Suppr超能文献

基于指示位移比色传感器阵列与机器学习的六安瓜片茶采摘期智能识别。

Intelligent identification of picking periods of Lu'an Guapian tea by an indicator displacement colorimetric sensor array combined with machine learning.

机构信息

Hunan Key Lab of Biomedical Materials and Devices, College of Life Sciences and Chemistry, Hunan University of Technology, Zhuzhou 412007, China; State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.

Hunan Key Lab of Biomedical Materials and Devices, College of Life Sciences and Chemistry, Hunan University of Technology, Zhuzhou 412007, China.

出版信息

Food Res Int. 2024 Nov;195:114960. doi: 10.1016/j.foodres.2024.114960. Epub 2024 Aug 22.

Abstract

Lu'an Gua Pian (LAGP) tea is one of the most famous green teas in China. The quality of green tea is related to its picking periods, especially the green tea before Qingming Festival (usually April 6th) is highly praised as precious in the market. In this work, a simple and cheap indicator displacement colorimetric sensor array combined with smartphone was developed to rapidly identify LAGP picked during different picking periods. First, the chemical component contents of LAGP picked before and after Qingming Festival were analyzed. Second, a well-designed colorimetric sensor array was proposed based on the tea component contents differences. Finally, machine learning was used to process the array data taken by a smartphone. By comparison, the accuracy of the best model for the prediction set was 97%. Meanwhile, the multi-channel advantages of the sensing array were demonstrated by an ablation experiment. In addition, the method achieved an AGREE analysis score of 0.88, indicating that it was environmental-friendly.

摘要

六安瓜片(LAGP)茶是中国最著名的绿茶之一。绿茶的质量与其采摘期有关,特别是清明节前(通常为 4 月 6 日)采摘的绿茶在市场上备受推崇。在这项工作中,我们开发了一种简单廉价的指示剂位移比色传感器阵列,并结合智能手机,快速识别不同采摘期的 LAGP。首先,分析了清明前后采摘的 LAGP 的化学成分含量。其次,根据茶叶成分含量的差异,提出了一种精心设计的比色传感器阵列。最后,利用智能手机采集的阵列数据进行机器学习处理。通过比较,预测集最佳模型的准确率为 97%。同时,通过消融实验证明了传感阵列的多通道优势。此外,该方法的 AGREE 分析评分达到 0.88,表明其具有环保性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验