.F., White, J.W., Mon, J.  2012.  Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models.  Remote Sensing of Environment. 124:224-233.

Jeffrey W. White, Pedro Andrade-Sanchez, Michael A. Gore, Kevin F. Bronson, Terry A. Coffelt, Matthew M. Conley, Kenneth A. Feldmann, Andrew N. French, John T. Heun, Douglas J. Hunsaker, Matthew A. Jenks, Bruce A. Kimball, Robert L. Roth, Robert J. Strand, Kelly R. Thorp, Gerard W. Wall, Guangyao Wang (2012) Field-based phenomics for plant genetics research. Field Crops Research, Volume 133: 101-112, ISSN 0378-4290, 10.1016/j.fcr.2012.04.003.

Recommended Reading

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Funding Statement

Development of this resource was supported in part by the National Institute of Food and Agriculture (NIFA) Solanaceae Coordinated Agricultural Project, and Dry Bean Root Health East Africa, Cotton Incorporated and United States Department of Agriculture – Agricultural Research Service (USDA-ARS).  Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the United States Department of Agriculture. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. The USDA is an equal opportunity provider and employer.

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