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Mathematical approach to analysis of therapeutic properties of four important flowers mentioned in Siribhoovalaya- An ancient Indian multilingual manuscript
Indian Journal of Traditional Knowledge ( IF 0.7 ) Pub Date : 2020-12-23
A Padmashree, Hamsapriye, G S Nagananda, S Sandeep, S Swetha

Pushpayurveda is considered to be a unique branch of ayurvedic medicine which was first conceived by Jain monks as early as 9th century. Various ancient Indian manuscripts contain notes about the use of flowers for medicinal applications. The petals of flowers could be directly administered orally or can be made into the form of juice, decoction and or by mixing with other active ingredients. ‘Siribhoovalaya’, a multilingual literature written by Jain monk Kumudendu muni mentions the application of eight important flowers for the purification of mercury. In the present study, the antibacterial and antioxidant analysis of extracts of four of the eight mentioned flowers- Panasa, Padari, Kedige, Krishnapushpa was carried out. The results of antioxidant analysis were studied in detail with the help of modern mathematical software MATHEMATICA. Combination of all four flowers was found to be effective against B. cereus, S. aureus and S. marcescenes. The antioxidant activity was found reduced when a combination of the four flowers were used. The extract of Ketaki showed significantly higher antioxidant activity compared to all the other extracts. The whole study is carried out based on the standard tests of hypotheses, using ANOVA and the correlation effect is studied using regression models.

中文翻译:

Siribhoovalaya(一种古老的印度多语言手稿)中提到的四种重要花卉的治疗特性分析的数学方法

Pushpayurveda被认为是阿育吠陀医学的一个独特分支,最早由mon那教僧侣于9日提出。世纪。各种古代印度手抄本都包含有关将花用于医疗用途的注释。花的花瓣可以直接口服,也可以制成果汁,水煎汤的形式,或与其他活性成分混合制成。in那教和尚Kumudendu muni撰写的多语种文学作品《 Siribhoovalaya》中提到了八种重要花卉在汞净化中的应用。在本研究中,对八种提到的花中的四种(Panasa,Padari,Kedige,Krishnapushpa)的提取物进行了抗菌和抗氧化分析。在现代数学软件MATHEMATICA的帮助下,对抗氧化剂的分析结果进行了详细的研究。发现所有四朵花的组合均有效对抗蜡状芽孢杆菌金黄色葡萄球菌marcescenes。当使用四朵花的组合时,发现抗氧化剂活性降低。与所有其他提取物相比,Ketaki的提取物显示出明显更高的抗氧化活性。整个研究是基于假设的标准检验,使用ANOVA进行的,并且使用回归模型研究了相关效果。
更新日期:2020-12-23
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