<?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/F85A6331-6BE8-4199-82B3-C56255202D6D" ns1:id="F85A6331-6BE8-4199-82B3-C56255202D6D"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/44D1A3D9-0E12-49AC-90CC-61C8D2ED6140" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/486C79D3-3A40-4754-AA6E-C543BE483DD7" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/486C79D3-3A40-4754-AA6E-C543BE483DD7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3BF846E8-E54C-4D21-AFB9-B81CA58DF919" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/7D2795CE-95D1-43FD-B934-625E85149D2E" ns1:rel="FUND" ns1:start="2023-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10085176</ns2:identifier></ns2:identifiers><ns2:title>PollenProtect: Using AI to create pollinator-protection zones</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>The intensification of agriculture has undermined vital pollination services provided by wild insect pollinators (WIPs), resulting in a downward decline in pollinator numbers and significant concerns about the sustainability of food production systems. Current methods to address biodiversity loss and productivity are missing vital information about WIP populations and the economic/environmental impacts of cultivating habitats for them within the agricultural landscape. The innovation between AgriSound and RegenFARM aims to address these issues through the use of novel sensor technology to capture population data about WIPs in the field and use this to create optimised land strategies using AI enabled simulation to improve the productivity of crops, while enabling farmers/growers to build resilience and operate more sustainably.

This project seeks to undertake critical development and pilot trials, moving the innovation from TRL4 to TRL6/7 with projected market entry Q42025\.</ns2:abstractText></ns2:project>