Professor Jinchang Ren j.ren@rgu.ac.uk
Professor of Computing Science
AI and Hyperspectral Imaging based Non-Destructive inspection for Advancing Peat Use Efficiency in Whisky Production: A Feasibility Study
People Involved
YINHE LI y.li24@rgu.ac.uk
Research Student
Project Description
This project aims to explore the feasibility of non-destructive inspection for peat using hyperspectral imagery and machine learning techniques. The primary objectives are to determine the quality of peat, measure the level of phenol released during processing, and identify the source of peat. By leveraging advanced spectral analysis methods, we seek to provide a rapid and automated approach for peat analysis, eliminating the need for manual quality control processes. By gaining insights into the quality and source of peat, whisky manufacturers can make informed decisions to select the most suitable peat for their production process, resulting in improved whisky quality.
| Type of Project | Knowledge Exchange |
|---|---|
| Status | Project Live |
| Funder(s) | Innovate UK |
| Value | £4,065.00 |
| Project Dates | Oct 1, 2023 - Mar 31, 2024 |
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