Proceedings :: International Society of Precision Agriculture

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Badenhorst, P.E

George, D

Velasquez, A.E

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Authors

Becker, M

Velasquez, A.E

Guerrero, H.B

HIguti, V.A

Milori, D.M

Magalhães, D.V

Nawar, S.M

Mouazen, A.M

George, D

Manfield , A

Badenhorst, P.E

Phelan, A

Topics

Engineering Technologies and Advances

Proximal Sensing in Precision Agriculture

Applications of Unmanned Aerial Systems

Type

Oral

Year

2016

2018

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Filter results3 paper(s) found.
1. Helvis - a Small-scale Agricultural Mobile Robot Prototype for Precision Agriculture The use of agricultural robots is emerging in a complex scenario where it is necessary to produce more food to feed a crescent population, decrease production costs, fight plagues and diseases, and preserve nature. Around the world, there are many research institutes and companies trying to apply mobile robotics techniques in agricultural fields. Mostly, large prototypes are being used and their shapes and dimensions are very similar to tractors and trucks. In the present study, a small-scale... M. Becker, A.E. Velasquez, H.B. Guerrero, V.A. Higuti, D.M. Milori, D.V. Magalhães Download paper
2. Comparing Predictive Performance of Near Infrared Spectroscopy at a Field, Regional, National and Continental Scales by Using Spiking and Data Mining Techniques The development of accurate visible and near infrared (vis-NIR) spectroscopy calibration models for selected soil properties is a crucial step for variable rate application in precision agriculture. The objective of the present study was to compare the prediction performance of vis-NIR spectroscopy at local, regional, national and continental scales using data mining techniques including spiking. Fresh soil samples collected from farms in the UK, Czech Republic, Germany, Denmark and the Netherlands... S.M. Nawar, A.M. Mouazen, D. George, A. Manfield Download paper
3. 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

Filter results3 paper(s) found.

1. Helvis - a Small-scale Agricultural Mobile Robot Prototype for Precision Agriculture

The use of agricultural robots is emerging in a complex scenario where it is necessary to produce more food to feed a crescent population, decrease production costs, fight plagues and diseases, and preserve nature. Around the world, there are many research institutes and companies trying to apply mobile robotics techniques in agricultural fields. Mostly, large prototypes are being used and their shapes and dimensions are very similar to tractors and trucks. In the present study, a small-scale... M. Becker, A.E. Velasquez, H.B. Guerrero, V.A. Higuti, D.M. Milori, D.V. Magalhães

Download paper

2. Comparing Predictive Performance of Near Infrared Spectroscopy at a Field, Regional, National and Continental Scales by Using Spiking and Data Mining Techniques

The development of accurate visible and near infrared (vis-NIR) spectroscopy calibration models for selected soil properties is a crucial step for variable rate application in precision agriculture. The objective of the present study was to compare the prediction performance of vis-NIR spectroscopy at local, regional, national and continental scales using data mining techniques including spiking. Fresh soil samples collected from farms in the UK, Czech Republic, Germany, Denmark and the Netherlands... S.M. Nawar, A.M. Mouazen, D. George, A. Manfield

Download paper

3. 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