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Title: SHANNON-WEINER'S DIVERSITY INDEX FOR LINKING YIELD MONITOR AND REMOTELY SENSED DATA FOR CORN

Author
item DIKER, KENAN
item HEERMANN, DALE
item BAUSCH, WALTER
item WRIGHT, DAVID - RED HEN INC.

Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/20/2004
Publication Date: 7/20/2004
Citation: Diker, K., Heermann, D.F., Bausch, W.C., Wright, D.K. 2004. Shannon-weiner's diversity index for linking yield monitor and remotely sensed data for corn. Transactions of the ASAE.

Interpretive Summary: Yield monitors have been used for collecting yield for several years. Yield monitor data can be utilized for decision making for up-coming years management strategies. However, there are several errors associated with yield monitor data. Assessment of these errors by remote sensing technology was studied. Results showed that yield variability at the edges of the field were higher than that suggested by remotely sensed data. Speed of the harvester, headland planting/harvesting, and/or harvester travel into and out of the field seemed to be the contributors to the errors. We concluded that remote sensing of yield variability could be an efficient way to quantify the yield monitor errors. We expect producers and crop consultants will find this methodology useful in assessment of errors introduced by yield monitors.

Technical Abstract: 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 to yield variability by harvest practices, yield monitor and aerial image data were collected in 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 (r2) improved from 0.67 to 0.76. Shannon-Weiner's Diversity Index (SWDI), an index used in ecological studies to determine how diverse the 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 others due to the speed of the harvester, headland harvest and time for yield monitor fill-up and emptying. The highly diverse yield monitor areas were about 2 times that of remotely sensed data as indicated by the SWDI. Results indicated that the outer 6.1 m 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.