Project Summaries

12-252  Project Manager: E. M. Barnes


Diane L. Rowland and Josh Thompson, University of Florida

The primary objective in this proposed research is to quantify root growth and architecture and correlate these measurements with soil moisture patterns and direct quantification of crop water use through the use of sap flow.  We found that there was a significant correlation between cotton sap flow and soil moisture at 60 cm for non-irrigated plots. These data suggest that certain depths (in this case 60 cm) relate more strongly to crop water use than others. Our root images from a minirhizotron camera system allowed us to confirm that the zone of highest root proliferation for the non-irrigated plots occurred at the 60 cm depth. Therefore, the zone of greatest water uptake would be expected to be at 60 cm where the greatest root mass existed and should give the strongest direct relationship with crop water use.

This project provided details about the effect of reduced irrigation on root architecture and crop water-use. It also allowed us to directly relate soil moisture and root architecture and morphology with quantified patterns of crop water uptake, and to examine how these relationships may change under reduced irrigation. Finally, it allowed us to validate the efficacy of various soil moisture measurement technologies to serve as indirect measurements of crop water use. Our results indicate that it is critical to determine what soil depth accurately reflects crop water use and use measurements of soil moisture at that depth to schedule irrigation. Since plant water use may act independently of soil moisture, using soil moisture as a surrogate for irrigation scheduling may be problematic in some cases. Therefore, it is essential to validate the relationship between soil moisture and sap flow and to identify the appropriate soil depths to monitor soil moisture for irrigation scheduling. Knowledge about this relationship could determine the success or failure of irrigation scheduling systems utilizing soil moisture sensors and could prove to be essential for improving cotton irrigation scheduling efficiency in the southeast.


Project Year: 2012

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