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J�??�?�¸rgensen, R.N
Dempsey, D
Magalhães, P.S
Badenhorst, P.E
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Authors
J�??�?�¸rgensen, R.N
Midtiby, H.S
Giselsson, T.M
Krol, C
Dempsey, D
Cerri, D.G
Gray, G.R
Magalhães, P.S
Badenhorst, P.E
Phelan, A
Topics
Precision Crop Protection
Precision A to Z for Practitioners
Engineering Technologies
Applications of Unmanned Aerial Systems
Type
Poster
Oral
Year
2012
2008
2018
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Filter results4 paper(s) found.

1. BrainWeed - Teach-In System for Adaptive High Speed Crop / Weed Classification and Targeting

Conducting inter row mechanical weeding requires the precise location of each individual crop plant is known. One technique is to record the global position of each seed when sown using  RTK-GPS systems. Another... R.N. JÃ???Ã??Ã?¸rgensen, H.S. Midtiby, T.M. Giselsson

2. AMMO Ag: Agricultural Marketing & Merchandising Optimizer

EHedger provides an integrated risk management solution for farm operations utilizing our proprietary AMMO platform combined with proven hedging strategies, first-hand market insight, effective trade execution and farming expertise. AMMO software enables real-time analysis of crop/livestock production. Farmers can set profit margins, evaluate variable profit scenarios, understand production costs and risks, and create sustainable marketing programs to maximize their... C. Krol, D. Dempsey

3. Technological Improvement on Sugar Cane Yield Monitor

This paper presents the technological improvement on sugar cane yield monitor. The system designed employs load cells as an instrument for weighing billets, set up on the side conveyor of the harvester before the sugar cane billets are dropped into a field transport wagon. This data, along with the information gathered by GPS installed on the harvester, enabled the elaboration of a digital yield map using GIS. In order to improve the yield monitor a re-design of the first prototype was accomplished.... D.G. Cerri, G.R. Gray, P.S. Magalhães

4. Yield Assessment of a 270 000 Plant Perennial Ryegrass Field Trial Using a Multispectral Aerial Imaging Platform

Current assessment of non-destructive yield in forage breeding programs relies largely on the visual assessment by experts, who would categorize biomass to a discrete scale. Visual assessment of biomass yield has inherent pitfalls as it can generate bias between experimental repeats and between different experts. Visual assessment is also time-consuming and would be impractical on large-scale field trials. A method has been established to allow for a rapid, non-destructive assessment of biomass... P.E. Badenhorst, A. Phelan