THE START AND EARLY HISTORY OF CHEMOMETRICS:SELECTED INTERVIEWS.PART 1

This is a first foray into the historical start and early years of chemometrics from about 1972 onwards.We have gathered interviews with three originators(Kowalski,Wold and Massart)as well as with aselected group of six other well-known chemometricians who gradually became active in the 1970s(Christie,Clementi,Hopke,Martens,Brown and Deming).The interviews include amongst a host ofsubjective recollections a succinct record of the key historical literature as highlighted by the interviewees'own rankings of‘earliest’and‘best’.A discussion of the most general commonalities in these interviews together with other historicalmaterial is presented in the second part of the paper.     

THE START AND EARLY HISTORY OF CHEMOMETRICS:SELECTED INTERVIEWS.PART 2

This is a first foray into the historical start and early years of chemometrics from about 1972 onwards.We have gathered interviews with three originators(Kowalski,Wold and Massart)as well as with aselected group of six other well-known chemometricians who gradually became active in the 1970s(Christie,Clementi,Hopke,Martens,Brown and Deming).The interviews include amongst a host ofsubjective recollections a succinct record of the key historical literature as highlighted by the interviewees'own rankings of‘earliest’and‘best’.A discussion of the most general commonalities in these interviews together with other historicalmaterial is presented in the second part of the paper.     

Assessment of Water Quality in the Elbe River at Low Water Conditions Based on Factor Analysis

An assessment of water quality measurements during a long‐lasting low water period in the Elbe River is presented. Weekly samples were taken from May to December 2003 at a sampling site in the middle part of the Elbe River. For multivariate data analysis, 34 parameters of 46 samplings were considered. As a result of this analysis, 78% of the variance of the data set is explained by five factors. They can be assigned to the following latent variables: season (37.5%) > tributaries (12.7%) > re‐suspension (10.4%) > discharge (9.4%) > complexation (8.5%). For the investigated sampling site, two key processes were identified as dominating factors on the water quality during low water conditions. First, seasonal phytoplankton development caused changes in redox conditions with consequences for re‐solution of pollutants from sediments. Second, tributaries have a higher impact on the main stream, due to changes in mixing processes. Therefore, in addition to flood investigations, monitoring strategies, and management plans should be developed in order to survey changes in water quality during low water conditions.     

Use of principal components of UAV-acquired narrow-band multispectral imagery to map the diverse low stature vegetation fAPAR

The fraction of absorbed photosynthetically active radiation (fAPAR) is an important plant physiological index that is used to assess the ability of vegetation to absorb PAR, which is utilized to sequester carbon in the atmosphere. This index is also important for monitoring plant health and productivity, which has been widely used to monitor low stature crops and is a crucial metric for food security assessment. The fAPAR has been commonly correlated with a greenness index derived from spaceborne optical imagery, but the relatively coarse spatial or temporal resolution may prohibit its application on complex land surfaces. In addition, the relationships between fAPAR and remotely sensed greenness data may be influenced by the heterogeneity of canopies. Multispectral and hyperspectral unmanned aerial vehicle (UAV) imaging systems, conversely, can provide several spectral bands at sub-meter resolutions, permitting precise estimation of fAPAR using chemometrics. However, the data pre-processing procedures are cumbersome, which makes large-scale mapping challenging. In this study, we applied a set of well-verified image processing protocols and a chemometric model to a lightweight, frame-based and narrow-band (10 nm) UAV imaging system to estimate the fAPAR over a relatively large cultivated land area with a variety of low stature vegetation of tropical crops along with native and non-native grasses. A principal component regression was applied to 12 bands of spectral reflectance data to minimize the collinearity issue and compress the data variation. Stepwise regression was employed to reduce the data dimensionality, and the first, third and fifth components were selected to estimate the fAPAR. Our results indicate that 77% of the fAPAR variation was explained by the model. All bands that are sensitive to foliar pigment concentrations, canopy structure and/or leaf water content may contribute to the estimation, especially those located close to (720 nm) or within (750 nm and 780 nm) the near-infrared spectral region. This study demonstrates that this narrow-band frame-based UAV system would be useful for vegetation monitoring. With proper pre-flight planning and hardware improvement, the mapping of a narrow-band multispectral UAV system could be comparable to that of a manned aircraft system.     

EXPERIMENTAL DESIGN IN CHEMOMETRICS

Chemometrics is defined as the application of mathematical and statistical methods to chemical systems.Systems theory is seen to be useful for organizing and categorizing the inputs to and outputs fromchemical systems.Advances in measurement science in the 1950s and 1960s,particularly in analyticalchemistry,created a need for a multivariate approach to data analysis.Early chemometrics emphasizedthe use of structure-finding methods for existing data sets.In many instances,data sets can be obtainedfrom designed experiments.Such data sets are more likely to contain the desired information and the datacan usually be acquired at less cost.Renewed interest in statistical process control will provide many new,more robust data sets in the future.     

Assessment of Water Quality in the Elbe River at Flood Water Conditions Based on Cluster Analysis,Principle Components Analysis,and Source Apportionment

An assessment of water quality measurements during a spring flood in the Elbe River is presented. Daily samples were taken at a site in the middle Elbe, which is part of the network of the International Commission for the Protection of the Elbe River (IKSE/MKOL). Cluster analysis (CA), principal components analysis (PCA), and source apportionment (APCS apportioning) were used to assess the flood‐dependent matter transport. As a result, three main components could be extracted as important to the matter transport in the Elbe River basin during flood events: (i) re‐suspended contaminated sediments, which led to temporarily increased concentrations of suspended matter and of most of the investigated heavy metals; (ii) water discharge related concentrations of pedogenic dissolved organic matter (DOM) as well as preliminary diluted concentrations of uranium and chloride, parameters with stable pollution background in the river basin; and (iii) abandoned mines, i.e., their dewatering systems, with particular influence on nickel, manganese, and zinc concentrations.     

Spatial distribution of heavy metals in Hong Kong's marine sediments and their human impacts: a GIS-based chemometric approach

A geographic information system (GIS)-based chemometric approach was applied to investigate the spatial distribution patterns of heavy metals in marine sediments and to identify spatial human impacts on global and local scales. Twelve metals (Zn, V, Ni, Mn, Pb, Cu, Cd, Ba, Hg, Fe, Cr and Al) were surveyed twice annually at 59 sites in Hong Kong from 1998 to 2004. Cluster analysis classified the entire coastal area into three areas on a global scale, representing different pollution levels. Backward discriminant analysis, with 84.5% correct assignments, identified Zn, Pb, Cu, Cd, V, and Fe as significant variables affecting spatial variation on a local scale. Enrichment factors indicated that Cu, Cr, and Zn were derived from human impacts while Al, Ba, Mn, V and Fe originated from rock weathering. Principal component analysis further subdivided human impacts and their affected areas in each area, explaining 87%, 84% and 87% of the total variances, respectively. The primary anthropogenic sources in the three areas were (i) anti-fouling paint and domestic sewage; (ii) surface runoff, wastewater, vehicle emissions and marine transportation; and (iii) ship repainting, dental clinics, electronic/chemical industries and leaded fuel, respectively. Moreover, GIS-based spatial analysis facilitated chemometric methods.     

SHORT COMMUNICATION CHEMOMETRIC ASPECTS OF AN ENVIRONMENTAL STUDY

The application of several chemometric topics in connection with an environmental study is described.Atwo-way ANOVA is used to show the irregularity of the distribution of heavy metals in the rural soilsaround a lead smelter.Multivariate statistical methods are also applied to show significant correlationsbetween metals and the wind direction.Principal components analysis and Varimax rotation seem toconfirm the validity of the conclusions.     

A NEW APPROACH TO CONFIRMATION BY INFRARED SPECTROMETRY

In the series of analytical techniques for identification of chemical substances,infrared spectrometrypresents by far the highest information content.However,the information is most complicated too.Itconcerns a multitude of band positions,band intensities and band shapes,which,moreover,can bedisturbed by matrix and other effects.The high redundancy,however,allows conclusions to be made bya qualitative,subjective procedure.IR is often used to prove the equality between a sample and a reference material,e.g.in quality controlof a production process.In forensic control,the question to be answered is mostly not to prove equality,but whether or not the presence of a compound in a sample,e.g.a drug,can be proved.Moreover,testinghas to be performed according to objective rules.To fulfil these requirements,a new retrieval algorithm,the‘Adequate Peaks Search’,is presented.Itconcerns representing the reference spectra by sets of adequate peak positions and the sample spectrumby a set of all peak positions,whereafter the cross-sections of the sample set and the reference sets aredetermined.The concept‘adequate peak’is defined and criteria have been formulated to evaluate theresults into a positive(presence of the analyte is proved) or negative(presence is not proved)conclusion.The detection limit when the Adequate Peaks Search(APS)method was applied was four to seven timeslower than that attained by a number of experts.     

Chemometrics data analysis of marine water quality and source identification in Southern Hong Kong

Various chemometric methods were used to analyze data sets of marine water quality for 19 parameters measured at 16 different sites of southern Hong Kong from 2000 to 2004 (18,240 observations), to determine temporal and spatial variations in marine water quality and identify pollution sources. Hierarchical cluster analysis (CA) grouped the 12 months into three periods (January-April, May-August and September-December) and the 16 sampling sites into two groups (A and B) based on similarities in marine water-quality characteristics. Discriminant analysis (DA) was important in data reduction because it used only eight parameters (TEMP, TURB, Si, NO(3)(-)-N, NH(4)(+)-N, NO(2)(-)-N, DO, and Chl-a) to correctly assign about 86% of the cases, and five parameters (SD, NH(4)(+)-N, TP, NO(2)(-)-N, and BOD(5)) to correctly assign >81.15% of the cases. In addition, principal component analysis (PCA) identified four latent pollution sources for groups A and B: organic/eutrophication pollution, natural pollution, mineral pollution, and nutrient/fecal pollution. Furthermore, during the second and third periods, all sites received more organic/eutrophication pollution and natural pollution than in the first period. SM5, SM6, SM17, SM10, SM11, SM12, and SM13 (second period) were affected by organic and eutrophication pollution, whereas SM3 (third period) and SM9 (second period) were influenced by natural pollution. However, differences between mineral pollution and nutrient/fecal pollution were not significant among the three periods. SM17 and SM10 were affected by mineral pollution, whereas SM4 and SM9 were highly polluted by nitrogenous nutrient/fecal pollution.