Lead Participant: P.E.S. Technologies Limited


Feeding 9.8 billion people in 2050 in a climate change context will depend on our skills to keep soils alive. Food production is directly correlated with soil health. To manage and improve soil health, farmers need reliable information about the chemical, physical and biological properties of their soils. There are methods available to assay soil nutrients and determine the physical properties of soils. Only respiration-based methods are currently available to farmers to measure the microbial contributions to soil health, but these give no information on the microbiota present and are affected by other sources of CO2 in the soil. Next-generation sequencing has potential as a biological indicator of soil health, but the costs are high, the tests take hours to conduct, and the data obtained requires experts in order to interpret it.

Our solution is to tap into the wealth of information contained in the volatile organic compounds (VOCs) released by soil biota. These have been demonstrated to be excellent indicators of soil biota activity, but their detection and analysis currently requires laboratory-based instrumentation and skilled personnel. In preliminary work we developed a sensor that can detect soil VOCs and demonstrated that its responses can be correlated with soil health. In this project we will determine the responses of such sensors to a wide range of different soils and cropping systems. These will be correlated with conventional soil health indicators and next-generation sequencing data. Machine learning will be used to process the data obtained to provide a cloud-based database that can be accessed directly by sensors in the field. Use of robots to deploy the sensors with associated GPS data will be investigated to provide farmers with comprehensive and fine-scale data of soil health on their farms so that they can assess the impact of farming practices on soil health and adapt these to increase soil health and productivity. Testing every square meter of land data would be unfeasibly expensive with current testing methods (£60/sample) as the average UK farm size is 930,000 sq. m..

The project will be led by P.E.S. Technologies, a start-up company that developed a plastic electronic sensor for soil VOCs, in collaboration with Hutchinsons, UK agronomy specialists, and the Small Robot Company. Academic partners will be NIAB-EMR, the leading UK horticultural research organisation, the Natural Resources Institute with long experience in VOC profiling, and the University of Essex with expertise in machine learning.

Lead Participant

Project Cost

Grant Offer

P.E.S. Technologies Limited, London £633,309 £ 443,316


University of Greenwich, United Kingdom £50,679 £ 50,679
Small Robot Company Limited, Gosport £282,338 £ 197,637
National Inst of Agricultural Botany £256,987 £ 256,987
H.L. Hutchinson Limited, WISBECH £74,020 £ 24,413
University of Essex, United Kingdom £62,916 £ 62,916


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