<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/852EFBDF-3550-474F-A642-F382258FB628" ns1:id="852EFBDF-3550-474F-A642-F382258FB628"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/C300A5D4-B9E1-4585-B158-352F38B2C3AF" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3843810F-2EAD-40A9-9DA5-A1E4A8450DDC" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3843810F-2EAD-40A9-9DA5-A1E4A8450DDC" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/D97CFAAF-4343-4518-B561-0FBBA4A67925" ns1:rel="FUND" ns1:start="2022-01-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10020378</ns2:identifier></ns2:identifiers><ns2:title>Colombian avocado feasibility study</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>For some farmers, pesticides represent one-third of their costs, and pesticide overuse through blanket spraying of fields has significant biodiversity implications. While pesticides treat diseases and pests, they also kill helpful bugs (an essential source of nutrients), requiring nitrogen-based fertiliser to boost crop yields. Artificial pesticide use is increasing every year, and this pesticide-fertiliser combination has the potential to contaminate groundwater sources.

Agribot is developing precision farming technologies to reduce pesticide use. Agribot uses AI to detect crop stress (under/over-fed, under/over-watered, mites, disease) from satellite data, and diagnose disease with 99.98% accuracy. This creates an invaluable early detection system, enabling the use of less aggressive (often organic) treatments that only work if administered early.

As part of this feasibility study, research will be carried out to explore the process of adding additional crops to the Agribot models specifically avocados, coffee and cacao so that farmers on an international level can benefit from accurate and accessible precision farming technology.</ns2:abstractText></ns2:project>