Monitoring wheat protein content on-harvester - Australian experiences

In: Precision Agriculture ‘05
Authors:
James Taylor 1Australian Centre for Precision Agriculture McMillan Building A05, University of Sydney NSW 2006
j.taylor@agec.usyd.edu.au

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,
Brett Whelan 1Australian Centre for Precision Agriculture McMillan Building A05, University of Sydney NSW 2006

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,
Lars Thylén 1Australian Centre for Precision Agriculture McMillan Building A05, University of Sydney NSW 2006

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,
Mikael Gilbertsson 2Swedish Institute of Agricultural and Environmental Engineering (JTI) Box 7033, SE-750 07 Uppsala

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, and
James Hassall 3”Kiewa”, Gilgandra, NSW, Australia

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Type:
Chapter
Pages:
369–375
DOI:
https://doi.org/10.3920/978-90-8686-549-9_046

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An on-harvester protein sensor has been tested for two seasons on a commercial combine harvester in Australia. Operators report that sensor and software were relatively easy to use especially since the model used is still a prototype set-up. Some problems with operation were noted and have been addressed for future commercial development. Output from the Zeltex NIT protein sensor was coherent and often strongly correlated to yield response, giving a good indication that the observed protein patterns were real. Absolute protein values however appeared suppressed and a new calibration curve for Australia has been developed for the Zeltex AccuHarvest® sensor.

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Cover Precision Agriculture ‘05
E-Book ISBN:
9789086865499
Publisher:
Wageningen Academic
Print Publication Date:
24 Oct 2005
Preliminary Material
Editorial
Field effect transistors in precision agriculture
A review of spectroscopic methods and their suitability as analytical techniques for farm testing
Guidance and automated steering drive resurgence in precision farming
Precision agriculture: the solution to control nutrient emissions?
Precision agriculture: a Western Australian perspective
Discrimination between nitrogen deficiency and fungal infection of winter wheat by laser induced fluorescence
Site-specific identification of fungal infection and nitrogen deficiency in wheat crop using remote sensing
Use of remote sensing within the optical and thermal spectral ranges in order to detect Septoria tritici on winter wheat
Digital infrared thermography for the assessment of leaf pathogens
Managing soilborne diseases in Australian field crops using precision agriculture and soil DNA tests
Detection and mapping of Ridolfia segetum Moris patches in sunflower (Helianthus annuus L.) crop using remote sensing techniques
Weed density prediction with secondary input of DEM information
Feasibility of a real-time weed detection system using spectral reflectance
Site-specific weed control using digital image analysis and georeferenced application maps: On-farm experiences
Site specific weed control and spatial distribution of a weed seedbank
Weed identification with chlorophyll fluorescence image analysis
The sampling problem in weed control - are currently applied sampling strategies adequate for site-specific weed control?
Describing weed patches by shape parameters
Development of an image analysis system for estimation of weed pressure
Vision based detection of volunteer potatoes as weeds in sugar beet and cereal fields
Effect of travel speed on characterizing citrus canopy structure with a laser scanner
Crop variability and resulting management effects
Vehicle mounted sensors for estimating tiller density and leaf area index (LAI) of winter wheat
Temporal prediction of nitrogen status in wheat under the influence of water deficiency using spectral and thermal information
Measuring crop status using multivariate analysis of hyperspectral field reflectance with application to disease severity and plant density
Analyses of spaceborne hyperspectral and directional CHRIS data to deliver crop status for precision agriculture
Wheat yield population response to variable rate N fertilization strategies using active NDVI sensors
In-field assessment of wheat-leaf polyphenolics using the new optical leaf-clip Dualex
Application of hyperspectral canopy reflectance measurement and partial least square regression to predict within-field spatial variation in crop growth and nitrogen status before heading stage of rice
Optimum waveband selection for determining the nitrogen uptake in winter wheat by active remote sensing
Spatial variability of crop water stress in an olive grove with high-spatial thermal remote sensing imagery
Laser-induced chlorophyll fluorescence sensing to determine biomass and nitrogen uptake of winter wheat under controlled environment and field conditions
Digital infrared thermography for monitoring canopy health of wheat
On-the-go detection of plant parameters by camera vision in rape
Suitability of different crop parameters for the determination of site-specific nitrogen fertilizer demand
Spatial relationships between soil amino sugar nitrogen, soil properties and landscape attributes
A comparison of fertilizer strategies for spring barley (Hordeum vulgare L.) based on measured yield response to applied N on morainic soils in SE Norway
Discriminating the effect of nitrogen and other environmental stresses on spatial variability of wheat yield in Mediterranean environments
Evaluation of mapping and on-line nitrogen fertilizer application strategies in multi-year and multi-location static field trials for increasing nitrogen use efficiency of cereals
Predicting variation in plant N-uptake in three fields using soil organic matter, texture and Near Infrared Reflectance (NIR) spectroscopy
Providing operational nitrogen recommendations to farmers using satellite imagery
Change in spatial variability structure of NDVI readings related to observation scale
Cotton lint quality spatial variability and correlation with soil properties and yield
Prediction of within-field yield and protein variability in malting barley using canopy reflectance, thermal stress, and soil electrical conductivity
Evaluation of an on-combine wheat protein analyzer on Montana hard red spring wheat
Uniform potato quality with site-specific potassium application
Evaluation of forage yield map techniques on a mowing-conditioning machine

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