Shannon-Wiener's diversity index for linking yield monitor and remotely sensed data for corn

Yield is the ultimate measure for quantifying the effect of agricultural inputs. Measurement of yield variability is needed for developing and evaluating site-specific crop management strategies. However there are many sources of error in measuring the actual yield variability. To assess the contribution of harvest practices to yield variability, yield monitor and aerial image data were collected in the 2000 growing season. Aerial images were collected by a DuncanTech MS3100 multispectral digital camera on two dates. The boundary effect on variability of yield monitor data was studied by successive clipping of yield monitor data for determining the effect of the harvester operations at the end of the field on the yield monitor errors. Results indicated that the correlations between grain yield and the normalized difference vegetation index (NDVI) at the V16 growth stage were improved as the field perimeter was clipped to 30.5 m inside of the field boundary; the coefficient of determination (r(2)) improved front 0.67 to 0.76. The Shannon-Wiener diversity index (SWDI), an index used in ecological studies to determine how diverse a population is, showed that diversity at the perimeter was decreased as additional clipping of data occurred inside the field perimeter. The yield variability was considerably higher in the clipped areas than in other areas due to the speed of the harvester, headland harvest, and time for yield monitor fill-up and emptying. Areas of the highly diverse yield monitor were about twice that of remotely sensed data, as indicated by the SWDL Results indicated that the outer 6.1 in was responsible for about 34% of the high yield diversity at the perimeter of the field. The headland harvesting effect was included fully in that 34% high yield diversity.