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Updated: Jul 15, 2026

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

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使用负担得起的多通道光谱传感器与机器学习相结合,快速识别咖啡品种和来源

Diang Sagita1, Slamet Widodo2, Sutrisno Suro Mardjan2

  • 1Agricultural Engineering Sciences, Graduate School, IPB University, Bogor 16680, Indonesia; Research Center for Appropriate Technology, National Research and Innovation Agency, Subang 41213, Indonesia.

Food research international (Ottawa, Ont.)
|May 13, 2025
PubMed
概括

这项研究使用了负担得起的光谱传感器和机器学习来准确地识别咖啡的种类和来源,而不是破坏性地. 线性差异分析 (LDA) 在物种识别方面达到100%的准确性,在原产地识别方面达到91.7%的准确性.

关键词:
人工智能的人工智能是人工智能.食品计算 食品计算食品质量控制 食品质量控制多通道光谱传感器多通道光谱传感器快速识别 快速识别 快速识别

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