Department of Medicinal Chemistry, School of Pharmacy, Guilan University of Medical Sciences, Rasht, Iran.
Student Research Committee, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Phytochem Anal. 2019 Jul;30(4):405-414. doi: 10.1002/pca.2823. Epub 2019 Feb 19.
In addition to the development of analytical equipment, another movement has also appeared in the field of computer assisted techniques for metabolite assessment. Although, some studies can be found in the literature there is still not available reliable and user-friendly software which is coupled with a simple chromatography method for developing a database to identify medicinal plants.
Developing a novel similarity search approach for high-performance thin-layer chromatography (HPTLC) fingerprinting.
Combined HPTLC with image analysis approach was used for similarity assessment of 70 standard medicinal plants. Ethyl acetate-ethyl methyl ketone-formic acid 98%-water (50:30:10:10) were chosen among different examined mobile phases. Liebermann-Burchard and anisaldehyde reagents were chosen for HPTLC derivatisation for visualisation. Image analysis based on Cannys' method was used to determine the spot size of each HPTLC image. A similarity search algorithm based on colour (RGB, HSV and Lab) information alone or together with retardation factor (R ) and spot size information calculated with the software was built to assess the fingerprinting of medicinal plants.
The software was capable of calculating spots size and R values. It authenticated unknown samples based on comparing images information, spots size and/or R in the built database. Similarity values were 75-96% for the selected plants chromatograms with those of the same plant in the database. It presents better results than principal components analysis (PCA), classification and regression trees (CART) and partial least squares discriminant analysis (PLS-DA).
The procedure paves the way for constructing a database of HPTLC images of medicinal plants.
除了分析设备的发展，在计算机辅助技术领域也出现了另一种用于代谢物评估的方法。虽然文献中可以找到一些研究，但仍然没有可靠且易于使用的软件，该软件与简单的色谱方法相结合，可用于开发识别药用植物的数据库。
开发一种用于高效薄层色谱（HPTLC）指纹图谱的新型相似性搜索方法。
采用 HPTLC 与图像分析相结合的方法，对 70 种标准药用植物进行相似性评估。在所考察的不同流动相中选择了乙酸乙酯-甲乙酮-甲酸 98%-水（50:30:10:10）。选择 Liebermann-Burchard 和茴香醛试剂用于 HPTLC 衍生化以可视化。基于 Cannys 方法的图像分析用于确定每个 HPTLC 图像的斑点大小。建立了一种基于颜色（RGB、HSV 和 Lab）信息的相似性搜索算法，或者与软件计算的保留因子（R）和斑点大小信息一起，用于评估药用植物的指纹图谱。
该软件能够计算斑点大小和 R 值。它通过比较图像信息、斑点大小和/或数据库中相同植物的 R 值来验证未知样品。所选植物色谱与数据库中相同植物的相似度值为 75-96%。它的结果优于主成分分析（PCA）、分类和回归树（CART）和偏最小二乘判别分析（PLS-DA）。
该方法为构建药用植物 HPTLC 图像数据库铺平了道路。
