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A Review on Robust Computational Approaches Based Identification and Authentication of Herbal Raw Drugs
Letters in Drug Design & Discovery ( IF 1 ) Pub Date : 2020-08-31 , DOI: 10.2174/1570180817666200304125520
Preet Amol Singh 1 , Neha Bajwa 1 , Subh Naman 1 , Ashish Baldi 1
Affiliation  

Background: Over the last decade, there has been a sudden rise in the demand for herbal as well as Information and Technology (IT) industry around the world. Identification of plant species has become useful and relevant to all the members of the society including farmers, traders, hikers, etc. Conventional authentication techniques such as morphological characterization, histological methods, and optical microscopy require multiple skills which are tedious, timeconsuming and difficult to learn for non-experts. This creates a hurdle for individuals interested in acquiring knowledge of species. Relying on rapid, economical and computerized approaches to identify and authenticate medicinal plants has become a recent development.

Objective: The purpose of this review is to summarize artificial intelligence-based technologies for wider dissemination of common plant-based knowledge such as identification and authentication to common people earlier limited to only experts.

Methods: A robust plant identification design enabling automated plant-organ and feature-based identification utilizing pattern recognition and image processing techniques resulting in image retrieval and recognition has been highlighted in this review for all the concerned stakeholders. Attempts have been made to compare conventional authentication methods with advanced computerized techniques to emphasize the advantages and future applications of an automated identification system in countering adulteration and providing fair trade opportunities to farmers.

Results: Major findings suggested that microscopical features such as shape and size of calcium oxalate crystals, trichomes, scleriods, stone cells, fibers, etc. are the essential descriptors for identification and authentication of herbal raw drugs using computational approaches.

Conclusion: This computational design can be successfully employed to address quality issues of medicinal plants. Therefore, computational techniques proved as a milestone in the growth of agriculture and medicinal plant industries.



中文翻译:

基于鲁棒计算方法的中草药原料药识别与鉴定研究进展

背景:在过去的十年中,全球对草药以及信息技术(IT)行业的需求突然增加。植物种类的识别已变得有用,并与包括农民,商人,远足者等在内的社会所有成员相关。传统的鉴定技术,例如形态表征,组织学方法和光学显微镜,要求多种技能,这些技能繁琐,耗时且难以掌握。向非专家学习。这为有兴趣获取物种知识的个人带来了障碍。依靠快速,经济和计算机化的方法来鉴定和鉴定药用植物已成为最近的发展。

目的:这篇综述的目的是总结基于人工智能的技术,以更广泛地传播基于植物的常识,例如对仅限于专家的普通人进行识别和认证。

方法:在本综述中,针对所有相关利益方强调了一种可靠的植物识别设计,该设计能够利用模式识别和图像处理技术进行植物器官和特征的自动识别,从而实现图像检索和识别。已经尝试将传统的认证方法与先进的计算机技术进行比较,以强调自动识别系统在对抗掺假和为农民提供公平贸易机会方面的优势和未来的应用。

结果:主要发现表明,草酸钙晶体,毛状体,菌毛,石细胞,纤维等的微观特征是使用计算方法对草药原料药进行鉴定和鉴定的基本描述。

结论:该计算设计可成功用于解决药用植物的质量问题。因此,计算技术被证明是农业和药用植物产业发展的里程碑。

更新日期:2020-08-31
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