2024/05/03 by Yijun Yan, Jinchang Ren, Yan, Yijun +9
Environmental Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Rangeland and Wildlife Management #Remote Sensing and LiDAR Applications #Soil Geostatistics and Mapping #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2405.02191
openalex publication_date 2024/05/03 · openalex created_date 2024/05/11 · openalex updated_date 2026/07/28
Peat, a crucial component in whisky production, imparts distinctive and irreplaceable flavours to the final product. However, the extraction of peat disrupts ancient ecosystems and releases significant amounts of carbon, contributing to climate change. This paper aims to address this issue by conducting a feasibility study on enhancing peat use efficiency in whisky manufacturing through non-destructive analysis using hyperspectral imaging. Results show that shot-wave infrared (SWIR) data is more effective for analyzing peat samples and predicting total phenol levels, with accuracies up to 99.81%.