Posted 2 August 2004As part of the SA LINK project `Integrated management strategies for potato cyst nematodes` PhD student Bill Heath, from the Nematology and Entomology Research Group at Harper Adams University College, Shropshire, has undertaken experiments to compare the distribution of light reflected from healthy potato plants and plants infected with PCN.
Potato cyst nematodes (PCN) are microscopic worms present in approximately two-thirds of the potato-growing land in England and Wales. They feed in the roots of the potato crop making it less efficient at taking up both water and nutrients from the soil, reducing potato production by nine per cent.
The detection of PCN over large areas is problematic and current methods are unsuited to monitoring the patchy nematode populations found in commercial fields. A method of quickly scanning large fields for PCN infestation would enable growers to target expensive control methods on infected areas.
Light (electromagnetic energy from the sun) is present over a wide spectrum of which only a small part is visible to the human eye. Growing plants absorb mostly visible light and convert it to sugars for nutrition. Healthy plants reflect near-infra-red (NIR) light, invisible to humans, but capable of detection by sophisticated sensors. A reduction in plant health status can be measured by comparing the ratio of NIR and visible light reflected from the crop canopy.
Preliminary results from the PhD study, using a field spectrometer to measure reflectance from pot-grown and individual field plants, indicated a good relationship between PCN damage and canopy reflectance.
The analysis was subsequently extended to cover entire fields using data collected from an aircraft flown over commercial potato crops. Aircraft sensors recorded reflected light from the crop at more than 140 wavelengths, enabling very detailed calculations on the status of the crop across the extensive area surveyed.
Results from the aerial survey were consistent with measurements obtained from the field spectrometer. Imagery from satellites was also investigated for regional trend monitoring of PCN distribution with partial success.
Spectral regions suitable for the identification of PCN infestation have been identified and development of a PCN-specific detection device is currently under discussion.
For further information contact: Bill Heath on 01952 815361 or Patrick Haydock 01952 815292.