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Wilhelm, N
Hackl, H
Ali, U
Harkin, S.J
Mohd Hanif, A
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Authors
Baresel, P
Mistele, B
Yuncai, H
Schmidhalter, U
Hackl, H
Abu Kassim, F
Vadamalai, G
Mohd Hanif, A
Balasundram, S.K
Jones, B
McBeath, T
Wilhelm, N
Balasundram, S.K
Chong, Y
Mohd Hanif, A
Ali, U
Esau, T.J
Farooque, A
Zaman, Q
Harkin, S.J
Buckmaster, D
Krogmeier, J
Evans, J
Zhang, Y
Glavin, M
Byrne, D
Harkin, S.J
Topics
Sensor Application in Managing In-season Crop Variability
Precision Crop Protection
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Decision Support Systems
Geospatial Data
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2016
2018
2022
2024
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Filter results7 paper(s) found.

1. A Comparison of Plant Temperatures as Measured By Thermal Imaging and Infrared Thermometry

... P. Baresel, B. Mistele, H. Yuncai, U. Schmidhalter, H. Hackl

2. A Non-Destructive Method of Estimating Red Tip Disease in Pineapple

Red Tip disease typically reduces pineapple yields by up to 50%. At present, the causal agent of Red Tip disease is still unconfirmed. B... F. Abu kassim, G. Vadamalai, A. Mohd hanif, S.K. Balasundram

3. Shifting Fertiliser Response Zones in a Four Year, Whole-paddock Cereal Cropping Experiment.

Precision agriculture in cropping areas of dryland Australia has focused on managing within production zones. These are ideally stable, possibly soil- and topography-based areas within fields. There are many different ideas on how to delimit and implement zones, and a four year whole-field experiment, with low, medium and high treatment philosophies applied per 9m seeder/harvester width across the entire field, was established to explore how zones might best be established and used. The treatment... B. Jones, T. Mcbeath, N. Wilhelm

4. Monitoring Potassium Levels in Peat-Grown Pineapple Using Selected Spectral Ratios

In this study, we assessed the biophysical changes within pineapple (var. MD2) in response to different potassium (K) rates using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430 nm and 680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e.... S.K. Balasundram, Y. Chong, A. Mohd hanif

5. Integration of High Resolution Multitemporal Satellite Imagery for Improving Agricultural Crop Classification: a Case Study

Timely and accurate agriculture information is vital for ensuring global food security. Satellite imagery has already been proved as a reliable tool for remote crop mapping. Planet satellite imagery provides high cadence, global satellite coverage with higher temporal and spatial resolution than the Landsat-8 and Sentinel-2. This study examined the potential of utilizing high-resolution multitemporal imagery along with and normalized difference vegetation index (NDVI) to map the agricultural crops... U. Ali, T. Esau, A. Farooque, Q. Zaman

6. Automated Geometrical Field Boundary Delineation Algorithm for Adjacent Job Sites

Establishing farmland geometric boundaries is a critical component of any assistive technology, designed towards the automation of mechanized farming systems. Observing farmland boundaries enables farmers and farm machinery contractors to determine; seed purchase orders, fertiliser application rate, and crop yields. Farmers must supply acreage measurements to regulatory bodies, who will use the geometric data to develop environmental policies and allocate farm subsidies appropriately. Agricultural... S.J. Harkin

7. In-Field and Loading Crop: A Machine Learning Approach to Classify Machine Harvesting Operating Mode

This paper addresses the complex issue of classifying mode of operation (active, idle, stationary unloading, on-the-go unloading, turning) and coordinating agricultural machinery. Agricultural machinery operators must operate within a limited time window to optimize operational efficiency and reduce costs. Existing algorithms for classifying machinery operating modes often rely on heuristic methods. Examples include rules conditioned on machine speed, bearing angle and operational time... D. Buckmaster, J. Krogmeier, J. Evans, Y. Zhang, M. Glavin, D. Byrne, S.J. Harkin