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Applications of indirect measures of electrical conductivity were evaluated
in several field experiments. This work aims to identify added input variables
to refine the in-season prediction of yield.
TEAM-VRT entered into discussions with John Mayfield concerning the potential
commercialization of a sensor-based N fertilizer applicator for cereal
crops.

The results that we were looking for (increased yields at I over N rates)
came through at Covington. However, at 10 OFF field experiments in 2000,
this same result could not be repeated. Using the in-season response index
(RINDV ), we were able to proj ect responsiveness to applied N, which
changes from location to location based on climatic conditions specific
to each parcel of land, and that changes on the same land from year to
year.
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