Honey, in particular monofloral varieties, is a valuable commodity. Here, we present proton trans... more Honey, in particular monofloral varieties, is a valuable commodity. Here, we present proton transfer reaction-time of flight-mass spectrometry, PTR-ToF-MS, coupled to chemometrics as a successful tool in the classification of monofloral honeys, which should serve in fraud protection against mispresentation of the floral origin of honey. We analyzed 7 different honey varieties from citrus, chestnut, sunflower, honeydew, robinia, rhododendron and linden tree, in total 70 different honey samples and a total of 206 measurements. Only subtle differences in the profiles of the volatile organic compounds (VOCs) in the headspace of the different honeys could be found. Nevertheless, it was possible to successfully apply 6 different classification methods with a total correct assignment of 81-99% in the internal validation sets. The most successful methods were stepwise linear discriminant analysis (LDA) and probabilistic neural network (PNN), giving total correct assignments in the external validation sets of 100 and 90%, respectively. Clearly, PTR-ToF-MS/chemometrics is a powerful tool in honey classification.
Different calibration methods have been applied for the determination of the Hydroxyl Number in p... more Different calibration methods have been applied for the determination of the Hydroxyl Number in polyester resins, namely Partial Least Squares (PLS), Principal Component Regression (PCR), Ordinary Least Squares with selection of the variables by genetic algorithm (OLS-GEN) and back-propagation Artificial Neural Networks (BP-ANN). The predictive ability of the regression models was estimated by splitting the dataset in training and test sets by application of the Kohonen self-organising maps. The linear methods (OLS-GEN, PLS and PCR) showed comparable results while artificial neural networks provided the best results both in fitting and prediction.
The growing number of studies on platinum(II) complexes is stimulated by their importance as anti... more The growing number of studies on platinum(II) complexes is stimulated by their importance as antitumour chemotherapeutics. 195Pt NMR spectroscopy is a very useful tool for characterizing and investigating these complexes. An accurate estimation of NMR chemical shifts plays an important role in the evaluation of molecular structure. Moreover, the predictions should be fast and accurate in order to be useful
The optimisation of the sensitivity in the ICP-MS determination of 83 isotopes, as a function of ... more The optimisation of the sensitivity in the ICP-MS determination of 83 isotopes, as a function of 21 operative parameters was performed by generating an initial experimental design that was used to define, by principal component analysis, the multi-criteria target function. The first PC, which contained an overall evaluation of the signal intensity of all isotopes, was used to rank the experiments. The modified simplex optimisation technique was then applied on the ranked experiments. The increase in signal intensity was, on the average, 3.9 times for the isotopes considered for the simplex procedure. When finally convergence was achieved, a PLS regression model calculated on the available experiments allowed to investigate the effect played by each factor on the experimental response. Simplex and PCA proved to be extremely effective to obtain the optimisation and to generate the multi-criteria target function: they can be suggested as an automatic method to perform the optimisation of the instrumental operative conditions.
This paper reports the development of calibration models for quality control in the production of... more This paper reports the development of calibration models for quality control in the production of ethylene/propylene/1-butene terpolymers by the use of multivariate tools and FT-IR spectroscopy. 1-Butene concentration prediction is achieved in terpolymers by coupling FT-IR spectroscopy to multivariate regression tools. A dataset of 26 terpolymers (14 coming from a constrained experimental design for mixtures, plus 12 terpolymers used for external validation) was analysed by FT-IR spectroscopy. An internal method of "Polimeri Europa" plant, based on (13)C NMR spectroscopy is used to determine the percentage of 1-butene in the samples. Then, different multivariate tools are used for 1-butene concentration prediction based on the FT-IR spectra recorded. Different multivariate calibration methods were explored: principal component regression (PCR), partial least squares (PLS), stepwise OLS regression (SWR) and artificial neural networks (ANNs). The model obtained by back-propagation neural networks turned out to be the best one. The performances of the BP-ANN model were further improved by variable selection procedures based on the calculation of the first derivative of the network. The proposed approach allows the monitoring in real time of the polymer synthesis and the estimation of the characteristics of the product attainable from the concentration of 1-butene.
This work is an extension of a method for monitoring the conservation state of pigmented surfaces... more This work is an extension of a method for monitoring the conservation state of pigmented surfaces presented in a previous paper. A cotton canvas painted with an organic pigment (Alizarin) was exposed to UV light in order to evaluate the effects of the applied treatment on the surface of the sample. The conservation state of the pigmented surface was monitored with ATR-FT-IR spectroscopy and multivariate control charts. The IR spectra were analysed by principal component analysis (PCA) and the relevant principal components (PCs) were used for constructing multivariate Shewhart, cumulative sums (CUSUM) and simultaneous scores monitoring and residuals tracking (SMART) control charts. These tools were successfully applied for the identification of the presence of relevant modifications occurring on the surface of the sample. Finally, with the aim to more deeply investigate what happened to the sample surface during the UV exposure, a PCA of the residuals matrix of degradation analyses only, not present in the previous paper, was performed. This analysis produced interesting results concerning the identification of the processes taking place on the irradiated surface.
Optimization of the experimental settings of a laser probe analyzer used for monitoring the inter... more Optimization of the experimental settings of a laser probe analyzer used for monitoring the interlace level of yarns in the textile industry was performed to reduce large number of errors that concern the reading of the interlace level of internal reference materials. The aim was to obtain a repeatable and accurate reading of the interlace level for two classes of products: texturized and stretched yarns. The experimental design techniques allowed to build a regression model for each class, relating the instrument reading and the experimental parameters of the control analyzer. The use of the optimal settings suggested by the regression models ensured great improvement in the accuracy of the readings furnished by the probe. This improvement ranged from 8% to 10% in the case of the texturized threads and from 15% to 32% in the case of the stretched ones, bringing about a relevant improvement in the quality control process.
SIMCA classification can be applied to 2D-PAGE maps to identify changes occurring in cellular pro... more SIMCA classification can be applied to 2D-PAGE maps to identify changes occurring in cellular protein contents as a consequence of illnesses or therapies. These data sets are complex to treat due to the large number of proteins detected. A method for identifying relevant proteins from SIMCA discriminating powers is proposed, based on the Box-Cox transformation coupled to probability papers. The method successfully allowed the identification of the relevant spots from 2D maps.
A new algorithm for generating simulated sodium dodecil sulfate two-dimensional polyacrylamide ge... more A new algorithm for generating simulated sodium dodecil sulfate two-dimensional polyacrylamide gel electrophoresis (SDS 2D-PAGE) map images was developed. To choose the simulation strategy able to provide realistic 2D-PAGE maps, several parameters that characterize the statistical features of the images and data sets of images were taken into account, such as the distribution of size, intensity, and volume of the spots and their changes of position and volume along different replications of the same 2D-PAGE map. In this way, also the low reproducibility of replications of the same SDS 2D-PAGE maps was taken into account. The present algorithm can be usefully employed for the development of new classification and/or image analysis algorithms applied to bidimensional electrophoretic data sets, given the usually small number of experimental replications available.
Page 1. Current Analytical Chemistry, 2006, 2, 181-194 181 Artificial Neural Networks Application... more Page 1. Current Analytical Chemistry, 2006, 2, 181-194 181 Artificial Neural Networks Applications in the Field of Separation Science Optimisation Emilio Marengo*, Elisa Robotti, Marco Bobba, and Maria Cristina Liparota Department ...
A new method has been developed for monitoring the degradation of paintings. Two inorganic pigmen... more A new method has been developed for monitoring the degradation of paintings. Two inorganic pigments (ultramarine blue and red ochre) were blended with linseed oil and spread on canvas. Each canvas was subjected to simulated accelerated ageing in the presence of typical degradation agents (UV radiation and acidic solution). Periodically the painted surfaces were analysed by FT-Raman, to investigate the status of the surface. The data obtained were analysed by principal component analysis (PCA). Finally the Shewhart and cumulative sum control charts based on the relevant principal components (PC) and the so called scores monitoring and residuals tracking (SMART) charts were built. The method based on the use of PC to describe the process was found to enable identification of the presence of relevant modification occurring on the surface of the samples studied.
Honey, in particular monofloral varieties, is a valuable commodity. Here, we present proton trans... more Honey, in particular monofloral varieties, is a valuable commodity. Here, we present proton transfer reaction-time of flight-mass spectrometry, PTR-ToF-MS, coupled to chemometrics as a successful tool in the classification of monofloral honeys, which should serve in fraud protection against mispresentation of the floral origin of honey. We analyzed 7 different honey varieties from citrus, chestnut, sunflower, honeydew, robinia, rhododendron and linden tree, in total 70 different honey samples and a total of 206 measurements. Only subtle differences in the profiles of the volatile organic compounds (VOCs) in the headspace of the different honeys could be found. Nevertheless, it was possible to successfully apply 6 different classification methods with a total correct assignment of 81-99% in the internal validation sets. The most successful methods were stepwise linear discriminant analysis (LDA) and probabilistic neural network (PNN), giving total correct assignments in the external validation sets of 100 and 90%, respectively. Clearly, PTR-ToF-MS/chemometrics is a powerful tool in honey classification.
Different calibration methods have been applied for the determination of the Hydroxyl Number in p... more Different calibration methods have been applied for the determination of the Hydroxyl Number in polyester resins, namely Partial Least Squares (PLS), Principal Component Regression (PCR), Ordinary Least Squares with selection of the variables by genetic algorithm (OLS-GEN) and back-propagation Artificial Neural Networks (BP-ANN). The predictive ability of the regression models was estimated by splitting the dataset in training and test sets by application of the Kohonen self-organising maps. The linear methods (OLS-GEN, PLS and PCR) showed comparable results while artificial neural networks provided the best results both in fitting and prediction.
The growing number of studies on platinum(II) complexes is stimulated by their importance as anti... more The growing number of studies on platinum(II) complexes is stimulated by their importance as antitumour chemotherapeutics. 195Pt NMR spectroscopy is a very useful tool for characterizing and investigating these complexes. An accurate estimation of NMR chemical shifts plays an important role in the evaluation of molecular structure. Moreover, the predictions should be fast and accurate in order to be useful
The optimisation of the sensitivity in the ICP-MS determination of 83 isotopes, as a function of ... more The optimisation of the sensitivity in the ICP-MS determination of 83 isotopes, as a function of 21 operative parameters was performed by generating an initial experimental design that was used to define, by principal component analysis, the multi-criteria target function. The first PC, which contained an overall evaluation of the signal intensity of all isotopes, was used to rank the experiments. The modified simplex optimisation technique was then applied on the ranked experiments. The increase in signal intensity was, on the average, 3.9 times for the isotopes considered for the simplex procedure. When finally convergence was achieved, a PLS regression model calculated on the available experiments allowed to investigate the effect played by each factor on the experimental response. Simplex and PCA proved to be extremely effective to obtain the optimisation and to generate the multi-criteria target function: they can be suggested as an automatic method to perform the optimisation of the instrumental operative conditions.
This paper reports the development of calibration models for quality control in the production of... more This paper reports the development of calibration models for quality control in the production of ethylene/propylene/1-butene terpolymers by the use of multivariate tools and FT-IR spectroscopy. 1-Butene concentration prediction is achieved in terpolymers by coupling FT-IR spectroscopy to multivariate regression tools. A dataset of 26 terpolymers (14 coming from a constrained experimental design for mixtures, plus 12 terpolymers used for external validation) was analysed by FT-IR spectroscopy. An internal method of "Polimeri Europa" plant, based on (13)C NMR spectroscopy is used to determine the percentage of 1-butene in the samples. Then, different multivariate tools are used for 1-butene concentration prediction based on the FT-IR spectra recorded. Different multivariate calibration methods were explored: principal component regression (PCR), partial least squares (PLS), stepwise OLS regression (SWR) and artificial neural networks (ANNs). The model obtained by back-propagation neural networks turned out to be the best one. The performances of the BP-ANN model were further improved by variable selection procedures based on the calculation of the first derivative of the network. The proposed approach allows the monitoring in real time of the polymer synthesis and the estimation of the characteristics of the product attainable from the concentration of 1-butene.
This work is an extension of a method for monitoring the conservation state of pigmented surfaces... more This work is an extension of a method for monitoring the conservation state of pigmented surfaces presented in a previous paper. A cotton canvas painted with an organic pigment (Alizarin) was exposed to UV light in order to evaluate the effects of the applied treatment on the surface of the sample. The conservation state of the pigmented surface was monitored with ATR-FT-IR spectroscopy and multivariate control charts. The IR spectra were analysed by principal component analysis (PCA) and the relevant principal components (PCs) were used for constructing multivariate Shewhart, cumulative sums (CUSUM) and simultaneous scores monitoring and residuals tracking (SMART) control charts. These tools were successfully applied for the identification of the presence of relevant modifications occurring on the surface of the sample. Finally, with the aim to more deeply investigate what happened to the sample surface during the UV exposure, a PCA of the residuals matrix of degradation analyses only, not present in the previous paper, was performed. This analysis produced interesting results concerning the identification of the processes taking place on the irradiated surface.
Optimization of the experimental settings of a laser probe analyzer used for monitoring the inter... more Optimization of the experimental settings of a laser probe analyzer used for monitoring the interlace level of yarns in the textile industry was performed to reduce large number of errors that concern the reading of the interlace level of internal reference materials. The aim was to obtain a repeatable and accurate reading of the interlace level for two classes of products: texturized and stretched yarns. The experimental design techniques allowed to build a regression model for each class, relating the instrument reading and the experimental parameters of the control analyzer. The use of the optimal settings suggested by the regression models ensured great improvement in the accuracy of the readings furnished by the probe. This improvement ranged from 8% to 10% in the case of the texturized threads and from 15% to 32% in the case of the stretched ones, bringing about a relevant improvement in the quality control process.
SIMCA classification can be applied to 2D-PAGE maps to identify changes occurring in cellular pro... more SIMCA classification can be applied to 2D-PAGE maps to identify changes occurring in cellular protein contents as a consequence of illnesses or therapies. These data sets are complex to treat due to the large number of proteins detected. A method for identifying relevant proteins from SIMCA discriminating powers is proposed, based on the Box-Cox transformation coupled to probability papers. The method successfully allowed the identification of the relevant spots from 2D maps.
A new algorithm for generating simulated sodium dodecil sulfate two-dimensional polyacrylamide ge... more A new algorithm for generating simulated sodium dodecil sulfate two-dimensional polyacrylamide gel electrophoresis (SDS 2D-PAGE) map images was developed. To choose the simulation strategy able to provide realistic 2D-PAGE maps, several parameters that characterize the statistical features of the images and data sets of images were taken into account, such as the distribution of size, intensity, and volume of the spots and their changes of position and volume along different replications of the same 2D-PAGE map. In this way, also the low reproducibility of replications of the same SDS 2D-PAGE maps was taken into account. The present algorithm can be usefully employed for the development of new classification and/or image analysis algorithms applied to bidimensional electrophoretic data sets, given the usually small number of experimental replications available.
Page 1. Current Analytical Chemistry, 2006, 2, 181-194 181 Artificial Neural Networks Application... more Page 1. Current Analytical Chemistry, 2006, 2, 181-194 181 Artificial Neural Networks Applications in the Field of Separation Science Optimisation Emilio Marengo*, Elisa Robotti, Marco Bobba, and Maria Cristina Liparota Department ...
A new method has been developed for monitoring the degradation of paintings. Two inorganic pigmen... more A new method has been developed for monitoring the degradation of paintings. Two inorganic pigments (ultramarine blue and red ochre) were blended with linseed oil and spread on canvas. Each canvas was subjected to simulated accelerated ageing in the presence of typical degradation agents (UV radiation and acidic solution). Periodically the painted surfaces were analysed by FT-Raman, to investigate the status of the surface. The data obtained were analysed by principal component analysis (PCA). Finally the Shewhart and cumulative sum control charts based on the relevant principal components (PC) and the so called scores monitoring and residuals tracking (SMART) charts were built. The method based on the use of PC to describe the process was found to enable identification of the presence of relevant modification occurring on the surface of the samples studied.
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