The proposed project will develop a functional rapid data analytic procedure which will involve RTK-GPS surveyed information on test plots, high spatial and RTK-GPS as-planted data, novel techniques to utilize as-planted data to develop row-by-row planted maps. The high resolution row-by-row planted knowledge will provide ability to develop methodology for rapid extraction of plot-by-plot canopy response to quickly analyze large field datasets. It is expected that the newer data analytic technique would provide rapid data analysis but with results equivalent or better results compared to manual analysis. UAS TIRIS will accurately measure canopy temperatures under varying ambient conditions. This data analytic technique can provide critical knowledge for high throughput phenotyping and can be utilized in breeding and precision agriculture programs to develop more resilient soybean programs for the Kansas growers.

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On-farm planter application data was utilized to create row-by-row way point. The 10 Hz data provided high resolution RTK-GPS information required to develop row-by-row planted data for ArcGIS analysis and mapping. Way points from each row unit were converted from point data to line data (representing row unit pass), and finally buffers were created around each line. The planter row unit passes with buffers was overlaid on low altitude high-resolution data to extract crop response data.
The individual steps needed to go from planter as-applied point data to creating buffers for each row unit pass was accomplished. In year-2 the process as indicated for 2021 work will be completely automated including automatically naming each plot for plot-by-plot analysis.