Ashok Kumar Mishra

In a recently developed procedure for parallel factor (PARAFAC) analysis of total synchronous fluorescence spectroscopy (TSFS), the issue of no-trilinearity of TSFS data set was addressed by representing the TSFS data in excitation-emission matrix fluorescence (EEMF) layout which ensures the trilinearity to data sets "a must" for PARAFAC analysis. This representation leads to generation of significantly large number of variables, which do not contain any experimentally acquired fluorescence information. It is essential that such variables be handled properly before subjecting TSFS data in EEMF layout to PARAFAC analysis. Based on our understanding of mechanism by which PARAFAC analysis on TSFS data in EEMF layout works, we used three possible ways: (i) assigning a value of zero, (ii) assigning missing (NaN) values, and (iii) combination of zero and NaN values to handle such variables. We evaluated each of these three possibilities and compared the outcomes of PARAFAC analysis with respect to two important parameters: (i) proximity between the actual and retrieved TSFS profile of all the three fluorophores and (ii) time taken for the convergence of PARAFAC algorithm. The obtained results of PARAFAC analyses on TSFS data in EEMF layout showed that better analytical results are obtained if we set all the variables with no experimentally acquired information to missing (NaN) values, though the computational time is significantly high. PARAFAC analysis tends to converge prematurely when a value of zero was assigned to all the variables in EEMF layout that do not contain any experimentally acquired information. The present work also showed that by using the combination of zero and missing values it is possible to optimize the computational time and retrieve PARAFAC separated TSFS profile from EEMF layout with reasonable purity.

Over the years mainly three unconventional fluorescence techniques, Excitation–emission matrix fluorescence (EEMF), synchronous fluorescence spectroscopy (SFS), and total synchronous fluorescence spectroscopy (TSFS) are introduced for the analysis of multifluorophoric mixtures. Application of EEMF, SFS and TSFS are conceptually different. The existing literature lacks a review article that gives an overview on conceptual and analytical aspects of EEMF, SFS and TSFS for general as well as specialized fluorescence scientific community. The present review article attempts to address these issues and discusses various conceptual and practical aspects of EEMF, SFS and TSFS spectroscopy. The present article contains numerous novel fluorescence parameters, concept of concentration dependent red shift, protocol for finding the optimum wavelength offset for SFS data acquisition is introduced, various practical aspects of integrating chemometric methods with TSFS and number of successful applications of EEMF, SFS and TSFS for the analysis of complex and simple multifluorophoric mixtures is discussed.

In recent years, total synchronous fluorescence (TSF) spectroscopy has become popular for the analysis of multifluorophoric systems. Application of PARAFAC, a popular deconvolution tool, requires trilinear structure in the three-way data array. The present work shows that TSF based three-way array data set of dimension sample × wavelength × Δ λ does not have trilinear structure and hence it should not be subjected to PARAFAC analysis. This work also proposes that a TSF data set can be converted to an excitation-emission matrix fluorescence (EEMF) like data set which has trilinear structure, so that PARAFAC analysis can be performed on it. This also enables the retrieval of PARAFAC-separated component TSF spectra. © 2012 Elsevier B.V.

Oral submucous fibrosis (OSF) is a precancerous condition which leads to the development of fibrous band and loss of oral mucosa elasticity. In the absence of medical treatment OSF can also lead to oral cancer. In the present work, in vivo fluorescence data obtained from the oral tissues of the pre-treated OSF subjects, post-treated OSF subjects, and the normal healthy volunteers were subjected to principal component analysis (PCA) and partial least square discriminate analysis (PLS-DA). PCA and PLS-DA are unsupervised and supervised pattern recognition methods, respectively. PCA and PLS-DA models were found to be highly sensitive and specific. The receiver operating characteristic (ROC) curve of the PLS-DA models mainly consisted of horizontal and vertical lines with an area under the curve of greater than 0.9 which shows that PLS-DA models are genuine classifier. Outcomes of the present work clearly illustrate that by combining the in vivo fluorescence spectroscopy with PCA and PLS-DA, a fast, sensitive, and non-invasive procedure could be obtained for the diagnosis of OSF affected subjects. The developed diagnosis procedure could be of significant importance in rural areas where access to clinical diagnosis is relatively difficult and costly. © 2013 The Royal Society of Chemistry.

Petroleum fuels are generally non-polar. The presence of ethanol in the petrol-ethanol fuel blends increases the polarity of the fuel blend. It was observed that absorption spectral shift of the Reichardt's ET(30) dye is sensitive to the petrol-ethanol blend polarity. It was also found that ET(30) dye has a characteristic λmax of absorption in petrol-ethanol blends irrespective of the petrol batch with which blends were prepared. In the present work, a sensitive analytical method for the petrol batch independent quantification of ethanol content in petrol-ethanol blends has been developed. © 2012 Elsevier B.V.

In the present study, the possibility of using the multivariate curve resolution alternating least square (MCR-ALS) analysis for the simultaneous extraction of the pure synchronous fluorescence spectra at various wavelength offsets (δλ) for each fluorophore from the total synchronous fluorescence spectroscopy (TSFS) data set of the dilute aqueous mixtures of the three fluorophores, was explored. The present work was based on the assumption that unfolded TSFS data has a bilinear structure and therefore it can be subjected to MCR-ALS analysis. Three fluorophores, benzo[a]pyrene(BaP), perylene(PE), and pyrene(PY), were chosen. These three fluorophores show fluorescence at all the seven wavelength offsets (δλ) used to create the TSFS data set. In addition, Raman scattering due to solvent molecules (i.e. water) also appear in the wavelength ranges where these fluorophores show fluorescence. These two factors make the simultaneous extraction of synchronous spectral profile at various δλs from the TSFS data set relatively difficult. The appearance of the diagonal signals in the three-dimensional landscapes of TSFS shows the presence of the Raman scattering. The Raman signal due to solvent molecules was found to influence the synchronous profile of a fluorophore to different extents at different δλs. TSFS data set of dimension, sample × wavelength × δλ, was unfolded along the first mode to obtain the unfolded TSFS data set. Pure synchronous spectral profiles at various δλs were obtained for each fluorophore by performing the MCR-ALS analysis on the unfolded TSFS data. However Raman scattering signals could not be eliminated from the synchronous spectral profiles of the PE and PY. For the mitigation of Raman scattering from the calculated spectral profiles, TSFS data of solvent blank were subtracted from all the samples before performing the MCR-ALS analysis. The obtained spectral profiles of BaP, PE, and PY were found to match with their actual spectral profiles which verifies that unfolded TSFS data set has a bilinear structure. To test the strength of the present work, MCR-ALS analysis was also performed on the unfolded TSFS data set of 12 groundwater samples which were contaminated with the BaP- and PY-spiked gasoline. The obtained results show that it is possible to monitor the presence of BaP and PY in groundwater samples. © 2012 Elsevier B.V.

Total synchronous fluorescence spectroscopy (TSFS)-based three-way array sample × excitation wavelength × δ λ has inherently complex data structure. Multivariate curve resolution alternating least square (MCR-ALS) analysis is a soft mathematical modelling technique that can be used to retrieve pure spectral and contribution profile of the fluorophores of a multifluorophoric mixture provided it is applied to bilinear data sets. In the present work, possibilities of generating bilinear two-way arrays by (i) unfolding and (ii) augmenting the TSFS-based three-way array were studied. Bilinear characteristics of the obtained two-way arrays were tested by subjecting them to MCR-ALS analysis. It was found that lack of analytical-mathematical relationship between spectral profile along the excitation wavelength mode and the offset mode do not allow the application of MCR-ALS analysis on augmented TSFS data set. Moreover, the augmentation procedure and chemical-mathematical rank of the subsequently obtained data sets were found to be 'not independent' of each other. Two-way array sample × (excitation wavelength × δ λ) obtained by unfolding TSFS-based three-way array along the sample mode was found to have symmetrical structure, i.e., both sample mode and spectral mode have equal mathematical and chemical rank making them highly attuned to MCR-ALS analysis.

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence (TSF) spectroscopy are two conceptually different fluorescence techniques that have been used to map the fluorescence responses of the fluorophores present in a multifluorophoric mixture. EEMF was introduced four decades back and most of the fluorimeters have the suitable computer program which allows the acquisition EEMF spectra. Recently introduced TSF spectroscopy has been shown to possess good application potential in analytical fluorimetry and has started attracting the attention of analytical chemists. TSF data structure, however, is intrinsically different from EEMF data structure and a better understanding of TSF data structure is crucial to utilising its application potential. In the present work, a comprehensive comparative study between EEMF and TSF spectroscopic data set was performed by taking aqueous mixtures containing low concentrations of benzo[a]pyrene, chrysene, and pyrene as test case. The EEMF and TSF data structures were clearly explained by taking pyrene as an example. The effects of Rayleigh and Raman scattering on the quality of EEMF and TSF data sets were studied. EEMF and TSF data sets of dilute aqueous mixtures of benzo[a]pyrene, chrysene, and pyrene were subjected to three chemometric techniques PARAFAC, N-PLS, and MCR-ALS analysis. TSF data set in particular was found to be highly attuned to MCR-ALS analysis. Obtained results of chemometric analyses on EEMF and TSF data sets show that TSF data of dilute aqueous mixtures provides more accurate spectral and concentration information than EEMF data sets. Therefore, TSF spectroscopy could be considered as an alternate to the EEMF for the analyses of dilute multifluorophoric mixtures. © 2013 Elsevier B.V.

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix.

The complexity of molecular compositions of ayurvedic preparations makes their classification or quality monitoring a difficult task. Classification of aqueous-based ayurvedic preparations with commonly used techniques such as Fourier transform infrared and near infrared spectroscopy is more difficult due to strong interferences from water signals. In the present work, by taking an aqueous-based ayurvedic preparation (jirakadyarista) as a test case, it has been shown that a simple, fast and efficient procedure for the classification of such preparations can be achieved by combining synchronous fluorescence spectroscopy with chemometric methods such as principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). The PCA and PLS-DA models obtained were found to be sensitive and specific in classifying the jirakadyarista samples.