UV-Vis spectroscopy method for authentication studies on olive oils and vinegars

This research project addresses three independent studies that are related to the authentication of olive oil and sherry wine vinegar through the usage of UV-Vis spectroscopy. In the first study, an adulteration study was carried out in olive oils by using colored vegetable oils with natural colorants.. Two different procedures were developed aiming at detecting the falsification. The second study presents a novel method based on the standard deviation of normalized spectra at adequate wavelengths. This method has provided an accurate resolution of spectra at individual components in a two-component system which can be used for multicomponent systems with bigger sizes. The method then was effectively applied to different olive oil sets. Finally, the third study was performed in order to determine the characterization of sherry wine vinegars. For the first time, chromatic parameters were used for characterizing sherry wine vinegar according to the type of the wine used and the acetification process followed during the elaboration process. Once again, the results were satisfactory. The UV-Vis spectroscopic technique has been proven to be a versatile tool for a rapid and nondestructive analysis in oil and vinegar samples based on the study of their spectra

Scientific communication skills

Proporcionar a los alumn@s de recursos y herramientas que les ayuden a preparar y realizar ponencias orales científicas de forma organizada usando un correcto lenguaje científico tecnológico.La presentación está compuesta de 54 diapositivas, organizadas para dar en 5 horas lectivas. Incluye teoría y actividades para realizar

Scientific writing

El objetivo de este material es proporcionar a los alumnos las herramientas necesarias para poder elaborar material científico de forma adecuada: artículos, tesis, ensayos.... Incluye además pautas para manejar de forma eficaz los buscadores bibliográficos y los gestores de referencias, así como dar difusión a los resultados científicos en redes sociales.Se trata de una presentación que incluye 63 diapositivas organizadas para dar en 5 horas lectivas

Interpreting the near infrared region of explosives

The NIR spectra from 1000 to 2500 nm of 18 different explosives, propellant powders and energetic salts were collected and interpreted. NIR spectroscopy is known to provide information about the combination bands and overtones of highly anharmonic vibrations as those occurring in XH bonds (CH, NH and OH). Particularly intense and complex were the bands corresponding to the first combination region (2500&#-1900&;8239#nm) and first overtone stretching mode (2nu) of CH and NH bonds (1750&#-1450&;8239#nm). Inorganic oxidizing salts including sodium/potassium nitrate, sodium/potassium chlorate, and sodium/potassium perchlorate displayed low intense or no NIR bands

Toxicidad de las setas. Aspectos Químicos

Material docente que explica desde un punto de vista químico, la toxicidad de las setas, las causas de dicha toxicidad así como los síntomas y enfermedades que producen.Universidad de Cádiz, Aula Universitaria del Estrecho y Asociación Micológica de AlgecirasPDF con 63 página

A Novel Method Based on Headspace-Ion Mobility Spectrometry for the Detection and Discrimination of Different Petroleum Derived Products in Seawater

The objective of the present study is to develop an optimized method where headspace-ion mobility spectrometry is applied for the detection and discrimination between four petroleum-derived products (PDPs) in water. A Box-Behnken design with a response surface methodology was used, and five variables (incubation temperature, incubation time, agitation, sample volume, and injection volume) with influences on the ion mobility spectrometry (IMS) response were optimized. An IMS detector was used as a multiple sensor device, in which, each drift time acts as a specific sensor. In this way, the total intensity at each drift time is equivalent to multiple sensor signals. According to our results, 2.5 mL of sample incubated for 5 min at 31 degrees C, agitated at 750 rpm, and with an injection volume of 0.91 mL were the optimal conditions for successful detection and discrimination of the PDPs. The developed method has exhibited good intermediate precision and repeatability with a coefficient of variation lower than 5%, (RSD (Relative Standard Deviation): 2.35% and 3.09%, respectively). Subsequently, the method was applied in the context of the detection and discrimination of petroleum-derived products added to water samples at low concentration levels (2 mu L center dot L-1). Finally, the new method was applied to determine the presence of petroleum-derived products in seawater samples.This work has been co-financed by the 2014-2020 ERDF Operational Program and by the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia. Project reference: "FEDER-UCA18-107214"

Machine learning approaches over ion mobility spectra for the discrimination of ignitable liquids residues from interfering substrates

In arson fires, ignitable liquids (ILs) are frequently used to start combustion. For this reason, detecting IL residues (ILRs) at the fire scene is a key factor in fire investigation to determine whether a crime has been committed as well as to establish the modus operandi of the perpetrator. In the present study, the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) for the detection of ILRs in fire debris from complex matrices in combination with machine learning (ML) tools is proposed as an alternative to the traditional method, based on gas chromatography–mass spectrometry (GC-MS), described by the ASTM E1618 standard method. For this purpose, petroleum-derived substrates (vinyl, nylon, and polyester) and natural substrates (cotton, cork and linoleum) burned alone and with different ILs (gasoline, diesel, ethanol and charcoal starter with kerosene) were used. In addition, samples were taken at different times (0, 1, 6, 12, 24 and 48 h) after the fire was finished. The ion mobility sum spectrum (IMSS) of each sample was obtained and different ML algorithms were applied. The first derivative was performed at the IMSS, as well as a Savitzky-Golay filter. Hierarchical cluster analysis (HCA) revealed a clustering trend as a function of substrate and ILs used, where the studied sampling times did not affect the resulting clusters. The classification models for the detection of the presence of ILRs have high performance with an accuracy of 100% for support vector machines (SVM) and random forest model (RF), followed by linear discriminant analysis (LDA) with an accuracy of 86.67%. When discriminating the type of ILs used, the RF model obtained an accuracy of 100%, followed by the LDA with 97.22% and finally the SVM model with an accuracy of 93.06%. In addition, a simple web application has been developed where the trained models can be used, so any researcher can apply the method to detect ILRs in fire debris

Novel method based on ion mobility spectroscopy for the quantification of adulterants in honeys

According to European Union Regulation, honey is a food product whose composition cannot be modified. However, high-quality honey is often adulterated by adding sweeteners of other sugar compounds. This paper studies the suitability of Ion Mobility Spectra from generated headspace as a method for the detection and discrimination of honey adulterated by different substances. A Box-Behnken design in conjunction with a re sponse surface methodology was employed to optimize five different variables related to headspace generation (incubation temperature, incubation time, injection volume, weight of the samples and pre-heating time). The resulting model showed a regression coefficient of R2 = 88.07%, it is therefore suitable for a reliable selection of the experimental variables. Repeatability and intermediate precision were also evaluated, and coefficients of variation below 5% were obtained (CV of 4.6% and 4.2% respectively). The developed method has been applied to different samples resulting for the mixture of honey and other sweeteners at different percentages (5%–50%) in an attempt to mimic the adulterated products that are more commonly found in the market. A thorough and exact classification (100%) with regards to the presence/absence of adulterant as well as the type of adulterant used has been achieved. A Partial Least Squares regression model was completed in order to determine the percentage of the different adulterants. The prediction error was below 4% in all the cases. These results de monstrate the applicability of the developed method for the detection and quantification of adulterated honey with different adulterant contents

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches

Extraction of Anthocyanins and Total Phenolic Compounds from Açai (Euterpe oleracea Mart.) Using an Experimental Design Methodology. Part 3: Microwave-Assisted Extraction

In this work, two methods based on microwave-assisted extraction techniques for the extraction of both anthocyanins and total phenolic compounds from acai have been developed. For that, a full factorial design (Box-Behnken design) has been used to optimize the following four variables: solvent composition (25-75% methanol in water), temperature (50-100 degrees C), pH (2-7), and sample/solvent ratio (0.5 g: 10 mL-0.5 g: 20 mL). The anthocyanins and total phenolic compounds content have been determined by ultra high-pressure liquid chromatography and Folin-Ciocalteu method, respectively. The optimum conditions for the extraction of anthocyanins were 38% MeOH in water, 99.63 degrees C, pH 3.00, at 0.5 g: 10 mL of ratio, while for the extraction of total phenolic compounds they were 74.16% MeOH in water, 99.14 degrees C, pH 5.46, at 0.5 g: 20 mL of ratio. Both methods have shown a high repeatability and intermediate precision with a relative standard deviation lower than 5%. Furthermore, an extraction kinetics study was carried out using extraction periods ranging from 2 min until 25 min. The optimized methods have been applied to acai-containing real samples. The results with such real samples have confirmed that both methods are suitable for a rapid and reliable extraction of anthocyanins and total phenolic compounds