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Quality evaluation of Hanyuan Zanthoxylum bungeanum Maxim. Using computer vision system combined with artificial neural network: A novel method

机译:汉源花椒的质量评价。计算机视觉系统与人工神经网络结合使用的新方法

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摘要

A novel technology based on computer vision system (CVS) and artificial neural network (ANN) was developed for the quality evaluation of Hanyuan Zanthoxylum bungeanum Maxim (HZB). The quality evaluation of HZB mainly depended on its colour, odour substances, and impurities. In this study, the contents of volatile oil (VOC), total alkylamides (TALC) and impurities (IMC) were determined and used as indices for quality control of HZB. Furthermore, CVS was also performed to determine the colour parameters (RGB values) and further transforms to CIE L*, a(*,) and b*. Then, ANN was carried out to analyse the correlations between colour values obtained by CVS and quality parameters of HZB (VOC, TALC, and IMC). Higher performance and stability were presented by using CVS for determining the coloristic values of HZB. In addition, the present results also showed that the established method based on ANN could be used to predict the VOC, TALC, and IMC of HZB with the R-2 values of 0.9991, 0.9995, and 0.9998, respectively. This novel technology based on CVS combined with ANN could be used for the rapid, non-destructive, and effective evaluation of the quality of HZB.
机译:开发了一种基于计算机视觉系统(CVS)和人工神经网络(ANN)的新技术,用于汉源花椒(HZB)的质量评价。 HZB的质量评估主要取决于其颜色,气味物质和杂质。本研究测定了挥发油(VOC),总烷基酰胺(TALC)和杂质(IMC)的含量,并将其用作HZB质量控制的指标。此外,还执行了CVS以确定颜色参数(RGB值),并进一步转换为CIE L *,a(*)和b *。然后,采用人工神经网络分析通过CVS获得的颜色值与HZB的质量参数(VOC,TALC和IMC)之间的相关性。通过使用CVS确定HZB的色度值,可以提供更高的性能和稳定性。此外,目前的结果还表明,基于ANN的已建立方法可用于预测HZB的VOC,TALC和IMC,R-2值分别为0.9991、0.9995和0.9998。基于CVS和ANN的这项新技术可用于快速,无损且有效地评估HZB的质量。

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