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Ravindran, P
Nagel, P
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Authors
Herrmann, I
Vosberg, S
Ravindran, P
Singh, A
Townsend, P
Conley, S
Nagel, P
Fleming, K
Fleming, K
Schottle, N
Nagel, P
Koch, G
Topics
Precision Agriculture and Global Food Security
Big Data, Data Mining and Deep Learning
Profitability and Success Stories in Precision Agriculture
Type
Poster
Oral
Year
2018
2022
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Filter results3 paper(s) found.

1. Exploring Tractor Mounted Hyperspectral System Ability to Detect Sudden Death Syndrome Infection and Assess Yield in Soybean

Pre-visual detection of crop disease is critical for both food and economic security. The sudden death syndrome (SDS) in soybeans, caused by Fusarium virguliforme (Fv), induces 100 million US$ crop loss, per year, in the US alone. Field-based spectroscopic remote sensing offers a method to enable timely detection, but still requires appropriate instrumentation and testing. Soybean plants were measured at canopy level over a course of a growing season to assess the capacity of spectral measurements... I. Herrmann, S. Vosberg, P. Ravindran, A. Singh, P. Townsend, S. Conley

2. Changing the Cost of Farming: New Tools for Precision Farming

Accurate prescription maps are essential for effective variable rate fertilizer application.  Grid soil sampling has most frequently been used to develop these prescription maps.  Past research has indicated several technical and economic limitations associated with this approach.  There is a need to keep the number of samples to a minimum while still allowing a reasonable level of map quality.  As can be seen, precision agriculture management... P. Nagel, K. Fleming

3. You Can Not Manage What You Dont Measure

The problem of variability in soil nutrient analysis has been studied for years by a number of industry experts; unable to decipher and commercialize hyperspectral soil sensing. Many studies have taken years of testing to account for variability thathas a dramatic impacts on precision of recommendations. The main tradeoff we have identified is between accuracy and precision. Large quantities of raw data are required... K. Fleming, N. Schottle, P. Nagel, G. Koch