Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures.

The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not highlight the most influencing variables for each separation, whereas the ICA Loadings highlighted the same variables as did CCA. This study shows the potential of CCA for the extraction of pertinent information from a data matrix, using a procedure based on an original optimisation criterion, to produce results that are complementary, and in some cases may be superior, to those of PCA and ICA.

Solid-phase microextraction set-up for the analysis of liver volatolome to detect livestock exposure to micropollutants.

Starting from a critical analysis of a first "proof of concept" study on the utility of the liver volatolome for detecting livestock exposure to environmental micropollutants (Berge et al., 2011), the primary aim of this paper is to improve extraction conditions so as to obtain more representative extracts by using an extraction temperature closer to livestock physiological conditions while minimizing analytical variability and maximizing Volatile Organic Compound (VOC) abundancies. Levers related to extraction conditions and sample preparation were assessed in the light of both abundance and coefficient of variation of 22 candidate VOC markers identified in earlier volatolomic studies. Starting with a CAR/PDMS fiber and a 30min extraction, the reduction of SPME temperature to 40°C resulted in a significant decrease in the area of 14 candidate VOC markers (p<0.05), mainly carbonyls and alcohols but also a reduction in the coefficient of variation for 17 of them. In order to restore VOC abundances and to minimize variability, two approaches dealing with sample preparation were investigated. By increasing sample defrosting time at 4°C from 0 to 24h yielded higher abundances and lower variabilities for 15 and 13 compounds, respectively. Lastly, by using additives favouring the release of VOCs (1.2g of NaCl) the sensitivity of the analysis was improved with a significant increase in VOC abundances of more than 50% for 13 out of the 22 candidate markers. The modified SPME parameters significantly enhanced the abundances while decreasing the analytical variability for most candidate VOC markers. The second step was to validate the ability of the revised SPME protocol to discriminate intentionally contaminated broiler chickens from controls, under case/control animal testing conditions. After verification of the contamination levels of the animals by national reference laboratories, data analysis by a multivariate chemometric method (Common Components and Specific Weights Analysis - ComDim) showed that the liver volatolome could reveal dietary exposure of broilers to a group of environmental pollutants (PCBs), a veterinary treatment (monensin), and a pesticide (deltamethrin), thus confirming the usefulness of this analytical set-up.

Measuring Leaf Penetration and Volatilization of Chlorothalonil and Epoxiconazole Applied on Wheat Leaves in a Laboratory-Scale Experiment.

Estimation of pesticide volatilization from plants is difficult because of our poor understanding of foliar penetration by pesticides, which governs the amount of pesticide available for volatilization from the leaf surface. The description of foliar penetration is still incomplete because experimental measurements of this complex process are difficult. In this study, the dynamics of leaf penetration of C-chlorothalonil and C-epoxiconazole applied to wheat leaves were measured in a volatilization chamber, which allowed us to simultaneously measure pesticide volatilization. Fungicide penetration into leaves was characterized using a well-defined sequential extraction procedure distinguishing pesticide fractions residing at different foliar compartments; this enabled us to accurately measure the penetration rate constant into the leaves. The effect of pesticide formulation was also examined by comparing formulated and pure epoxiconazole. We observed a strong effect of formulation on leaf penetration in the case of a systemic product. Furthermore, the penetration rate constant of formulated epoxiconazole was almost three times that of pure epoxiconazole (0.47 ± 0.20 and 0.17 ± 0.07, respectively). Our experimental results showed high recovery rates of the radioactivity applied within the range of 90.5 to 105.2%. Moreover, our results confirm that pesticide physicochemical properties are key factors in understanding leaf penetration of pesticide and its volatilization. This study provides important and useful parameters for mechanistic models describing volatilization of fungicides applied to plants, which are scarce in the literature.