Excitation-emission fluorescence

The physical basis of spectroscopy is the interaction of light with matter. The main types of interaction of electromagnetic radiation with matter are absorption, reflection, excitation-emission (fluorescence, phosphorescence, luminescence), scattering, diffraction, and photochemical reaction (absorbance and bond breaking). Radiation damage may occur. Traditionally, spectroscopy is the measurement of light intensity... 

Multiway methods For analyzer data where a single sample generates a second order array (ex. GC/MS, LC/UV, excitation/emission fluorescence), multiway chemometric modehng methods, such as PARAFAC (parallel factor analysis) [121,122], can be used to exploit the second order advantage to perform effective calibration transfer and instrument standardization. 

There are several other chemometric approaches to calibration transfer that will only be mentioned in passing here. An approach based on finite impulse response (FIR) filters, which does not require the analysis of standardization samples on any of the analyzers, has been shown to provide good results in several different applications.81 Furthermore, the effectiveness of three-way chemometric modeling methods for calibration transfer has been recently discussed.82 Three-way methods refer to those methods that apply to A -data that must be expressed as a third-order data array, rather than a matrix. Such data include excitation/emission fluorescence data (where the three orders are excitation wavelength, emission wavelength, and fluorescence intensity) and GC/MS data (where the three orders are retention time, mass/charge ratio, and mass spectrum intensity). It is important to note, however, that a series of spectral data that are continuously obtained on a process can be constructed as a third-order array, where the three orders are wavelength, intensity, and time. 

There are two competing and equivalent nomenclature systems encountered in the chemical literature. The description of data in terms of ways is derived from the statistical literature. Here a way is constituted by each independent, nontrivial factor that is manipulated with the data collection system. To continue with the example of excitation-emission matrix fluorescence spectra, the three-way data is constructed by manipulating the excitation-way, emission-way, and the sample-way for multiple samples. Implicit in this definition is a fully blocked experimental design where the collected data forms a cube with no missing values. Equivalently, hyphenated data is often referred to in terms of orders as derived from the mathematical literature. In tensor notation, a scalar is a zeroth-order tensor, a vector is first order, a matrix is second order, a cube is third order, etc. Hence, the collection of excitation-emission data discussed previously would form a third-order tensor. However, it should be mentioned that the way-based and order-based nomenclature are not directly interchangeable. By convention, order notation is based on the structure of the data collected from each sample. Analysis of collected excitation-emission fluorescence, forming a second-order tensor of data per sample, is referred to as second-order analysis, as compared with the three-way analysis just described. In this chapter, the way-based notation will be arbitrarily adopted to be consistent with previous work. 

Any analytical data obtained by hyphenated instruments or by two-way spectroscopic techniques such as excitation-emission fluorescence spectroscopy are bilinear ones. The bilinear data matrix has a very useful property, namely the rank of such matrix obtained with any chemical mixture is equal to the number of chemical components in the mixture. Thus, theoretically, the rank of a data matrix of any pure chemical component is unit. It can be expressed by the product of two vectors ... 

Another development, also with a history in chemistry, is second-order calibration, where rank annihilation was developed for analyzing data from typically hyphenated instruments. This includes excitation-emission fluorescence spectra of different samples, liquid chromatography with ultraviolet (UV) detection for different samples and gas chromatography with mass spectrometric detection for different samples, giving an array. An illustration is given in Figure 10.2. 

Trilinearity in the underlying model can be assumed, e.g., when the output from a chromatograph is subjected to excitation-emission fluorescence measurement in the low-concentration range. In this case, the underlying model is often low-rank trilinear, the data produced for one sample are trilinear and a PARAFAC model separates the data uniquely into unit chromatograms, unit excitation spectra and unit emission spectra as A-, B- and C-loadings. 

Beltran JL, Ferrer R, Guiteras J, Multivariate calibration of polycyclic aromatic hydrocarbon mixtures from excitation-emission fluorescence spectra, Analytica Chimica Acta, 1998a, 373, 311-319. 

Sensor types ISE, QCM, SAW, single-X spectroscopy sensor arrays (QCM, SAW, ISE) multi-X spectroscopy, mass spectrometry, chromatography GC-MS excitation-emission- fluorescence... 

Important applications of Af-PLS are in the area of multivariate calibrations for excitation/emission fluorescence spectrometry, for hyphenated analytical methods, such as HPLC/diode array detection and GC/MS, or for multidimensional separation techniques with or without coupling to spectroscopy. 

Guimet et al. used two potential multiway methods for the discrimination between virgin olive oils and pure olive oils the unfold principal component analysis (U-PCA) and parallel factor analysis (PARAFAC), for the exploratory analysis of these two types of oils. Both methods were applied to the excitation-emission fluorescence matrices (EEM) of olive oils and followed the comparison of the results with the ones obtained with multivariate principal component analysis (PCA) based on a fluorescence spectrum recorded at only one excitation wavelength. 

Figure 1 Synchronous excitation/emission fluorescence spectra. (Reproduced with permission from Kelly CA, Law RJ, and Emerson HS (2000) Methods for the analysis of hydrocarbons and polycyclic aromatic hydrocarbons (PAH) in marine samples. Aquatic Environmental Protection Analytical Methods, CEFAS Lowestoft 12, 18pp. British Crown.)...

Patel-Sorrentino, N., S. Mounier, and J. Y. Benaim. 2002. Excitation-emission fluorescence matrix to study pH influence on organic matter fluorescence in the Amazon basin rivers. Water Research 36, no. 10 2571-2581. doi 10.1016/S0043-1354(01)00469-9. 

Raman scatter, and excitation emission fluorescence spectroscopy (EEFS). They use interaction with radiation from different regions of the electromagnetic spectrum to identify the chemical nature of molecules. For example, absorption of UV and VIS radiation causes valence electron transitions in molecules which can be used to measure species down to parts per million concentrations for fluorophores (i.e., EEFS) determination can even go down to parts per billion levels. Whereas UV, VIS, and EEFS are limited to a smaller, select group of molecules, the NIR, IR, and Raman scatter spectroscopy techniques are probing molecular vibrations present in almost any species their quantification limits are somewhat higher but can still be impressive. The reader is referred to textbooks for further details on basic principles of these spectroscopic techniques [3]. 

The simultaneous fluorometric determination of PG and BHA in cosmetics has also been described using excitation-emission fluorescence matrix data, which were processed by applying the second-order calibration method based on self-weighted alternating normalized residue fitting algorithm [80]. The detection limit obtained for PG was 2.2 ng/mL. 

Finally, an example should be provided about a class of methods, which have also explorative purposes, which will be discussed with more detail and theoretical depth in Chapter 7, that is multiway analysis methods [81]. These methods, among which parallel factor analysis (PARAFAC) will be shown here in action compared to PCA, are to some extent referred to as the conceptual (and mathematical) extension of PCA to arrays of order higher than two. They show their potentiality when the variability of a data set is related to different sources, or conditions, at which a full set of properties for each sample is measured [17-21]. An example, quite common in the food science analysis, is the excitation-emission fluorescence landscape, where, for each sample, an emission spectrum is recorded at each wavelength of the excitation signal. 

Garcfa-Reiriz A, Damiani PC, OUvieri AC, Canada-Canada F, Munoz de la Pena A. Nonlinear four-way kinetic-excitation-emission fluorescence data processed by a variant of parallel factor analysis and by a neural network model achieving the second-order advantage malo-naldehyde determination in oUve oil samples. Anal Chem 2008 80 7248-56. 

As we will see further in this chapter, knowing the structure of the data plays a fundamental role when applying any multiway technique. For illustrating this, we will comment on the data collected from the two most popular instrumentations used in food sciences nowadays that are able to produce multiway data Excitation-emission fluorescence spectroscopy (EEM) and hyphenated chromatographic systems (i.e. gas chromatography connected to mass spectrometry—GC-MS). The benefit and drawbacks of both techniques in the framework of food analysis will be discussed in successive chapters. Here we will just focus on the stmcture of the three-way array. Figure 1 shows the final three-way structure that is obtained when several samples are analysed by both EEM and hyphenated chromatography. However, the inner structure of this tensor varies due to the different nature of the measurement... 

Wu, F.C., MiUs, R.B., Evans, R.D., and Dillon, P.J. (2004). Kinetics of metal-fulvic acid complexation using a stopped-flow technique and three-dimensional excitation emission fluorescence spectrophotometer. Ana/. C/tcm., 76(1), 110-113. 

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