Up to 40% of the world’s food production is lost to pests each year, according to the Food and Agriculture Organization of the United Nations. Over $220 billion is lost to plant diseases annually, while at least $70 billion is lost to invasive insects.
Strawberries will be used in the Midlands-based study’s testing of the new technology. The fruit, which Aston University estimates is worth £350 million to the UK economy, is susceptible to the potato aphid, which has the power to destroy a whole harvest.
Although pesticides can be used to treat crops, there is growing pressure to develop alternatives due to their negative effects on the environment.
IPM, or integrated pest management, is one approach to developing an early warning system. Instead of spraying plants with chemicals, it monitors for the development of insects and illnesses on the plants, although it is believed to have so far proven unreliable and expensive.
The new initiative combines machine learning hardware with recent advancements in photonics technology to analyze low amounts of volatile organic compounds (VOCs) released by plants, which are indicators of their health.
Aston Institute of Photonic Systems (AIPT) Professor David Webb issued a statement in which he stated: “Better invertebrate pest and plant disease monitoring technologies would greatly help decrease agricultural losses.
“However, the majority of electronic noses use electrochemical sensors, which have weak specificity, sensitivity problems, and sensor drift/aging effects.
We want to address this by using the rapidly developing field of photonics, which is the study of light, and working with researchers from several fields.
The Biotechnology and Biological Sciences Research Council (BBSRC) and the Natural Environment Research Council will each contribute £200,000 to the 12-month experiment.
“With the predicted growth in the world’s population, there is increased pressure on the agricultural industry to attain higher crop yields,” stated Dr. Joe Roberts of Harper Adams University.
“Reducing crop losses within existing production systems will improve food security without increasing resource use.”
Dr Roberts continued: “We intend to establish an interdisciplinary community of agricultural science, optical sensing and machine learning experts to develop novel plant health monitoring platforms that enhance agricultural production through localised pest and disease monitoring to detect hotspots.”