Multivariate analysis and geochemical investigations of groundwater in a semi-arid region, case of superficial aquifer in Ghriss Basin, Northwest Algeria

This study aims to investigate the hydrochemical characteristics of shallow aquifer in a semi-arid region situated in northwest Algeria,and to understand the major factors governing groundwater quality.The study area is suffering from recurring droughts,groundwater resource over-exploitation and groundwater quality degradation.The approach used is a combination of traditional hydrochemical analysis methods of multivariate statistical techniques,principal component analysis(PCA),and ratios of major ions,based on the data derived from 33 groundwater samples collected in February 2014.Results show that groundwater in the study area are highly mineralized and collectively has a high concentration of chloride(as Cl^(−)).The dominant water types are Na-Cl(27%),Mg-HCO_(3)(24%)and Mg-Cl(24%).According to the(PCA)approach,salinization is the main process that controls the hydrochemical variability.The PCA analysis reveal the impact of anthropogenic factor especially the agricultural activities on the groundwater quality.The PCA highlighted two types of recharge:Superficial recharge from effective rainfall and excess irrigation water distinguished by the presence of nitrate and lateral recharge or vertical leakage from carbonate formations marked by the omnipresence of HCO_(3)^(−).Additionally,three categories of samples were identified:(1)samples characterized by good water quality and receiving notable recharge from carbonate formations;(2)samples impacted by the natural salinization process;and(3)samples contaminated by anthropogenic activities.The major natural processes influencing water chemistry are the weathering of carbonate and silicate rocks,dissolution of evaporite as halite,evaporation and cation exchange.The study results can provide the basis for local decision makers to ensure the sustainable management of groundwater and the safety of drinking water.

STUDY ON THE MULTIVARIATE STATISTICAL ESTIMATION OF TROPICAL CYCLONE INTENSITY USING FY-3 MWRI BRIGHTNESS TEMPERATURE DATA

A technique for estimating tropical cyclone(TC) intensity over the Western North Pacific utilizing FY-3Microwave Imager(MWRI) data is developed. As a first step, we investigated the relationship between the FY-3 MWRI brightness temperature(TB) parameters, which are computed in concentric circles or annuli of different radius in different MWRI frequencies, and the TC maximum wind speed(Vmax) from the TC best track data. We found that the parameters of lower frequency channels' minimum TB, mean TB and ratio of pixels over the threshold TB with a radius of 1.0 or 1.5 degrees from the center give higher correlation. Then by applying principal components analysis(PCA)and multiple regression method, we established an estimation model and evaluated it using independent verification data, with the RMSE being 13 kt. The estimated Vmax is always stronger in the early stages of development, but slightly weaker toward the mature stage, and a reversal of positive and negative bias takes place with a boundary of around 70 kt. For the TC that has a larger error, we found that they are often with less organized and asymmetric cloud pattern, so the classification of TC cloud pattern will help improve the acuracy of the estimated TC intensity, and with the increase of statistical samples the accuracy of the estimated TC intensity will also be improved.

Spatial variation assessment of groundwater quality using multivariate statistical analysis(Case Study:Fasa Plain,Iran)

Groundwater is considered as one of the most important sources for water supply in Iran.The Fasa Plain in Fars Province,Southern Iran is one of the major areas of wheat production using groundwater for irrigation.A large population also uses local groundwater for drinking purposes.Therefore,in this study,this plain was selected to assess the spatial variability of groundwater quality and also to identify main parameters affecting the water quality using multivariate statistical techniques such as Cluster Analysis(CA),Discriminant Analysis(DA),and Principal Component Analysis(PCA).Water quality data was monitored at 22 different wells,for five years(2009-2014)with 10 water quality parameters.By using cluster analysis,the sampling wells were grouped into two clusters with distinct water qualities at different locations.The Lasso Discriminant Analysis(LDA)technique was used to assess the spatial variability of water quality.Based on the results,all of the variables except sodium absorption ratio(SAR)are effective in the LDA model with all variables affording 92.80%correct assignation to discriminate between the clusters from the primary 10 variables.Principal component(PC)analysis and factor analysis reduced the complex data matrix into two main components,accounting for more than 95.93%of the total variance.The first PC contained the parameters of TH,Ca2+,and Mg2+.Therefore,the first dominant factor was hardness.In the second PC,Cl-,SAR,and Na+were the dominant parameters,which may indicate salinity.The originally acquired factors illustrate natural(existence of geological formations)and anthropogenic(improper disposal of domestic and agricultural wastes)factors which affect the groundwater quality.

New Method for Multivariate Statistical Process Monitoring

A new method using discriminant analysis and control charts is proposed for monitoring multivariate process operations more reliably.Fisher discriminant analysis (FDA) is used to derive a feature discriminant direction (FDD) between each normal and fault operations,and each FDD thus decided constructs the feature space of each fault operation.Individuals control charts (XmR charts) are used to monitor multivariate processes using the process data projected onto feature spaces.Upper control limit (UCL) and lower control limit (LCL) on each feature space from normal process operation are calculated for XmR charts,and are used to distinguish fault from normal.A variation trend on an XmR chart reveals the type of relevant fault operation.Applications to Tennessee Eastman simulation processes show that this proposed method can result in better monitoring performance than principal component analysis (PCA)-based methods and can better identify step type faults on XmR charts.

Quality assessment of Jinhongtang Granule using UFLC-MS/MS and multivariate statistical analysis

Jinhongtang is a traditional Chinese medicine formula composed of Rheum palmatum L.stem,Sargentodoxa cuneata stem,and Taraxacum mongolicum and is used for the treatment of sepsis.However,quality assessment method for Jinhongtang is not available.In present study,we developed a UFLC-MS/MS method to determine 16 analytes in 20 batches of home-made and commercial Jinhongtang.Multivariate statistical analysis revealed the significant differences in the quality of home-made and commercial Jinhongtang and the difference in the quality of home-made samples was more significant.The integrated strategy based on UFLC-MS/MS and multivariate statistical analysis provided a new basis for the overall quality assessment of Jinhongtang.

Multivariate Statistical Analysis of Large Datasets: Single Particle Electron Microscopy

Biology is a challenging and complicated mess. Understanding this challenging complexity is the realm of the biological sciences: Trying to make sense of the massive, messy data in terms of discovering patterns and revealing its underlying general rules. Among the most powerful mathematical tools for organizing and helping to structure complex, heterogeneous and noisy data are the tools provided by multivariate statistical analysis (MSA) approaches. These eigenvector/eigenvalue data-compression approaches were first introduced to electron microscopy (EM) in 1980 to help sort out different views of macromolecules in a micrograph. After 35 years of continuous use and developments, new MSA applications are still being proposed regularly. The speed of computing has increased dramatically in the decades since their first use in electron microscopy. However, we have also seen a possibly even more rapid increase in the size and complexity of the EM data sets to be studied. MSA computations had thus become a very serious bottleneck limiting its general use. The parallelization of our programs—speeding up the process by orders of magnitude—has opened whole new avenues of research. The speed of the automatic classification in the compressed eigenvector space had also become a bottleneck which needed to be removed. In this paper we explain the basic principles of multivariate statistical eigenvector-eigenvalue data compression;we provide practical tips and application examples for those working in structural biology, and we provide the more experienced researcher in this and other fields with the formulas associated with these powerful MSA approaches.

Water Quality Assessment of a Tropical Mexican Lake Using Multivariate Statistical Techniques

Water quality of Mexican tropical lake Chapala was assessed through multivariate statistical techniques, cluster analysis (CA) and principal component analysis (PCA) at ten different monitoring sites for ten physicochemical variables and six metals. This study evaluated and interpreted complex water quality data sets and apportioned of pollution sources to get better information about water quality. From descriptive statistics results, the highest concentrations of metals occurred during the dry season, and this trend was explained by the fact that an unusual rainy event occurred during the month of February 2009 and brought metals into the lake by runoffs from nearby mountains. According to international criteria for water consumption by aquatic organisms [USEPA], only Zn concentration values were below these criteria whereas the values of Ni, Pb, Cd and Fe were above the corresponding values set in these criteria (Ni: 52 μg·L-1, Pb: 2.5 μg·L-1, Cd: 0.25 μg·L-1, and Fe: 1000 μg·L-1). The correlations were observed by PCA, which were used to classify the samples by CA, based on the PCA scores. Seven significant cluster groups of sampling locations—(sites 4 and 5), (sites 3 and 9), (site 7), (site 10), (sites 2 and 6), (site 8) and (site 1)— were detected on the basis of similarity of their water quality. The results revealed that the stress exerted on the lake caused by waste sources follows the order: domestic > agricultural > industrial.

Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.

Evaluation of hydro-chemistry in a phreatic aquifer in the Vindhyan Region, India, using entropy weighted approach and geochemical modelling

Groundwater quality monitoring and geochemical characterization in the phreatic aquifer are critical for ensuring universal and equitable access to clean,reliable,and inexpensive drinking water for all.This research was intended to investigate the hydrogeochemical attributes and mechanisms regulating the chemistry of groundwater as well as to assess spatial variation in groundwater quality in Satna district,India.To accomplish this,the groundwater data comprising 13 physio-chemical parameters from thirty-eight phreatic aquifer locations were analysed for May 2020 by combining entropy-weighted water quality index(EWQI),multivariate statistics,geochemical modelling,and geographical information system.The findings revealed that the groundwater is fresh and slightly alkaline.Hardness was a significant concern as 57.89% of samples were beyond the permissible limit of the World Health Organisation.The dominance of ions were in the order of Ca^(2+)> Na^(+)> Mg^(2+)> K^(+) and HCO_(3)^(-)> SO_(4)^(2-)> Cl^-> NO_(3)^(-)> F^(-).Higher concentration of these ions is mainly concentrated in the northeast and eastern regions.Pearson correlation analysis and principal component analysis(PCA) demonstrated that both natural and human factors regulate groundwater chemistry in the region.The analysis of Q-mode agglomerative hierarchical clustering highlighted three significant water clusters.Ca-HCO_3 was the most prevalent hydro-chemical facies in all three clusters.Geochemical modelling through various conventional plots indicated that groundwater chemistry in the research region is influenced by the dissolution of calcite/dolomite,reverse ion exchange,and by silicate and halite weathering.EWQI data of the study area disclosed that 73.69% of the samples were appropriate for drinking.Due to high salinity,Magnesium(Mg^(2+)),Nitrate(NO_(3)^(-)),and Bicarbonate(HCO_(3)^(-)) concentrations,the north-central and north-eastern regions are particularly susceptible.The findings of the study may be accomplished by policymakers and groundwater managers to achieve sustainable groundwater development at the regional scale.

Genetic differentiation in functional traits among wild cherry (Prunus avium L.) half-sib lines

Understanding intra-specific variation in leaf functional traits is one of the key requirements for the evaluation of species adaptive capacity to ongoing climate change, as well as for designing long-term breeding and conservation strategies. Hence, data of 19 functional traits describing plant physiology, antioxidant properties, anatomy and morphology were determined on 1-year-old seedlings of wild cherry (Prunus avium L.) half-sib lines. The variability within and among half-sib lines, as well as the estimation of multi-trait association, were examined using analysis of variance (ANOVA) followed by Tukey's honestly significant difference test and multivariate analyses: principal component analysis (PCA), canonical discriminant analysis (CDA) and stepwise discriminant analysis (SDA). Pearson’s correlation coefficient was used to evaluate linear correlation between the study parameters. The results of the ANOVA showed the presence of statistically significant differences (P < 0.01) among half-sib lines for all study traits. The differences within half-sib lines, observed through the contribution of the examined sources of variation to the total variance (%), had higher impact on total variation in the majority of the examined traits. Pearson’s correlation analysis and PCA showed strong relationships between gas exchange in plants and leaf size and stomatal density, as well as between leaf biomass accumulation, intercellular CO_(2) concentration and parameters related to antioxidant capacity of plants. Likewise, the results of SDA indicate that transpiration and stomatal conductance contributed to the largest extent, to the discrimination of the wild cherry half-sib lines. In addition, PCA and CDA showed separation of the wild cherry half-sib lines along the first principal component and first canonical variable with regards to humidity of their original sites. Multiple adaptive differences between the wild cherry half-sib lines indicate high potential of the species to adapt rapidly to climate change. The existence of substantial genetic variability among the wild cherry half-sib lines highlights their potential as genetic resources for reforestation purposes and breeding programmes.

Quantitative hazard assessment system(Has-Q) for open pit mine slopes

Rock slope hazard assessment is an important part of risk analysis for open pit mines.The main parameters that can lead to rock slope failures are the parameters traditionally used in geomechanical classifications,the slope geometrical parameters and external factors like rainfall and blasting.This paper presents a methodology for a hazard assessment system for open pit mine slopes based on 88 cases collated around the world using principal components analysis,discriminant analysis and confidence ellipses.The historical cases used in this study included copper,gold,iron,diamond,lead and zinc,platinum and claystone mines.The variables used in the assessment methodology are uniaxial compressive strength of intact rock;spacing,persistence,opening,roughness,infilling and orientation of the main discontinuity set;weathering of the rock mass;groundwater;blasting method;and height and inclination of the pit.While principal component analysis was used to quantify the data,the discriminant analysis was used to establish a rule to classify new slopes about its stability condition.To provide a practical hazard assessment system,confidence ellipses were used to propose a hazard graph and generate the HAS-Q.The discriminant rule developed in this research has a high discrimination capacity with an error rate of 11.36%.

Delineation of spring capture zones in southern Great Basin,USA based on modeling results and geochemical data

The protection zones or capture zones of springs in desert environments can be hard to identify,but they are critical to spring protection.Most springs fed by regional aquifers are susceptible to contamination and groundwater development.The U.S.Environmental Protection Agency has established hydrogeologic mapping methods to delineate protection zones for springs.However,it is often difficult to determine a regional aquifer system's flow pattern with this technique alone,and the use of these methods is not conducive to efficient groundwater management.Particle tracking analysis using a well-conceptualized and calibrated numerical model for the three-dimensional groundwater flow domain feeding a given group of springs can help facilitate the identification of spring capture zone boundaries.Building upon this basis,a multifaceted approach was developed to define clear boundaries of the capture zones for the springs in the Furnace Creek,Ash Meadows,and the Muddy River areas in the southern Great Basin,USA.Capture zones were first delineated from inverse particle tracking and Hydrologic Unit 12 watersheds.Afterwards,they were adjusted based on water budgets,geology,and hydrologically significant faults.Finally,a geochemical analysis of the groundwater chemistry and isotopic data was conducted to verify the extent of each spring capture zone.This multifaceted approach adds confidence to the new delineations.

Spatial and statistical assessment of nitrate contamination in groundwater:Case of Sais Basin, Morocco

The objective of this study is to evaluate the nitrate contamination in the plioquaternary aquifer of Sais Basin based on a statistical approach. A total of 98 samples were collected in the cultivated area during the spring and autumn period of 2018. The results show that 55% and 57% of the samples in spring and autumn respectively exceed the threshold fixed by WHO(50 mg/L). However, nitrate concentrations do not show seasonal and spatial variation(p>0.05). The results of the correlation matrix, principal component analysis(PCA), and hierarchical cluster analysis(HCA) suggest that nitrate pollution is related to anthropogenic source. Moreover, multiple linear regression results show that NO3 is more positively explained in the spring period by Ca and SO4 and negatively explained by pH and HCO3. Regarding the autumn period, nitrate pollution is positively explained by Ca and negatively by pH. This study proposes a useful statistical platform for assessing nitrate pollution in groundwater.

Metabolomics-based comparative analysis of the effects of host and environment on Viscum coloratum metabolites and antioxidative activities

Viscum coloratum(Kom.)Nakai is a well-known medicinal hemiparasite widely distributed in Asia.The synthesis and accumulation of its metabolites are affected by both environmental factors and the host plants,while the latter of which is usually overlooked.The purpose of this study was to comprehensively evaluate the effects of host and habitat on the metabolites in V.coloratum through multiple chemical and biological approaches.The metabolite profile of V.coloratum harvested from three different host plants in two habitats were determined by multiple chemical methods including high-performance liquid chromatography-ultraviolet(HPLC-UV),gas chromatography-flame ionization detector(GC-FID)and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry(UPLC-QTOF/MS).The differences in antioxidant efficacy of V.coloratum were determined based on multiple in vitro models.The multivariate statistical analysis and data fusion strategy were applied to analyze the differences in metabolite profile and antioxidant activity of V.coloratum.Results indicated that the metabolite profile obtained by various chemical approaches was simultaneously affected by host and environment factors,and the environment plays a key role.Meanwhile,three main differential metabolites between two environment groups were identified.The results of antioxidant assay indicated that the environment has greater effects on the biological activity of V.coloratum than the host.Therefore,we conclude that the integration of various chemical and biological approaches combined with multivariate statistical and data fusion analysis,which can determine the influences of host plant and habitat on the metabolites,is a powerful strategy to control the quality of semi-parasitic herbal medicine.

The role of graveyards in species conservation and beta diversity:a vegetation appraisal of sacred habitats from Bannu,Pakistan

Graveyards or sacred groves are often places of natural vegetation protected by spiritual believers because of their sacred beliefs and indigenous culture.A study of graveyards was conducted to determine their role in species conservation,community formation,and associated indicators and species composition using multivariate statistical approaches.It was hypothesized that variations in the age of graveyards would give rise to diverse plant communities under the impact of various edaphic and climatic factors.Quantitative ecological techniques were applied to determine various phytosociological attributes.All the data were put in MS Excel for analysis in PCORD and CANOCO softwares for cluster analysis(CA),two-way cluster analysis(TWCA),indicator species analysis and canonical correspondence analysis.CA and TWCA through Sorenson distance measurements identified five major graveyard plant communities:(1)FicusBougainvillea-Chenopodium;(2)Acacia-Datura-Convolvulus;(3)Ziziphus-Vitex-Abutilon;(4)Acacia-Lantana-Salsola;and(5)Melia-Rhazya-Peganum.Species such as Capparis decidua,Herniaria hirsuta,Salvadora oliedes and Populus euphratica were only present inside graveyards rather than outside and advocate the role of graveyards in species conservation.The impact of different environmental and climatic variables plus the age of the graveyards were also assessed for comparison of plant communities and their respective indicator species.The results indicate that higher chlorine concentration,age of graveyards,low soil electrical conductivity,lower anthropogenic activities,higher nitrogen,calcium and magnesium concentrations in the soil,and sandy soils were the strong environmental variables playing a significant role in the formation of graveyard plant communities,their associated indicators and species distribution patterns.These results could further be utilized to evaluate the role of edaphic and climatic factors,indicator species and conservation management practices at a greater scale.

Statistical evaluation of fluoride contamination in groundwater resources of Santiago del Estero Province, Argentina

This study investigates the suitability of statistical techniques for evaluating the fluoride content and the groundwater quality from Robles Department(RD)and Banda Department(BD)in Santiago del Estero(Argentina).For the original statistical study,evaluation of nine parameters(fluoride,pH,conductivity,atmospheric and water temperature,total dissolved solids,chloride,hardness,and alkalinity)of 110 collected underground water samples from 23 dispersed rural areas was proposed.Groundwater samples were obtained by sampling taken from wells at different depths.Fluoride levels were determined by a standard colorimetric method in two seasonal periods,the dry(from April to September)and rainy(from October to March)period.The analytical results obtained for physicochemical parameters such as pH,total dissolved solids(TDS),and temperature does not reveal any notable difference between the rainy and dry seasons studied.In both seasons,the atmospheric temperature average was 22℃.With respect to fluoride content,approximately 50%of the analysed groundwater samples exceeded the limit established by current legislation(1.0 mg/L),obtaining concentration levels in the range of 0.01-2.80 mg/L.This study demonstrates the usefulness of the univariate statistical method(quartiles calculation,interquartile range IQR),multivariate principal component analysis(PCA),and cluster analysis to establish a better understanding of the state of the contamination of the waters in the region studied.

Overall Evaluation on the Level of Rural Economic Development in 31 Regions of China

Taking China Rural Statistical Yearbook in 2008 as the data source, we select 10 indices scientifically and rationally. By using SPSS statistical software, factor analysis method and cluster analysis method in multivariate statistical analysis, we conduct analysis on the level of rural economic development in 31 provinces, municipalities directly under the Central Government, autonomous regions in China. Finally we extract 4 composite factors and offer the overall ranking of them. We divide the 31 regions of China into four types, namely the regions with developed agricultural economy, the regions with relatively developed agricultural economy, the regions with less-developed agricultural economy, and the regions with underdeveloped agricultural economy.

Contribution to the Hydrochemical Study of Groundwater from the Continental Terminal in Saloum

This paper focuses on the study of the aquifer of the Continental Terminal in the south of Saloum river. This study aims to participate in the knowledge of the physicochemical quality and to help understand the origins and processes of the mineralization of the water of the Continental Terminal (CT). Physicochemical treatments show an average pH of 6.61 indicating a slightly acidic water overall. The electrical conductivity varies between 37.4 and 12,320 μS·cm-1 with an average of 729.3 μS·cm-1. High conductivities are recorded around the ocean and the Saloum River, indicating higher mineralized waters in these areas. The geochemical study and multivariate statistical analysis indicate three groups of the sampled waters. Group 1 is mainly formed of the Ca-HCO3, Na-HCO3, Ca-Cl and Na-Cl facies. This group is the most common one and is found throughout the southern Saloum area. Group 2, mainly made up of the Ca-HCO3 and Na-HCO3 facies, is located in the center, east, west and north of the zone. The mineralization of these two groups is believed to be of carbonate, evaporitic and/or anthropogenic origin. Group 3 is formed from the Na-Cl facies. This group is located in the north and west of the area (near the ocean and the Saloum river). This group 3 suggests pollution of marine and anthropogenic origin. The calculated base indices suggest cationic exchanges between the waters and the formations of the water table of the terminal continental.

Assessment of spatial and seasonal water quality variation of Oum Er Rbia River(Morocco)using multivariate statistical techniques

The aim of this study is to assess the spatial and temporal water quality variation and to determine the main contamination sources in the Oum Er Rbia River and its main tributary,El Abid River.The water quality data were collected during 2000-2012 from fourteen sampling stations distributed along the river.The water quality indicators used were TEMP,pH,EC,turbidity,TSS,DO,NH_(4)^(+),NH_(3)^(-),TP,BOD5,COD and F.coli.The water quality data was analyzed using multivariate statistical methods including Pearson's correlation,PCA,and CA.The results showed that in some stations the water quality parameters were over Moroccan water standards.PCA applied to compare the compositional patterns among the analyzed water samples,identified and four factors accounting for almost 63% of the total variation in the data.This suggests that the variations in water compounds’concentration are mainly related to point source contamination(domestic and industrial wastewater),non-point source contamination(agriculture activities),as well as natural processes(weathering of soil and rock).CA showed relatively spatial and seasonal changes in surface water quality,which are usually indicators of contamination with rainfalls or other sources.Overall,this study showed that the water was potentially hazardous to health of the consumers and highlighted the need to treat industrial and municipal wastewater and to encourage sustainable agricultural practices to prevent adverse health effects.We therefore suggest wise management of anthropogenic activities in the catchment of Oum Er Bia River and their tributaries.

Chemical comparison of dried rehmannia root and prepared rehmannia root by UPLC-TOF MS and HPLC-ELSD with multivariate statistical analysis

To identify the chemical differences which lead to the different therapeutic effects of dried rehmannia root(DRR)and prepared rehmannia root(PRR),we compared the chemical composition of decoctions of randomly purchased DRR and PRR using ultra performance liquid chromatography(UPLC)coupled with time-of-fight mass spectrometry and high performance liquid chromatography(HPLC)coupled with evaporative light scattering detection(ELSD)with the aid of multivariate statistical analysis.Both approaches clearly revealed compositional and quantitative differences between DRR and PRR.UPLC-MS data indicated stachyose,rehmaiono-side A(or rehmaionoside B),acteoside(or forsythiaside,or isoacteoside),6-O-coumaroylajugol(or 6-O-E-feruloylajugol,or 6-O-Z-feruloylajugol)as important discriminators between DRR and PRR decoctions.HPLC-ELSD analysis showed that the content of fructose in the decoctions of PRR was about four times greater than that of DRR(P<10^(-5)),while sucrose content in the decoctions of PRR was only about one seventh of that in DRR(P<0.01).Our results suggest that some compounds,such as fructose,stachyose and rehmaionoside,may be responsible for the differing therapeutic effects of DRR and PRR.Furthermore,improvements in quality control for PRR,which is currently lacking in the Chinese Pharmacopoeia,are recommended.