Title

Spectral reflectance data of plant green

Author Identifiers

Kamal Alameh

National Library of Australia: nla.party-508964

Scopus: 7004211082

Collection Type

Dataset

Faculty

Faculty of Computing Health and Science

School or Research Centre

Centre for MicroPhotonic Systems Electron Science Research Institute

Contact

k.alameh@ecu.edu.au

Publisher

Edith Cowan University Research Online

Funders

Australian Research Council

ECU Industry Collaboration Schemes

Dataset Identifier

http://hdl.handle.net/102.100.100/6912

Description

The dataset contains spectral reflectance data of various crop plants and weeds. The data has been collected in the field using a spectrometer, from farm locations in Queensland and Western Australia. The dataset contains the spectral reflectance characteristics of various crop plants and weeds including sugarcane, cotton, wheat, skeleton weeds, guinea and Johnson grasses, which were monitored at different plant development stages in Gingin, Western Australia and Toowoomba and Bundaberg, Queensland. The data is categorised by time of year collected, plant name, weed name, farm and place. At this stage the dataset contains spectral reflectance data of more than 10 different plants, collected since 2008, however the dataset is growing. Data is stored in Excel file format.

Additional Information

Other participants in the research are Sreten Askraba (Senior Research Fellow, ESRI) and Arie Paap (Post Doctoral Research Fellow, ESRI).

Electron Science Research Institute - http://esri.ecu.edu.au/

Search and destroy lasers used in the fight against weeds - http://www.ecu.edu.au/news/media-releases/2013/02/search-and-destroy-lasers-used-in-the-fight-against-weeds

FoR Codes

020504, 070105

Research Activity Title

Laser-based photonic weed sensor

Research Activity Description

The aim of the project is to develop a microphotonic weed sensor engine to capture and analyse spectral data for accurate discrimination and detection of weeds and crops. The result would enable better agricultural weed eradication based on the unique properties of the green of weeds when compared to the green of the agricultural crop. Funding was provided via two ARC Linkage grants to improve the sensor device. Other funding sources have been ECU Industry Collaboration schemes. The project commenced in 2008 and is continuing.

Start of data collection time period

January 2008

Language

eng

Access Rights

Access to the dataset is subject to legal and commercial restrictions. Photonic Detection Systems is the commerical partner. Contact Professor Kamal Alameh of the Electron Science Research Institute at Edith Cowan University to determine access conditions.

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