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Selected papers from the latest issue:
Achieving bilinearity in non-bilinear augmented first order kinetic data applying calibration transfer
29 January 2012, 02:21:49
Publication year: 2012
Source: Chemometrics and Intelligent Laboratory Systems, Available online 28 January 2012
Maryam Khoshkam, Frans van den Berg, Mohsen Kompany-Zareh
In this paper a calibration transfer method is used to achieve bilinearity for augmented first order kinetic data. First, the proposed method is investigated using simulated data and next the concept is applied to experimental data. The experimental data consists of spectroscopic monitoring of the first order degradation reaction of carbaryl. This component is used for control of pests in fruits, vegetables, forages, cotton and other crops. It is highly toxic and likely human carcinogen, and is lethal to many non-target beneficial insects. The kinetic experiment is performed at different pH-values and emission wavelengths using an excitation wavelength equal to 275 nm. Rate constants of different data matrices at different pH values were calculated based on a hard modeling method. Analysis of simulated and experimental data shows that if there is a deviation from bilinearity, applying the model based methods to augmented datasets leads to inaccurate results. The application of a calibration transfer method as an additional step in the hard modeling procedure improves the results, and accurate estimation of reaction rate constants are obtained. The proposed method was compared to Local Spectra Mode of Analysis (LSMA) which was proposed by Puxtyet al. A comparison of the results shows that the proposed method is more efficient than LSMA and leads to less uncertainty in estimated rate constants and less percent error in the relative residuals.
Source: Chemometrics and Intelligent Laboratory Systems, Available online 28 January 2012
Maryam Khoshkam, Frans van den Berg, Mohsen Kompany-Zareh
In this paper a calibration transfer method is used to achieve bilinearity for augmented first order kinetic data. First, the proposed method is investigated using simulated data and next the concept is applied to experimental data. The experimental data consists of spectroscopic monitoring of the first order degradation reaction of carbaryl. This component is used for control of pests in fruits, vegetables, forages, cotton and other crops. It is highly toxic and likely human carcinogen, and is lethal to many non-target beneficial insects. The kinetic experiment is performed at different pH-values and emission wavelengths using an excitation wavelength equal to 275 nm. Rate constants of different data matrices at different pH values were calculated based on a hard modeling method. Analysis of simulated and experimental data shows that if there is a deviation from bilinearity, applying the model based methods to augmented datasets leads to inaccurate results. The application of a calibration transfer method as an additional step in the hard modeling procedure improves the results, and accurate estimation of reaction rate constants are obtained. The proposed method was compared to Local Spectra Mode of Analysis (LSMA) which was proposed by Puxtyet al. A comparison of the results shows that the proposed method is more efficient than LSMA and leads to less uncertainty in estimated rate constants and less percent error in the relative residuals.
Highlights
► Calibration transfer method is used to achieve bilinearity in augmented first order kinetic data for first time. ► The data were analyzed based on hard modelling methods. ► calibration transfer was used as an extra step inside the procedure. ► It is shown that using calibration transfer in hard modelling methods improve the results. ► A general and simple method is proposed for correction of non-bilinearity in full rank systems.Filling andD-optimal designs for the correlated Generalized Exponential models
29 January 2012, 02:21:49
Publication year: 2012
Source: Chemometrics and Intelligent Laboratory Systems, Available online 28 January 2012
J.M. Rodríguez-Díaz, M.T. Santos-Martín, H. Waldl, M. Stehlík
The aim of this paper is to provide guidelines for the statistically efficient estimation of parameters of a modified Arrhenius model for chemical kinetics. A modified Arrhenius model is used for instance by modeling a flux of methane in troposphere or by chemical kinetics for reactions at membranes.D-optimal and filling designs for the Generalized Exponential Model with correlated observations are studied, considering the exponential covariance with or without nugget effect. Both equidistant and exact designs for small samples are examined, studying the behavior of different types of filling designs when a greater number of observations is preferred. Probably the main lesson we can learn is that theD-optimal design is analytically peculiar and these designs can be practically obtained only by numerical computation; however, specially two point locallyD-optimal designs are very interesting, since they may help us to find a reasonable range for filling designs. The latter ones are probably only applicable when seeking for a higher number of design points. It is an interesting issue that very often the best designs do not use the whole design interval, but only a part of it; this should be taken into account by practitioners when they design their experiments. The second important observation is the large bias of the ML estimator of the correlation parameter. From the theoretical point of view this is not surprising since variance and correlation parameters are not simultaneously identifiable. We develop a bias reduction method and illustrate its effectiveness. We also provide practical implications for chemometrics.
Source: Chemometrics and Intelligent Laboratory Systems, Available online 28 January 2012
J.M. Rodríguez-Díaz, M.T. Santos-Martín, H. Waldl, M. Stehlík
The aim of this paper is to provide guidelines for the statistically efficient estimation of parameters of a modified Arrhenius model for chemical kinetics. A modified Arrhenius model is used for instance by modeling a flux of methane in troposphere or by chemical kinetics for reactions at membranes.D-optimal and filling designs for the Generalized Exponential Model with correlated observations are studied, considering the exponential covariance with or without nugget effect. Both equidistant and exact designs for small samples are examined, studying the behavior of different types of filling designs when a greater number of observations is preferred. Probably the main lesson we can learn is that theD-optimal design is analytically peculiar and these designs can be practically obtained only by numerical computation; however, specially two point locallyD-optimal designs are very interesting, since they may help us to find a reasonable range for filling designs. The latter ones are probably only applicable when seeking for a higher number of design points. It is an interesting issue that very often the best designs do not use the whole design interval, but only a part of it; this should be taken into account by practitioners when they design their experiments. The second important observation is the large bias of the ML estimator of the correlation parameter. From the theoretical point of view this is not surprising since variance and correlation parameters are not simultaneously identifiable. We develop a bias reduction method and illustrate its effectiveness. We also provide practical implications for chemometrics.
Highlights
► We study several design issues for modified Arrhenius modell ► We consider correlation between measurements. ► We provide applications to a flux of methane in troposphere. ► Two point designs are important for choice of temperature region. ► Special filling designs are very effective.Use of chemometric tools to estimate the effects of the addition of yeast, glucose-oxidase, soybean or horse bean flours to wheat flour on biochemical bread dough characteristics
25 January 2012, 01:24:57
Publication year: 2012
Source: Chemometrics and Intelligent Laboratory Systems, Available online 24 January 2012
A. Boussard, C.B.Y. Cordella, L. Rakotozafy, G. Moulin, F. Buche, ...
This work aimed to use chemometric tools to estimate and understand the interaction effects of yeast (Y), glucose oxidase (G) and horse bean (HB) or soybean (SB) flours on the biochemical characteristics of wheat bread dough. Mixing was carried out with wheat flour alone or supplemented with different ingredients (alone or in combination) such as Y, G and HB (1%) or SB (0.5%) flour. The biochemical factors related to lipid oxidation - lipid components and lipoxygenase (LOX) activity - were quantified in the initial flour and in dough after mixing. Thus, the polyunsaturated fatty acids (PUFA) either in the free form (free-PUFA) or present in triacylglycerol (PUFA-TAG), the primary oxidation products of linoleic acid (LH) such as hydroxyacid (HODE), hydroperoxide (HPODE) and ketodiene (KODE) and the carotenoid pigments were analyzed. Two experimental designs were built to quantify the effects on lipid oxidation of the different ingredients and their interactions with a limited number of experiments. Results were analyzed by using multivariate chemometrical methods, principal component analysis (PCA), statistical methods (Pareto chart) and Mahalanobis distance (MD). The HODE and KODE levels are dependent on the LOX botanical origin. In our conditions and in terms of lipid oxidation, the dough biochemical characteristics are not affected by the presence of G (without added glucose) in the formulation whatever the other ingredients were.
Source: Chemometrics and Intelligent Laboratory Systems, Available online 24 January 2012
A. Boussard, C.B.Y. Cordella, L. Rakotozafy, G. Moulin, F. Buche, ...
This work aimed to use chemometric tools to estimate and understand the interaction effects of yeast (Y), glucose oxidase (G) and horse bean (HB) or soybean (SB) flours on the biochemical characteristics of wheat bread dough. Mixing was carried out with wheat flour alone or supplemented with different ingredients (alone or in combination) such as Y, G and HB (1%) or SB (0.5%) flour. The biochemical factors related to lipid oxidation - lipid components and lipoxygenase (LOX) activity - were quantified in the initial flour and in dough after mixing. Thus, the polyunsaturated fatty acids (PUFA) either in the free form (free-PUFA) or present in triacylglycerol (PUFA-TAG), the primary oxidation products of linoleic acid (LH) such as hydroxyacid (HODE), hydroperoxide (HPODE) and ketodiene (KODE) and the carotenoid pigments were analyzed. Two experimental designs were built to quantify the effects on lipid oxidation of the different ingredients and their interactions with a limited number of experiments. Results were analyzed by using multivariate chemometrical methods, principal component analysis (PCA), statistical methods (Pareto chart) and Mahalanobis distance (MD). The HODE and KODE levels are dependent on the LOX botanical origin. In our conditions and in terms of lipid oxidation, the dough biochemical characteristics are not affected by the presence of G (without added glucose) in the formulation whatever the other ingredients were.
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