Abstract In the current article, an overview of recent applications and opportunities of image evaluation of high-performance thin-layer chromatograms (HPTLC) in food analysis and natural product research is presented. The article shortly covers the aspects of specialized software packages for image analysis, image post-correction, signal acquisition, and preprocessing. Contemporary aspects of image-based HPTLC fingerprinting, quantification of target compounds, and advanced chemometric modeling were reviewed. Special attention was dedicated to freely available software packages. Advantages and disadvantages of each one were discussed in terms of abilities to obtain chromatographic profiles and perform crucial steps in signal manipulation, such as background subtraction, denoising, and background detrending. The most frequently applied techniques for signal manipulation have been discussed and recommendation provided. In that sense, the article aims to provide a valuable guideline for readers dealing with the application of HPTLC image analysis in food and natural products research, especially in connection with the most frequently used chemometric techniques, in domains of pattern recognition, classification, and regression. Graphical Abstract

中文翻译：

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HPTLC 色谱图图像评估的最新趋势

摘要 在本文中，概述了高性能薄层色谱 (HPTLC) 在食品分析和天然产品研究中的图像评估的最新应用和机会。本文简要介绍了用于图像分析、图像后校正、信号采集和预处理的专用软件包的各个方面。回顾了基于图像的 HPTLC 指纹、目标化合物的量化和高级化学计量模型的现代方面。特别关注免费提供的软件包。从获得色谱图谱和执行信号处理中的关键步骤（如背景减除、去噪和背景去趋势）的能力方面讨论了每种方法的优缺点。已经讨论了最常用的信号处理技术并提供了建议。从这个意义上说，本文旨在为处理 HPTLC 图像分析在食品和天然产品研究中的应用的读者提供有价值的指导，尤其是在模式识别、分类和回归领域中最常用的化学计量技术方面。 . 图形概要