The camera-based detection system being trialled at a wheat National Variety Trials at Kingsthorpe near Toowoomba, Queensland.
"This system has potential to reduce labour requirements and travel costs associated with manual inspection of grain variety trials, and improve timeliness and accuracy of growth stage identification."
- Dr Alison McCarthy
A camera monitoring system developed for use on National Variety Trial (NVT) sites is making valuable additions to information collected by agronomists.
Funded through the GRDC’s Innovation Investment program, the system was developed by the University of Southern Queensland’s National Centre for Engineering in Agriculture (NCEA), and was used in the field for the first time in 2014.
Wheat and chickpea crops at NVT sites at Wellcamp and Kingsthorpe, in Queensland’s Darling Downs, and Turretfield Research Centre, in South Australia, were chosen for the initial trial of the camera system, which ran from July to crop maturation.
NCEA research fellow and project leader Dr Alison McCarthy says camera-based remote monitoring can be used to determine the spread and intensity of flowering and crop canopy growth.
“We have developed algorithms that automatically analyse the images captured by the cameras to detect flowers and crop growth.
“The system can then send alerts to the trial service providers who currently manually monitor the flowering date and growth stage.”
Dr McCarthy says the remote monitoring has yielded more accurate information about when a variety starts and finishes flowering, and when most of that flowering is taking place.
“This system has potential to reduce labour requirements and travel costs associated with manual inspection of grain variety trials, and improve timeliness and accuracy of growth stage identification,” she says.
The improved flowering data is likely to be particularly useful when determining some of the key susceptibilities and resistances of varieties to variables such as frost and disease.
Powered by a small solar panel and post-mounted in a PVC junction housing, the system is based on a 20-megapixel multi-spectral smartphone camera.
Every 30 minutes during daylight hours, the camera captures images through a red filter, to detect flowering, and through a UV filter to give a standard image.
Images are uploaded in real time to a website using an app developed by NCEA research fellow Dr Matthew Tscharke.
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