尼日利亚Ogbomoso一些粉末药材的比色分析

Q4 Economics, Econometrics and Finance Journal of Medicinal Plants for Economic Development Pub Date : 2019-10-01 DOI:10.4102/jomped.v3i1.68
A. Ogunkunle, J. E. Ideh
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Their colours were digitised by scanning the surface of the powders in petri dishes using a CamScanner installed on a Samsung Galaxy Tablet 10.1 Model 7500, and were qualitatively and quantitatively analysed by uploading the images into the online Cool Hypertext Preprocessor (Cool PHP) software tool, setting the number of colours at five, thus giving consideration to only five dominant colour shades in each image, all expressed as hexadecimal codes. The codes were uploaded into Chir.ag/art, another online tool, to read off the colour names. The relative mean percentage, frequency and relative colour intensity (RCI) of each colour shade were calculated, and the colour with the highest RCI was taken as the first or typical colour of each herb.Results: Nine of the 62 colours observed, namely Lucky, Sandrift, Cannon Pink, Potters Clay, Mandalay, Ferra, Domino, Russet and Roti, were highly restricted in distribution, each being the first or typical colour in only one species of the herbs (i.e. Enantia chlorantha, Garcinia kola, Hibiscus sabdariffa, Khaya senegalensis, Sarcocephalus latifolius, Sorghum bicolor, Theobroma cacao, Uvaria chamae and Zanthoxylum zanthoxyloides respectively). These colours were therefore substantially diagnostic of those herbs. Another nine colours among the most frequently observed colours and the number of species that had them were Pesto (9), Shadow (8), Driftwood (8), Barley Corn (5), Domino (4), Roman Coffee (4), Cape Palliser (4), Himalaya (4) and Husk (4); these were less diagnostic of the herbs in question. Based on the distribution of these colours, a diagnostic PHP colour chart was constructed for the authentication of the powdered medicinal herbs.Conclusion: Powders of the 17 medicinal herbs analysed have been characterised colourimetrically with each species being unambiguously diagnosed. 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引用次数: 0

摘要

背景:草药的感官评价与科学一样古老,但基于其荧光特性对草药进行鉴定是困难的,有时是不可行的,因为人类受到其颜色识别感的限制。目的:本文对一些粉末状草药材料进行了计算机辅助检查,以期对其进行热量测定,从而为其鉴定提供可靠的感官线索,防止可能的误认。背景:研究在尼日利亚Ogbomoso进行。方法:收集用于两种传统粉末药物的17种草药材料(即茎皮、根/根皮、藤本、果盏、叶鞘和种子),并将其粉碎。通过使用安装在三星Galaxy Tablet 10.1 Model 7500上的CamScanner在培养皿中扫描粉末表面,对其颜色进行数字化,并通过将图像上传到在线Cool超文本预处理器(Cool PHP)软件工具中进行定性和定量分析,将颜色数量设置为5,从而在每个图像中只考虑五种主要色调,所有色调都表示为十六进制代码。这些代码被上传到另一个在线工具Chir.ag/art中,用来读取颜色名称。计算每种颜色阴影的相对平均百分比、频率和相对颜色强度(RCI),并将RCI最高的颜色作为每种草药的第一种或典型颜色。结果:观察到的62种颜色中有9种,即Lucky、Sandrift、Cannon Pink、Potters Clay、Mandalay、Ferra、Domino、Russet和Roti,在分布上受到高度限制,每一种都是仅一种草本植物的第一或典型颜色(即分别为埃南蒂亚、藤黄、木槿、卡亚塞内加尔、宽叶Sarcoccephalus latifolis、双色高粱、可可豆、乌花菜和花椒)。因此,这些颜色基本上可以诊断出这些草药。在最常见的颜色和拥有这些颜色的物种数量中,还有9种颜色是Pesto(9)、Shadow(8)、Driftwood(8),Barley Corn(5)、Domino(4),Roman Coffee(4)、Cape Palliser(4)和Himalaya(4)以及Husk(4);这些对所讨论的草药诊断能力较弱。基于这些颜色的分布,构建了用于粉末药材鉴定的诊断PHP颜色图。结论:对所分析的17种药材的粉末进行了色度表征,每种药材都能明确诊断。因此,本研究避开了中药鉴定中人类颜色识别意识的主观性。
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Colourimetric analysis of some powdered medicinal herbs from Ogbomoso, Nigeria
Background: The organoleptic evaluation of herbal drugs is as old as science, but the authentication of herbs on the basis of their fluorescence characteristics is difficult and sometimes impracticable because humans are limited by their sense of colour recognition.Aim: This article undertakes a computer-aided examination of some powdered herbal materials with a view to characterising them calourimetrically, thus providing a reliable organoleptic clue for their authentication, against possible misidentification.Setting: Research was conducted in Ogbomoso, Nigeria.Methods: Seventeen herbal materials (i.e. stem bark, root/root bark, vines, fruit calyx, leaf sheath and seed) used for two traditional powdered drugs were collected and pulverised into powders. Their colours were digitised by scanning the surface of the powders in petri dishes using a CamScanner installed on a Samsung Galaxy Tablet 10.1 Model 7500, and were qualitatively and quantitatively analysed by uploading the images into the online Cool Hypertext Preprocessor (Cool PHP) software tool, setting the number of colours at five, thus giving consideration to only five dominant colour shades in each image, all expressed as hexadecimal codes. The codes were uploaded into Chir.ag/art, another online tool, to read off the colour names. The relative mean percentage, frequency and relative colour intensity (RCI) of each colour shade were calculated, and the colour with the highest RCI was taken as the first or typical colour of each herb.Results: Nine of the 62 colours observed, namely Lucky, Sandrift, Cannon Pink, Potters Clay, Mandalay, Ferra, Domino, Russet and Roti, were highly restricted in distribution, each being the first or typical colour in only one species of the herbs (i.e. Enantia chlorantha, Garcinia kola, Hibiscus sabdariffa, Khaya senegalensis, Sarcocephalus latifolius, Sorghum bicolor, Theobroma cacao, Uvaria chamae and Zanthoxylum zanthoxyloides respectively). These colours were therefore substantially diagnostic of those herbs. Another nine colours among the most frequently observed colours and the number of species that had them were Pesto (9), Shadow (8), Driftwood (8), Barley Corn (5), Domino (4), Roman Coffee (4), Cape Palliser (4), Himalaya (4) and Husk (4); these were less diagnostic of the herbs in question. Based on the distribution of these colours, a diagnostic PHP colour chart was constructed for the authentication of the powdered medicinal herbs.Conclusion: Powders of the 17 medicinal herbs analysed have been characterised colourimetrically with each species being unambiguously diagnosed. The study has therefore circumvented the subjectivity of the human sense of colour recognition in medicinal herb authentication.
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来源期刊
Journal of Medicinal Plants for Economic Development
Journal of Medicinal Plants for Economic Development Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
0.90
自引率
0.00%
发文量
14
审稿时长
32 weeks
期刊最新文献
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