基于多指标和多元统计分析的百两金综合质量评价OA北大核心CSTPCD
Comprehensive Quality Evaluation of Ardisia crispa(Thunb.)A.DC.Based on Multiple Indicators and Multivariate Statistical Analysis
基于水分、总灰分、酸不溶性灰分、浸出物、总黄酮、总酚、总皂苷含量共7个检测指标,通过相关性分析、主成分分析、聚类热图分析,以及CRITIC-TOPSIS和CRITIC-灰色关联度评价模型,对7批不同产地的百两金[(Ardisia crispa(Thunb.)A.DC.]开展综合质量评价研究.相关性分析结果表明,7个指标关系密切,信息存在一定重叠;主成分分析共提取总灰分、酸不溶性灰分、浸出物、总皂苷、水分含量5个主要检测指标,累计贡献率达93.293%;CRITIC法对各指标的赋权结果中,浸出物和总皂苷的权重值排名最为靠前,与主成分分析结果基本吻合.2种评价模型均显示了不同产地百两金较大的质量差异,以CRITIC-灰色关联度模型的变异系数较大(42.889 9%),更能反映百两金的质量差异,且与主成分和聚类热图分析结果基本一致.在该模型下,样品BLJ3排名最为靠前,BLJ1、BLJ2、BLJ6、BLJ7排名居中,而BLJ4、BLJ5排名较为靠后.综上所述,7个指标中,浸出物、总皂苷、水分、总灰分、酸不溶性灰分含量5个指标可以作为判断不同产地百两金质量的主要因素,尤其是浸出物、总皂苷含量提供的质量信息较多.2种评价模型中,CRITIC-灰色关联度模型更适用于不同产地的百两金综合质量评价.7批样品中,重庆市彭水县的样品(BLJ3)质量最好,可作为百两金优质种源首选;BLJ1、BLJ2、BLJ6、BLJ7质量居中,可作为备选种源;贵州省贵阳市2个样品(BLJ4、BLJ5)质量较差,在种质资源筛选中需尽量避免.
Based on seven indicators(moisture,total ash,acid-insoluble ash,extract,total flavonoids,total phenols and total saponins content),correlation analysis,principal component analysis,clustering heatmap analysis,CRITIC-TOPSIS and CRITIC-grey relational analysis models were used to comprehensively evaluate the quality of seven batches of Ardisia crispa(Thunb.)A.DC.from different areas.The results of correlation analysis showed close relationship among seven indexes,indicating some overlap of information.Principal component analysis extracted five main indicators,including total ash,acid-insoluble ash,extract,total saponins and moisture content,and the cumulative contribution rate was 93.293% .The weighting results of each indicator based on CRITIC method were basically consistent with principal component analysis,among which the weight values of the extract and total saponins content ranked highest.Both evaluation models showed significant quality differences among the A.crispa samples from different areas,but the coefficient of variation of the CRITIC-grey relational analysis model was larger to 42.889 9%,which better reflected the quality difference of A.crispa.And the results were basically consistent with the principal component and clustering heatmap analysis results.Under this model,sample BLJ3 ranked highest,BLJ1,BLJ2,BLJ6,BLJ7 ranked middle,and BLJ4,BLJ5 ranked lowest.In summary,among the seven indicators,the extract,total saponins,moisture,total ash and acid-insoluble ash content can be used as the main indicators for evaluating the quality of A.crispa from different areas,especially the extract and total saponins content providing the greater quality information.Among the two evaluation models,the CRITIC-grey relational analysis model is more suitable for the comprehensive quality evaluation of A.crispa.Among the seven batches of samples,sample BLJ3 from Pengshui County,Chongqing City is of the best quality,which could be used as the first choice for the high-quality provenances of A.crispa.BLJ1,BLJ2,BLJ6,BLJ7 are of medium quality and can be used as alternative provenances.The quality of the two samples(BLJ4 and BLJ5)from Guiyang,Guizhou Province is poor,which should be avoided as much as possible in the screening of provenances of A.crispa.
胡优琼;姜金香;黄安玲;任志琴;魏升华;王志威
贵州中医药大学 药学院,贵州 贵阳 550002
农业科学
百两金多指标多元统计分析质量评价权重分析法灰色关联度法
Ardisia crispa(Thunb.)A.DC.Multiple indicatorsMultivariate statistical analysisQuality evaluationCriteria importance though intercrieria correlationGrey relational analysis
《河南农业科学》 2024 (008)
51-60 / 10
国家重点研发计划项目(2018YFC1708101);国家自然科学基金地区科学基金项目(32360055,31760053);贵州省研究生科研基金项目(黔教合YJSKYJJ[2021]162);2023年贵州中医药大学研究生教育创新计划项目(YCXKYS2023022)
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