How 3D crop mapping can future-proof potatoes
© Gary Naylor Photography A world-leading potato research programme at Newcastle University is hoping to future-proof potatoes through a range of tools including 3D crop architecture mapping and early detection of pests and disease.
Dr Ankush Prashar, a crop scientist and lecturer at the university, explains how the team are mapping the crop canopy architecture of 300 potato varieties to gain a deeper understanding of how potato plants develop, as well as the variability in their architecture above ground.
This will ultimately help them develop a more robust set of crop traits and enable the detection of diseases such as blight and nematode infestations before symptoms reveal themselves.
See also: Potato growing innovations to cut inputs and carbon footprint
Environmental factors
“We’re aiming to look at the genetic and physiological traits of different varieties and link this to how they adapt to different biotic and environmental stresses such as diseases, drought and sub-optimal nutrition,” he says.
“We then want to use this information to develop an evaluation toolkit for farmers. The aim is to work towards a ‘digital agronomist’ which incorporates and integrates different data streams.”
Part of the research is also using machine learning to distinguish between different potato varieties and develop a weed model that assesses which weed species are more likely to grow in certain soil types and with particular potato varieties.
“We want to investigate the importance of a range of parameters that affect potatoes simultaneously, including soil health, nutrition, weeds and disease.
“Previous modelling systems only consider one of these factors at a time, but we know in the field that these stresses are experienced together,” says Ankush.
3D canopy mapping
The research team are using low-cost drone imaging to create 3D surface models of the potato crop canopy, giving detailed data on plant height and canopy cover over the growing season.
This approach demonstrates how a better understanding of crop development can inform decision making and improve management practice.
“In terms of use for the farmer, canopy monitoring information can identify key indicators of crop development and health.
“Early senescence or canopy lodging, for example, could help predict the onset of disease. When combined with other datasets, this can help determine a variety’s optimal harvest date.”
Detection of late blight and nematodes in potato crops
Two PhD students at Newcastle University are currently investigating the early detection of blight in potato crops before symptoms are visible to the human eye.
Blight lesions are normally seen in potato leaves about four days post-inoculation as the infected leaf cells begin to die.
However, it is possible to use technology to detect internal cellular response changes within the plant earlier in the pathogen’s infection cycle.
The research is based around two main internal potato crop responses: structural and spectral.
“In healthy crops with no disease or stress, crop cellular structures are strong and remain intact, ensuring optimal growth and function,” explains Newcastle University crop scientist Dr Ankush Prashar.
“When crops experience stress and become infected with disease, these structures begin to dismantle and physically change – and this is what we are closely monitoring,” Ankush adds.
Furthermore, as infected cells die, leaves begin to yellow and so the level of light reflectance from them changes.
“Using high-tech cameras, signature wavelengths are being assessed to identify infected plants before cells begin to die,” Ankush says.
When this information is combined with in-field spore sensors, weather forecasting and imaging sensors, farmers can have access to detailed forecasts.
“The aim is to allow more targeted fungicide spraying, giving growers the confidence to reduce application frequency and perhaps increase rates during peak blight pressure to achieve more effective control,” Ankush adds.
The PhD students are also using similar methods to monitor potato canopies to identify crops infected with nematodes without techniques that are destructive to the soil.
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