Field-health extension signal
Pezego is Mutus Tech's mobile tool for in-field pest detection and biotic-stress intelligence. It sits alongside NDVI and field records on the same field polygon — adding a pest signal to the Soil Health and Fertiliser operating loop.
Where this fits
Assess
Baseline field polygon, soil chemistry, climate and crop context.
Plan
12-month NPKS plan and N-rate sensitivity.
Execute
Recommendations published as Farm Tasks.
Monitor
NDVI, Climate History, observation notes — and Pezego as an optional biotic-stress signal.
Report
Operating records consolidated for partner review.
Pezego is positioned as pest detection / biotic-stress intelligence, not as a standalone IPM prescription system. Recommendations are interpreted with soil tests, crop context and management records, and validated through agronomy partners.
The mobile app
Pezego runs on iOS and Android and is designed for low-connectivity rural areas. Most identification responses arrive in under 30 seconds.
How it works
01
A leaf is chewed, an aphid colony is forming, an unfamiliar larva is on a stem. Open Pezego in the field.
02
The app sends your image to our vision model, anchored to your country's pest taxonomy. You get the pest name and confidence score in seconds.
03
Confirm crop and growth stage, drop a GPS pin and Pezego auto-fetches the local weather. Extension officers can verify or correct the identification.
04
A risk level and a region-specific IPM recommendation, drawn from AHDB, RR98 and partner agricultural guidelines.
Coverage
40+
Pests in the Ghana knowledge base — Fall Armyworm, stem borers, cassava mealybug, pod borer and more.
19
UK pests covered out of the box — grain aphid, pollen beetle, CSFB, slugs, potato cyst nematode and more.
10
Crops covered in Ghana with detailed growth-stage taxonomy — Maize, Rice, Cassava, Yam, Cocoa, Cowpea, Groundnut, Tomato, Pepper, Plantain.
38
Major pests covered across the platform; the PEZEGO IEEE IoT Journal paper documents the 38-pest / 10-crop UK coverage and the 10,000+ annotated images underpinning the model.
The knowledge base draws on AHDB encyclopaedia entries, the RR98 crop-stage management review, region-specific agricultural guidance and our own field data. Coverage figures are documented in the peer-reviewed PEZEGO IEEE IoT Journal paper. New pests, crops and regions can be added through partner programmes.
Two regions, two playbooks
Focused on Fall Armyworm in Maize and the broader smallholder pest set, with a Ghana extension-officer network in place. Region (Greater Accra, Ashanti, etc.) and district selectors built in. Recommendations are written in clear, short sentences for low-input farms.
Tuned for UK agronomy. The recommendation engine references AHDB sources and the RR98 crop-stage management review, with structured data on insecticide thresholds and resistance.
Two audiences
Designed for use in the field on a phone, including by smallholders with limited data access.
Pezego is the front line of our pest-outbreak monitoring. ESOs see every record in their region, can verify and correct identifications and act as the trusted human-in-the-loop.
Beyond identification
Every observation carries a GPS pin. Officers and researchers can pull every report within a chosen radius, making early detection of regional outbreaks a click rather than a phone tree.
ESO verification flags create a layer of trusted data on top of crowdsourced reports — useful for monitoring, research and reporting to funders.
Field staff share findings, photos and treatment notes, tagged by pest and crop. A living, regional IPM playbook contributed by the people closest to the fields.
Peer-reviewed
IEEE IoT Journal · Volume 12, Issue 23
Co-developed with RSK ADAS, the University of Sheffield and the University of Liverpool. 20+ farms, 10,000+ annotated images, 38 pests, 10 crops.
Get Pezego
Co-developed with the University of Sheffield, University of Liverpool and RSK ADAS. Available now on iOS and Android.
