|BARBATO, LUCIA - Texas Tech University|
|SESHRADI, SANTOSH - Texas Tech University|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/1/2013
Publication Date: N/A
Technical Abstract: The growth and development of a crop follows a temporal path from planting to harvest that is continuously affected by environment and management. The number of temporal paths associated with environment/management combinations (year-to-year and location-to-location) is quite large. The increasing use of automated data monitoring systems has made it possible to monitor plant/environment interactions on sub-hour intervals over growing seasons (>100 days). The resulting time series of data for a number of variables can easily produce data sets of more that one million observations. The analysis of datasets of this magnitude presents new challenges. We have developed a GIS-baed approach that presents seasonal time series of observations as “time surfaces”. These fine scaled, season-long time surfaces provide a means of qualitatively visualizing seasonal phenotypes of environmental and plant metabolic interactions. We have used this approach to analyze plant/environment interactions of cotton over multiple irrigation regimes across multiple growing seasons. Through the interactive manipulation of the datasets afforded by the GIS system novel insight has been gained into plant/environment interactions within and among years. Seasonal phenotypes are presented to show irrigation and canopy temperature interactions, the effects of irrigation on leaf-to-air VPD, and modeled responses of photosynthetic activity.