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快速确定红色四川胡 (Zanthoxylum bungeanum) 的地理真实性和刺痛强度,使用微分脉冲电压测量和机器学习算法

Di Zhang¹, Zitao Lin¹, Lilei Xuan¹

¹School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.

|December 4, 2023

概括

这项研究开发了一种使用微分脉冲电量计 (DPV) 和机器学习的方法,以确定Zanthoxylum bungeanum pericarp (PZB) 的起源和尖性. 该方法在原产地识别方面实现了100%的准确性,在改检测方面达到97.9%.

科学领域:

分析化学分析化学
食品科学食品科学食品科学
化学测量化学测量化学测量

背景情况:

由于视觉上的相似性,Zanthoxylum bungeanum pericarp (PZB) 的质量评估具有挑战性.
准确地确定地理来源和刺强度对于PZB质量控制至关重要.
现有的方法可能无法充分区分视觉上相似的PZB样本.

研究的目的:

开发一种分析方法来评估PZB的尖性和地理来源.
为了识别PZB样本中的改.
为PZB建立一个可靠的质量评估工具.

主要方法:

分析了来自中国的14个来源的210个PZB样本.
微分脉冲电量计 (DPV) 的应用,用于电化学分析.
利用机器学习算法,包括人工神经网络 (ANN) 和K-最近邻居 (KNN).

主要成果:

ANN和KNN在原产地识别方面实现了100%的准确性,在改检测方面达到97.9%的准确性.
安恩准确地预测了PZB的尖强度,R2 = 0.918.8.
DPV特征分析确定了多和胺为PZB敏性的关键贡献者.

结论:

与机器学习相结合的DPV提供了可靠的PZB质量评估方法.
这种方法可以有效地确保Zanthoxylum bungeanum pericarp.的地理真实性.
这些发现为PZB行业的质量控制提供了有希望的解决方案.

关键词:

奸淫的行为奸淫的行为微分脉冲电压测量微分脉冲电压测量原产地原产地起源刺痛的强度是刺痛的强度.四川的胡,就是四川胡.

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