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- Definitive screening designs and latent variable modelling for the optimization of solid phase microextraction (SPME): case study-quantification of volatile fatty acids in winesPublication . Pereira, Ana C.; Reis, Marco S.; Leça, João M.; Rodrigues, Pedro M.; Marques, José C.In the present study, we apply the recently proposed Definitive Screening Designs (DSD) to optimize HS-SPME extraction in order to analyze volatile fatty acids (VFA) present in wine samples. This is the first attempt to apply this new class of designs to one of the most well-known and widely applied extraction techniques. The latent structure of the responses is also explored for defining the optimal extraction conditions. DSD is a new screening design with the potential to significantly reduce the number of experiments required to estimate the model pa rameters and to establish the optimum operation conditions. Therefore, there is an obvious interest in assessing the benefits of DSD in practice. In this work, this design framework is applied to the simultaneous optimization of seven extraction parameters (responses). Both qualitative and quantitative extraction parameters are considered, in order to test the flexibility of DSD designs: a two-level qualitative variable, the fiber coating, and six quanti tative variables, namely the pre-incubation time, the extraction time and temperature, the headspace/sample volume, the effect of agitation during extraction and the influence of the ethanol content (sample dilution). Optimization of analytes' chromatographic responses was carried out both individually (response by response) and altogether, by modelling the responses in the latent variable space (i.e., explicitly considering their under lying correlation structure). In the end, a consensus analysis of all perspectives was considered in the definition of the overall optimal extraction conditions for the quantification of VFA in fortified wines. The solution found was to use a DVB/Car/PDMS fiber, 10 mL of samples in 20 mL vial, 40 min of extraction at 40 C. The analysis also revealed that the factors incubation time, agitation and sample dilution do not play a significant role in explaining the variability of extraction parameters. Therefore, they were set to the most convenient levels. The methodology followed was thoroughly validated and the following figures of merit were obtained: good linearity (R2 > 0.999, for all compounds), high sensitivity (LOD and LOQ are close or below the values found in literature), recoveries of approximately 100% and suitable precision (repeatability and reproducibility lower than 7.21% and 8.61%, respectively). Finally, the optimized methodology was tested in practice. Several wine samples were analyzed and the odor activity value calculated to facilitate the identification of their importance as odor active compounds in different aged fortified wines. This work demonstrates the benefits of using DSD and latent variable modelling for the optimization of analytical techniques, contributing to the implementation of rigorous, systematic and more efficient optimization protocols.
- Chemometric analysis of the volatile fraction evolution of Portuguese beer under shelf storage conditionsPublication . Rendall, Ricardo; Reis, Marco S.; Pereira, Ana Cristina; Pestana, Cristina; Pereira, Vanda; Marques, José CarlosIn this work we present a multivariate statistical analysis of the evolution of the volatile fraction of Portuguese beer over an extended period of 1 year under standard shelf storage conditions, using gas chromatography coupled with mass spectrometry (GC–MS). A systematic methodology is proposed for detecting the onset of meaningful changes in chemical composition during shelf storage and to monitor its evolution along time. We also put forward and discuss chemometric procedures for analyzing the contributions of different chemical com ponents in the definition of dynamic ageing trends. In summary, the chemometric analysis reveals that the chem ical composition of beer presents a statistically meaningful deviation from the reference scenario after a period of 7 months, although the deviation trend has its onset during the 6th month. The analysis performed also under lines the limitations of current variable contribution methods, and an alternative procedure was proposed based on the analysis in the original domain which finally led to a consistent and interpretable clustering structure of the volatile fraction compounds. Esters and higher alcohol compounds stand up on a cluster arrangement sug gesting that their strict control can effectively point out meaningful changes on beer aroma. Organic acids, name ly caprylic, capric and acetic acids can also be very helpful in that sense
- Optimal design of experiments applied to headspace solid phase microextraction for the quantification of vicinal diketones in beer through gas chromatography-mass spectrometric detectionPublication . Leça, João M.; Pereira, Ana C.; Vieira, Ana C.; Reis, Marco S.; Marques, José C.Vicinal diketones, namely diacetyl (DC) and pentanedione (PN), are compounds naturally found in beer that play a key role in the definition of its aroma. In lager beer, they are responsible for off-flavors (buttery flavor) and therefore their presence and quantification is of paramount importance to beer producers. Aiming at developing an accurate quantitative monitoring scheme to follow these off-flavor compounds during beer production and in the final product, the head space solid-phase microextraction (HS-SPME) analytical procedure was tuned through experiments planned in an optimal way and the final settings were fully validated. Optimal design of experiments (O-DOE) is a computational, statistically oriented approach for designing experiences that are most informative according to a well-defined criterion. This methodology was applied for HS-SPME optimization, leading to the following optimal extraction conditions for the quantification of VDK: use a CAR/PDMS fiber, 5 ml of samples in 20 ml vial, 5 min of pre-incubation time followed by 25 min of extraction at 30 C, with agitation. The validation of the final analytical methodology was performed using a matrix-matched calibration, in order to mini mize matrix effects. The following key features were obtained: linearity (R2 > 0.999, both for diacetyl and 2,3-pentanedione), high sensitivity (LOD of 0.92 mg L 1 and 2.80 mg L 1 , and LOQ of 3.30 mg L 1 and 10.01 mg L 1 , for diacetyl and 2,3-pentanedione, respectively), recoveries of approximately 100% and suitable precision (repeatability and reproducibility lower than 3% and 7.5%, respectively). The applicability of the methodology was fully confirmed through an independent analysis of several beer samples, with analyte concentrations ranging from 4 to 200 g L 1
- Multiresponse and multiobjective latent variable optimization of modern analytical instrumentation for the quantification of chemically related families of compounds: case study—Solid‐phase microextraction (SPME) applied to the quantification of analytes with impact on wine aromaPublication . Reis, Marco S.; Pereira, Ana C.; Leça, João M.; Rodrigues, Pedro M.; Marques, José C.The optimized operation of modern analytical instrumentation is a critical but complex task. It involves the simultaneous consideration of a large number of factors, both qualitative and quantitative, where multiple responses should be quantified and several goals need to be adequately pondered, such as global quantification performance, selectivity, and cost. Furthermore, the problem is highly case specific, depending on the type of instrument, target analytes, and media where they are dispersed. Therefore, an optimization procedure should be conducted frequently, which implies that it should be efficient (requiring a low number of experiments), as simple as possible (from experi mental design to data analysis) and informative (interpretable and conclusive). The success of this task is fundamental for achieving the scientific goals and to justify, in the long run, the high economic investments made and significant costs of operation. In this article, we present a systematic optimization proce dure for the prevalent class of situations where multiple responses are available regarding a family of chemical compounds (instead of a single analyte). This class of problems conducts to responses exhibiting mutual correlations, for which, furthermore, several goals need to be simultaneously considered. Our approach explores the latent variable structure of the responses created by the chemical affinities of the compounds under analysis and the orthogonality of the interpretable extracted components to conduct their simultaneous opti mization with respect to different analysis goals. The proposed methodology was applied to a real case study involving the quantification of a family of analytes with impact on wine aroma.
- Modelling the ageing process: a novel strategy to analyze the wine evolution towards the expected featuresPublication . Pereira, Ana C.; Carvalho, Maria J.; Miranda, Andreia; Leça, João M.; Pereira, Vanda; Albuquerque, Francisco; Marques, José C.; Reis, Marco S.In this work we present a new strategy to monitor the wine evolution during the ageing process. More specifi cally, we validate a procedure for analyzing how wine evolves during the ageing process in relation to the desired and expected quality features and we apply the proposed methodology to the case of a Portuguese fortified wine, the Madeira wine, where we compare the wine evolution under two different ageing processes. The approach developed consists on modeling samples labeled as aged reference wines (5 year old Madeira wines), produced from four different grape varieties, and then analyze how and in which extent young wines (up to 3 years old) come closer to the reference data set. The analysis is based on a comprehensive set of chemical data, including: polyphenolic composition, organic acids, reducing sugars, color and oenological parameters, commonly used as routine quality control information. The study considers several feature extraction methods, such as: Principal Components of Analysis (PCA), Independent Component of Analysis (ICA) and Partial Least Squares (PLS). The classification methodologies tested were: Linear Discriminant Analysis (LDA), nearest neigh bor (k-NN) and Soft Independent Modelling by Class Analogy (SIMCA). The different options of preprocessing/ feature extraction/classification were evaluated and compared using a Monte Carlo approach. From our analysis, the best combination of feature extraction/classification methodologies was PLS/LDA, which presented a classification performance of approximately 90% for three out of the four classes modeled, and of about 78% for the remaining one. Regarding the wines monitored during the first 3 years, our analysis revealed that they indeed mature in relation to the five year old reference wines. Furthermore, for some wines, it is possible to detect differences between the two ageing processes analyzed. This study is of particular importance for this type of wines, where the ageing process plays a central role for attaining the expected quality levels, implying significant risks and costs for local and industrial producers. Notwithstanding the specific case study presented, the strategy outlined can be extrapolated to other products with similar characteristics in terms of their monitoring and process control