VideometerLab4 多光谱成像系统

热点

采用多光谱成像技术对阿拉比卡咖啡豆和罗布斯塔咖啡豆进行了鉴别。

外部验证的判别模型实现了100%的正确分类。

回归模型检测到了阿拉比卡豆与罗布斯塔掺假。

多光谱成像可以用作快速筛查工具。

摘要

阿拉比卡咖啡豆的售价是罗布斯塔咖啡豆的两倍或更高，因此容易受到出于经济动机的替代掺假。需要快速、无损和高效的分析技术来监控供应链中阿拉比卡咖啡豆的真实性。在这项研究中，多光谱成像（MSI）被应用于鉴别烘焙的阿拉比卡咖啡豆和罗布斯塔咖啡豆，并对阿拉比卡咖啡豆与罗布斯塔的掺假进行定量预测。

正交偏最小二乘鉴别分析（OPLS-DA）模型，使用从单个咖啡豆中选择的光谱和形态特征建模，在测试数据集中实现了两种咖啡品种100%的正确分类。OPLS回归模型能够成功预测阿拉比卡与罗布斯塔的掺假水平。MSI分析有可能成为一种快速筛选工具，用于检测与阿拉比卡咖啡豆真伪相关的欺诈问题。

关键词

多光谱成像

阿拉比卡咖啡

罗布斯塔咖啡

真实性

掺假

替代

The use of multispectral imaging for the discrimination of Arabica and Robusta coffee beans 

Highlights

Multispectral imaging was used to discriminate Arabica and Robusta coffee beans.

Externally validated discriminative model achieved 100% correct classification.

Regression model allowed detection of Arabica bean adulteration with Robusta.

Multispectral imaging can be used as a rapid screening tool.

Abstract

Arabica coffee beans are sold at twice the price, or more, compared to Robusta beans and consequently are susceptible to economically motivated adulteration by substitution. There is a need for rapid, non-destructive, and efficient analytical techniques for monitoring the authenticity of Arabica coffee beans in the supply chain. In this study, multispectral imaging (MSI) was applied to discriminate roasted Arabica and Robusta coffee beans and perform quantitative prediction of Arabica coffee bean adulteration with Robusta.

The Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) model, built using selected spectral and morphological features from individual coffee beans, achieved 100% correct classification of the two coffee species in the test dataset. The OPLS regression model was able to successfully predict the level of adulteration of Arabica with Robusta. MSI analysis has potential as a rapid screening tool for the detection of fraud issues related to the authenticity of Arabica coffee beans. 

Keywords

multispectral imaging 

Arabica coffee

Robusta coffee

authenticity

adulteration

substitution

Figure 1. MSI analysis of individual coffee beans: A – coffee beans with marked regions of interest (ROIs); B – individual Arabica (top) and Robusta (bottom) beans extracted from the Petri dish using the BLOB tool.

Figure 2. Mean raw reflectance spectra of Arabica (n=105) and Robusta (n=70) coffee bean samples.

Figure 3. Representative MSI images of 100% Arabica (A), 100% Robusta (B) and 50% Arabica (C, left) + 50% Robusta (C, right) beans with masked background; and the respective nCDA images (A1-C1).

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