Proceedings

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Endres, G
Bradford, J
Dobers, S.E
Farahmand, K
Runge, M
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Authors
Samborski, S.M
Gozdowski, D
Dobers, S.E
Winstead, A.T
Norwood, S.H
Griffin, T
Adrian, A.M
Runge, M
Fulton, J.P
Sharma, L
Bu, H
Ashley, R
Endres, G
Teboh, J
Franzen, D.W
Momsen, E
Xu, J
Franzen, D.W
Nowatzki, J.F
Farahmand, K
Denton, A.M
Erickson, B
Lowenberg-DeBoer, J
Bradford, J
Topics
Remote Sensing Applications in Precision Agriculture
Precision A-Z for Practitioners
Sensor Application in Managing In-season CropVariability
Remote Sensing Applications in Precision Agriculture
Education and Outreach in Precision Agriculture
Type
Poster
Oral
Year
2010
2014
2018
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1. The Use Of A Ground Based Remote Sensor For Winter Wheat Grain Yield Prediction In Northern Poland

  The aim of the research was to investigate if algorithms developed for winter wheat, cv. Trend, yield predictions, based on ground measured GNDVI, differ significantly between 2 sequent years. The research was conducted in Pomerania, northern Poland (54° 31' N 17° 18' E) on sandy loam soils. The strip-trial design was used to compare the effect of 6 N treatments: 0, 50, 100, 150, 200 and 250 kg ha-1, applied as one dose at the beginning... S.M. Samborski, D. Gozdowski, S.E. Dobers

2. Adoption And Use Of Precision Agriculture Technologies By Practitioners

A survey of farmers and farm service providers were initiated to ascertain the adoption and use of precision agriculture technologies as well as the barriers to and incentives for adoption. Farm-level data were collected via audience response system at the 2009 Alabama Precision Ag and Field Crops Conference and local winter production meetings across the six crop reporting districts in Alabama. Service provider data were collected using an online survey. Questions common to farmers and service... A.T. Winstead, S.H. Norwood, T. Griffin, A.M. Adrian, M. Runge, J.P. Fulton

3. Active Optical Sensor Algorithms For Corn Yield Prediction And In-Season N Application In North Dakota

A recent series of seventy seven field N rate experiments with corn (Zea mays, L.) in North Dakota was conducted. Multiple regression analysis of the characteristics of the data set indicated that segregating the data into those with high clay soils and those with medium textures increased the relationship between N rate and corn yield. However, the nearly linear positive slope relationship in high clay soils and coarser texture soils with lower yield productivity indicated... L. Sharma, H. Bu, R. Ashley, G. Endres, J. Teboh, D.W. Franzen

4. Use Of Quality And Quantity Information Towards Evaluating The Importance Of Independent Variables In Yield Prediction

Yield predictions based on remotely sensed data are not always accurate.  Adding meteorological and other data can help, but may also result in over-fitting.  Working with American Crystal Sugar, we were able to demonstrate that the relevance of independent variables can be tested much more reliably when not only yield but also quality attributes are known, such as the sugar content and the sugar... E. Momsen, J. Xu, D.W. Franzen, J.F. Nowatzki, K. Farahmand, A.M. Denton

5. Tracking Two Decades of Precision Agriculture Through the Croplife Purdue Survey

The CropLife/Purdue University precision dealer survey is the longest-running continuous survey of precision farming adoption.  The 2017 survey is the 18th, conducted every year from 1997 to 2009, and then every other year following.  For individuals working in agriculture there is great value in knowing who is doing what and why, to get a better understanding of the utilities and applications, and to guide investments.  A major revision in survey questions was made... B. Erickson, J. Lowenberg-deboer, J. Bradford