Implementación de un sistema de aseguramiento de calidad en un laboratorio industrial: aplicaciones quimiométricas

[Resumen] Se han analizado los requisitos necesarios para la implantacion de un sistema de aseguramiento de la calidad, sometido a las directrices internacionales, para su posterior implantacion en un laboratorio industrial. Los estudios se han basado en la norma ISO 9002 (y la serie en 45000), tomando dos grandes ejes de trabajo: garantia de calidad (gestion, personal, organizacion, estructuracion de tareas...) y control de calidad. En este ultimo apartado, se han hecho diversas aplicaciones en temas de: diseño experimental, ejercicios interlaboratorio, analisis multivariante de productos, prediccion de propiedades fisico-quimicas de gasolinas y kerosenos mediante regresion multivariante acoplada con espectros copia infrarroja (zona media) con transformada de fourier. Se propone una posible via para realizar el analisis de la calidad de un producto (keroseno, combustible de aviacion) empleando la estadistica multivariante

Misidentification of PVC Microplastics in Marine Environmental Samples

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Poly(vinylchloride), PVC, is the third most demanded polymer in Europe although its presence in marine ecosystems, surprisingly, is scarcely observed. This does not reflect neither its production nor its widespread usage. Therefore, it is imperative to understand why this may happen. PVC is the least stable of the high-tonnage produced polymers as it has the highest sensitivity towards UV radiation and, therefore, photo-degradation is of maximum relevance. The big amount of additives included in PVC formulations, weathering and the different treatments required to isolate it from environmental samples can modify the surface of PVC microplastics, making their spectral identification/quantification an analytical challenge. All these factors can lead to large PVC underestimations in environmental studies, in which other polymers like PE, PP or PS outstand. Further, the fact that the infrared spectrum of weathered PVC can be confounded with that of PE is of most relevance and, therefore, remarkable misidentifications and/or wrong quantifications may occur. In this work some relevant factors that can explain the low percentages of PVC reported in the literature are discussed and special emphasis is made on the need for suitable spectroscopic databases that include PVC weathered standards. This has been confirmed by the results of a detailed study of PVC weathering under pilot-scale conditions, monitoring its spectroscopic and physical changes over time.This work is part of the project MicroplastiX (Grant PCI2020-112145) supported by the JPI_Oceans Program and by MCIN/AEI/10.13039/501100011033 and the European Union “Next Generation EU”/PRTR”; by the LAnd-Based solutions for PLAStics in the Sea (LABPLAS) Grant H2020- 101003954 and “ChemPlas” Project supported by the Agencia Estatal de Investigación (Grant PID2019-108857RB-C31/AEI/10.13039/501100011033). The Program ‘Consolidación e Estructuración de Unidades de Investigación Competitivas” of the Galician Government (Xunta de Galicia) is also acknowledged (Grant ED431C 2021/56). Funding for open access charge: Universidade da Coruña/CISUGXunta de Galicia; ED431C 2021/5

Development of an Analytical Procedure to Analyze Microplastics in Edible Macroalgae Using an Enzymatic-Oxidative Digestion

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Besides being food and a refuge to marine species, macroalgae are a powerful and renewable economic resource. However, they may introduce microplastics (MPs) in the trophic chain. We developed a reliable analytical method to characterize and quantify MPs in common and edible macroalgae. Several digestion methods and filters, along with various measurement options, were studied. A new enzymatic-oxidative protocol with a unique final filtration was selected and validated with a mixture of 5 commercial macroalgae (Undaria pinnatifida spp, Porphyra spp, Ulva spp, Laminaria ochroleuca and Himanthalia elongate). Further, it was shown that washing the macroalgae to release MPs is suboptimal and the potential adhesion of MPs to macroalgae was evaluated. A filter subsampling strategy that scans 33.64 % of its surface reduced the time required to characterize <70 μm particles and fibres directly on the 47 mm diameter filter using an IR microscope (1 sample/day).This work is a part of the projects MicroplastiX (Grant PCI2020-112145, JPI Oceans Project supported by MCIN/AEI/10.13039/501100011033 and by the European Union “Next Generation EU/PRTR”) and LAnd-Based solutions for PLAStics in the Sea, LABPLAS, (Grant H2020-101003954 supported by the EU H2020 program). The Program “Consolidación e Estructuración de Unidades de Investigación Competitivas” of the Galician Government (Xunta de Galicia) is also acknowledged (Grant ED431C 2021/56). Funding for open access charge: Universidade da Coruña/CISUGXunta de Galicia; ED431C 2021/5

New Ways for the Advanced Quality Control of Liquefied Natural Gas

[Abstract] Currently, gas chromatography is the most common analytical technique for natural gas (NG) analysis as it offers very precise results, with very low limits of detection and quantification. However, it has several drawbacks, such as low turnaround times and high cost per analysis, as well as difficulties for on-line implementation. With NG applications rising, mostly thanks to its reduced gaseous emissions in comparison with other fossil fuels, the necessity for more versatile, fast, and economic analytical methods has augmented. This work summarizes the latest advances to determine the composition and physico-chemical properties of regasified liquid natural gas, focusing on infrared spectroscopy-based techniques, as well as on data processing (chemometric techniques), necessary to obtain adequate predictions of NG properties.Part of this work was performed under the EMPIR 16ENG09 project ‘Metrological support for LNG and LBG as transport fuel (LNG III)’. This project has received funding from the EMPIR programme co-financed by the Participant States and from the European Union’s Horizon 2020 Research and Innovation programme. Mestrelab, Reganosa and Naturgy are acknowledged for hiring the services of the Group of Applied Analytical Chemistry for FTIR method development. The Program “Consolidación e Estructuración de Unidades de Investigación Competitivas” of the Galician Government (Xunta de Galicia) is also acknowledged (Grant ED431C 2021/56).Xunta de Galicia; ED431C 2021/5

Monitorization of Polyamide Microplastics Weathering Using Attenuated Total Reflectance and Microreflectance Infrared Spectrometry

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] The EU goal to reduce marine plastic litter by ca. 30% by 2020 stressed the need to deploy analytical methods to ascertain the polymeric nature of a residue. Furthermore, as plastics age under natural conditions and usual databases do not include their weathered spectra, (micro)plastics in environmental samples may be unidentified. In this paper, polyamide (nylon) microplastics weathering was monitored because of its ubiquity in household commodities, clothes, fishery items and industry, whose residues end up frequently in the environment. Infrared spectra (ATR and microreflectance) and Scanning Electron Microscopy (SEM) images were collected periodically while exposing nylon to controlled weathering. It was seen that ATR was more sensitive than microreflectance to monitor the structural evolution of polyamide and that the spectra and the surface of weathered microplastics showed remarkable differences with the pristine material, which stresses the need for considering its evolution when identifying microplastics in environmental studies. The evolution of six band ratios related to the chemical evolution of this polymer are presented. SEM images revealed the formation of secondary microplastics at the most advanced weathering stages of polyamide.This work was supported through the JPI-Oceans BASEMAN and MicroplastiX projects, sponsored by the Spanish Ministry of Science and Innovation (Agencia Estatal de Investigación) -partially financed by the European Regional Development Fund program- (Grants: PCIN-2015-170-C02-01; PCIN- PCI2020-112145 and CTM2016-77945-C3-3-R, ARPA-ACUA). The Program ‘Consolidación e Estructuración de Unidades de Investigación Competitiva’ of the Galician Government (Xunta de Galicia) is also acknowledged (Grant: ED431C-2017/28)Xunta de Galicia; ED431C-2017/2

Multiway real-time PCR gene expression profiling in yeast Saccharomyces cerevisiae reveals altered transcriptional response of ADH-genes to glucose stimuli

<p>Abstract</p> <p>Background</p> <p>The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena. In multiway studies samples are characterized by their expression profiles to monitor changes over time, effect of treatment, drug dosage etc. Here we perform a multiway study of the temporal response of four yeast <it>Saccharomyces cerevisiae </it>strains with different glucose uptake rates upon altered metabolic conditions.</p> <p>Results</p> <p>We measured the expression of 18 genes as function of time after addition of glucose to four strains of yeast grown in ethanol. The data are analyzed by matrix-augmented PCA, which is a generalization of PCA for 3-way data, and the results are confirmed by hierarchical clustering and clustering by Kohonen self-organizing map. Our approach identifies gene groups that respond similarly to the change of nutrient, and genes that behave differently in mutant strains. Of particular interest is our finding that <it>ADH4 </it>and <it>ADH6 </it>show a behavior typical of glucose-induced genes, while <it>ADH3 </it>and <it>ADH5 </it>are repressed after glucose addition.</p> <p>Conclusion</p> <p>Multiway real-time PCR gene expression profiling is a powerful technique which can be utilized to characterize functions of new genes by, for example, comparing their temporal response after perturbation in different genetic variants of the studied subject. The technique also identifies genes that show perturbed expression in specific strains.</p

A Reliable Method for the Isolation and Characterization of Microplastics in Fish Gastrointestinal Tracts Using an Infrared Tunable Quantum Cascade Laser System

[Abstract] Societal and environmental concern due to frequent reports of microplastics in fish stomachs raised as they may accumulate along the trophic chain. The request for analysing microplastics in fish stresses two major analytical issues: sample treatment and final characterization. The, so far, workhorse for chemical characterization is infrared spectroscopy which is time-consuming. Here, a quantum cascade laser-based device is used to accelerate the characterization stage. Its novelty poses new challenges for sample processing and particle handling because the unknown particles must be transferred to a reflective slide. In this study, three sample digestion protocols (alkaline-oxidative with H2O2, and alkaline-oxidative with NaClO and enzymatic-oxidative) and three different procedures to transfer the filter cake to reflective slides are compared. A simplified enzymatic-oxidative digestion (validated through an interlaboratory exercise) combined with a Syncore® automatic evaporation system and a Laser Direct Infrared Imaging (LDIR) device is proposed first time as a reliable and relatively fast method to treat gastrointestinal tracts of fish. Analytical recoveries were studied using samples of Scomber scombrus and they were ca. 100% for big –i.e., >500 μm- and ca. 90% for medium –i.e., 200–300 μm- particles and ca. 75% for 10 μm thick fibres.This research was supported by the LAnd-Based Solutions for PLAstics in the Sea Project (LABPLAS Project), Grant Agreement No. 101003954, under the European Union's Horizon 2020 research and innovation programme, and the Integrated approach on the fate of MicroPlastics (MPs) towards healthy marine ecosystems Project (MicroplastiX project), Grant PCI2020-112145, supported by the JPI_Oceans Program and by MCIN/AEI/10.13039/501100011033 and the European Union “Next Generation EU/PRTR”. The Program ‘Consolidación e Estructuración de Unidades de Investigación Competitivas” of the Galician Government (Xunta de Galicia) is also acknowledged (Grant ED431C 2021/56)Xunta de Galicia; ED431C 2021/5

Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils

[Abstract] Purpose – The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate multiple regression, principal components analysis, partial least squares, and support vector regression (SVR)). Design/methodology/approach – The rationale behind the use of SVR was the fuzzy characteristics of the signal and its inherent ability to find nonlinear, global solutions in highly complex dimensional input spaces. Thus, SVR allows extracting useful information from calibration samples that makes it possible to characterize physical-chemical properties of the lubricant oils. Findings – A dataset of 42 spectra measured from oil standards was studied to assess the concentration of copper into the oils and, thus, evaluate the wearing of the machinery. It was found that the use of SVR was very advantageous to get a regression model. Originality/value – The use of genetic algorithms coupled to SVR was considered in order to reduce the time needed to find the optimal parameters required to get a suitable prediction model

Development of a Fast and Efficient Method to Analyze Microplastics in Planktonic Samples

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Microplastics (MPs) affect plankton (a basis of the trophic chain) and planktivorous fish can ingest them through food confusion or by trophic transmission. Consensus to determine MPs in plankton is lacking and, so, three digestion treatments were evaluated: Alkaline (potassium hydroxide) and enzymatic (protease plus lipase) digestions, both combined with a hydrogen peroxide stage; and an oxidative method using a surfactant (sodium dodecyl sulfate) plus hydrogen peroxide. The alkaline method using potassium hydroxide was found to damage polystyrene. MPs were identified with a stereomicroscope and characterized by reflectance infrared microscopy in semi-automatic mode (using dedicated multi-well aluminium plates). Analytical recoveries for polypropylene, polystyrene, polyethylene, polyamide, polyvinyl chloride and polyethylene terephthalate were higher than 75%, 82% and 83% for the alkaline, enzymatic and oxidative treatments, respectively. The enzymatic method was successfully validated in a European interlaboratory exercise and the oxidative method was demonstrated to be a reliable, fast and cheaper alternative.The Spanish Government (Ministerio de Economía y Competitividad and Ministerio de Ciencia e Innovación-Agencia Estatal de Investigación) and the JPI-Oceans European Program are acknowledged by the BASEMAN (PCIN-2015-170-C02-01, with FEDER/ERDF funds) and the MicroplastiX (PCIN-PCI2020-112145) projects. Thanks are given also to the Spanish Government by the CTM2016-77945-C3-3-R (ARPA-ACUA) Grant. The Galician Government (“Xunta de Galicia”) is acknowledged for its support to the QANAP group (Programa de Consolidación y Estructuración de Unidades de Investigación Competitiva. Ref. ED431C 2017/28) partially financed by FEDER/ERDF fundsXunta de Galicia; ED431C 2017/2

Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice Classification

Research article[Abstract] Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected