通过特定产地颜色特征提升咖啡豆品质评估效率与公正性
Site-Specific Color Features of Green Coffee Beans
- 基于产地特异性颜色特征构建评估方法
- 相比现有方案计算成本更低且通用性强
- 可识别不同产地豆子，防造假，适合产业应用
咖啡是最重要的初级商品之一，但绿咖啡豆的筛选仍依赖人工目视，费力且主观。本文提出一种与产地无关的方法，提取优质绿咖啡豆种皮的特定产地颜色特征，并据此设计两种评估方案。由于该颜色特征具有产地特异性，机器学习分类器表明，相比现有方案，本方法更简单、计算成本更低、适用范围更广。最终，该特征能有效区分不同产地的合格豆，具备防伪功能，是本方案的独特优势。
原文摘要 · Abstract (English)
Coffee is one of the most valuable primary commodities. Despite this, the common selection technique of green coffee beans relies on personnel visual inspection, which is labor-intensive and subjective. Therefore, an efficient way to evaluate the quality of beans is needed. In this paper, we demonstrate a site-independent approach to find site-specific color features of the seed coat in qualified green coffee beans. We then propose two evaluation schemes for green coffee beans based on this site-specific color feature of qualified beans. Due to the site-specific properties of these color features, machine learning classifiers indicate that compared with the existing evaluation schemes of beans, our evaluation schemes have the advantages of being simple, having less computational costs, and having universal applicability. Finally, this site-specific color feature can distinguish qualified beans from different growing sites. Moreover, this function can prevent cheating in the coffee business and is unique to our evaluation scheme of beans.
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