Project Summaries

12-226  Project Manager: E. M. Barnes


Andrew N. French and Michael Gore, USDA-ARS; Pedro Andrade-Sanchez, University of Arizona.

The long-term sustainability of the cotton industry in the Southwest U.S. is in peril from regional climate change effects and increasing competition for scarce water resources from growing urban areas. Addressing these threats necessarily includes the development of genetically diverse, high-yielding, heat and drought tolerant cotton varieties. To accomplish this, ways are needed to improve the identification of superior genetic characteristics through field-based phenotyping.

Since 2010, our groups, USDA-ARS and University of Arizona, have been involved in the development of tools for high-throughput phenotyping (HTP) which will potentially lead to practical and low-cost ways to screen hundreds of cotton varieties at a time. Measurements from the sensors in use were extensively supported and validated. In 2012, we incorporated a new tool to the tractor-based platform: proximal scanning with light detection and ranging (LIDAR). LIDAR has the capability of rapidly and accurately scanning three-dimensional objects and is now used routinely for a wide variety of engineering applications. Use of LIDAR for mapping plants in outdoor settings is an emerging field, leading to the collection of unprecedented maps of plant canopy and leaf geometry. Provided a suitable platform, LIDAR can potentially collect high-density point-cloud data sets in minutes, yielding estimates of plant height, width and leaf orientation at thousands of locations.

In 2012, proximal LIDAR units were acquired, configured, and implemented within our cotton High-Throughput Phenotyping (HTP) experiment at Maricopa, Arizona. The HTP experiment evaluated multiple varieties grown in well-watered and water-limited environments to evaluate plant response to heat and drought stress. Software routines were created and analysis algorithms developed to retrieve estimates of plant height and width. LIDAR runs were conducted on 10 days, each consisting of 72 tractor passes and resulting in a total data collection of over 1 TB. Preliminary analyses showed excellent detection of cotton plant heights, widths and leaf angle. Extracts from the runs were used to illustrate estimation of plant height and width for each variety. Full analyses of all runs are anticipated for 2013.


Project Year: 2012

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