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Bekkerman, A
Jiang, Y
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Authors
Ahamed, T
Tian, L
Zhang, Y
Xiong, Y
Zhao, B
Jiang, Y
Ting, K
Maxwell, B.D
Bekkerman, A
Silverman, N
Payn, R
Sheppard, J
Izurieta, C
Davis, P
Hegedus, P.B
Maxwell, B.D
Hegedus, P.D
Loewen, S.D
Duff, H.D
Sheppard, J.W
Peerlinck, A.D
Morales, G.L
Bekkerman, A
Topics
Remote Sensing Applications in Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Decision Support Systems
Type
Oral
Year
2010
2018
2022
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Filter results3 paper(s) found.

1. Site-specific Management For Biomass Feedstock Production: Development Of Remote Sensing Data Acquisition Systems

Efficient biomass feedstock production supply chain spans from site-specific management of crops on field to the gate of biorefinery. Remote sensing data acquisition systems have been introduced for site-specific management, which is a part of the engineering solutions for biomass feedstock production. A stand alone tower remote sensing platform was developed to monitor energy crops using multispectral imagery. The sensing system was capable of collecting RGB and CIR images during the crop growing... T. Ahamed, L. Tian, Y. Zhang, Y. Xiong, B. Zhao, Y. Jiang, K. Ting

2. Can Optimization Associated with On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?

Crop production input decisions have become increasingly difficult due to uncertainty in global markets, input costs, commodity prices, and price premiums. We hypothesize that if producers had better knowledge of market prices, spatial variability in crop response, and weather conditions that drive crop response to inputs, they could more cost-effectively make profit-maximizing input decisions. Understanding the drivers of variability in crop response and designing accompanying management strategies... B.D. Maxwell, A. Bekkerman, N. Silverman, R. Payn, J. Sheppard, C. Izurieta, P. Davis, P.B. Hegedus

3. Decision Support from On-field Precision Experiments

Empirically driven adaptive management in large-scale commodity crop production has become possible with spatially controlled application and sub-field scale crop monitoring technology. Site-specific experimentation is fundamental to an agroecosystem adaptive management (AAM) framework that results in information for growers to make informed decisions about their practices. Crop production and quality response data from combine harvester mounted sensors and internet available remote sensing data... B.D. Maxwell, P.D. Hegedus, S.D. Loewen, H.D. Duff, J.W. Sheppard, A.D. Peerlinck, G.L. Morales, A. Bekkerman