<?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/8193D736-84D3-4D01-A011-445FC7CE98A4" ns1:id="8193D736-84D3-4D01-A011-445FC7CE98A4"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/B295B81D-8975-48F5-AC2C-2796A5E9D009" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/235BF6DE-6D9D-4EFE-8D2E-E204C7C8D519" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/235BF6DE-6D9D-4EFE-8D2E-E204C7C8D519" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/564A192E-0DD6-46E8-8E1B-E2DF70BE4C36" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-03-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/743356E5-3FF8-49C7-A1FB-EAC19DEBBF67" ns1:rel="FUND" ns1:start="2023-09-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10081207</ns2:identifier></ns2:identifiers><ns2:title>AI and Hyperspectral Imaging based Non-Destructive inspection for Advancing Peat Use Efficiency in Whisky Production: A 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>This collaborative project between The Scotch Whisky Research Institute (SWRI) and Robert Gordon University (RGU) aims to revolutionize peat analysis in the whisky industry using Artificial Intelligence (AI) and hyperspectral imaging techniques. By leveraging SWRI's expertise in whisky production and RGU's AI and hyperspectral imaging capabilities, we will achieve genuine and specific advantages in peat analysis for whisky production.

The project will develop a hyperspectral image acquisition and AI-driven analysis system, capable of obtaining high-quality hyperspectral data with precise spatial and spectral resolution. This advanced system will enable us to accurately analyse peat using advanced feature extraction and decision-making algorithms.

Hyperspectral imaging (HSI) combines spectroscopy with conventional 2-D imaging, allowing for spectral characterization of each pixel in an object. This unique capability enables the detection of minor differences in temperature, moisture, and chemical composition, surpassing the capabilities of conventional techniques. While HSI has been used to detect phenolic compounds in various materials, its application for non-destructive measurement of phenolic compounds in peat has not been fully explored.

Our innovation harnesses HSI technology to transcend the constraints of traditional, resource-heavy lab methods, offering the whisky industry an advanced, sustainable solution for peat analysis. The tangible benefits include expedited analysis, reduced resource dependency, enhanced phenol detection accuracy, and a greener approach to peat analysis. These advancements will directly contribute to improved peat efficiency, superior quality control, and consistent flavour profiling in whisky production.</ns2:abstractText></ns2:project>