Browsing by Subject "Gas chromatography"

Now showing 1 - 6 of 6
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    A volatilomic approach using ion mobility and mass spectrometry combined with multivariate chemometrics for the assessment of lemon juice quality
    (Elsevier, 2024-11-09) Giménez Campillo, Claudia; Arroyo Manzanares, Natalia; Campillo Seva, Natalia; Díaz García, Miriam Cristina; Viñas López-Pelegrin, Pilar; Química Analítica
    Lemon (Citrus limon (L.) Burm.) is a citrus fruit known for its high nutritional value and potent antioxidant activity. Lemon juice, obtained by squeezing the fruit, is widely used in the kitchen for its acidic taste to flavour dishes and drinks. It has also been attributed with various medicinal properties to treat conditions such as sore throat, fever, rheumatism and hypertension. Ensuring the quality and safety of lemon juice, as well as its geographical origin, is not easy due to the scarcity of analytical methods available for this purpose, which makes it difficult to detect adulterations. To meet this challenge of testing the authenticity and safety of lemon juice, multiple physicochemical parameters need to be evaluated, which is expensive and time-consuming, so it is of great interest to develop an alternative simple method. In this research, two alternative analytical methods were developed and optimized for the analysis of lemon juice samples based on headspace gas chromatography coupled to both mass spectrometry (HS-GC-MS) or ion mobility spectrometry (HS-GC-IMS). These new methods were compared with the method currently used in the food industry for quality control of juices, which is Fourier transform near infrared spectroscopy (FT-NIR). A total of 159 samples belonging to different lemon varieties were analysed by measuring the physicochemical parameters, FT-NIR spectra and fingerprinting of the juice samples based on the total volatile compounds profile by GC-MS and GC-IMS. Partial least squares (PLS) regression models were then constructed and all models were validated by paired tests with the values measured by the reference chemical methods. The models developed confirm that both HS-GC-MS and HS-GC-IMS methods are viable alternatives for predicting physicochemical parameters and ensuring lemon juice quality. Finally, the data were used to build chemometric models using orthogonal partial least squares discriminant analysis (OPLSDA) to distinguish lemon juices according to the lemon variety used in their manufacture. Very promising models were obtained with the HS-GC-MS and HS-GC-IMS data, suggesting the potential use of the volatile profile for lemon variety confirmation. Consequently, fingerprinting represents an alternative proposal to the conventional method applied in the food industry based on the use of chemical reference parameters or the use of the NIR technique.
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    Discrimination of the geographical origin of peaches by the monitoring of volatile organic compounds by gas chromatography with mass spectrometry and chemometric tools
    (Elsevier, 2024-02-24) Giménez Campillo, Claudia; Arroyo Manzanares, Natalia; Pastor Belda, Marta; Campillo Seva, Natalia; Viñas López-Pelegrin, Pilar; Química Analítica
    The peach is one of the most popular and widely consumed fruits in Europe. Spain is the largest peach-producing country in the world with several growing areas recognised by consumers. This work focuses on the development, optimisation and validation of a non-targeted metabolomics strategy for the determination of peach volatile organic compounds from different origins by headspace gas chromatography coupled to mass spectrometry (HS–GC–MS). The volatil profile found in each sample is used to classify peaches according to their origin. The results obtained were processed using MS-DIAL software and 279 features were detected, of which 102 volatile compounds were tentatively identified and 30 of them could also be quantified. In addition, the areas of all the features were used to build models based on orthogonal partial least squares discriminant analysis (OPLS-DA) to differentiate peaches according to their geographical origin. A very promising model was obtained, with a validation rate of 90.32%, which means that it could be used to guarantee the Protected Designation of Origin of different peaches with a simple analysis.
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    Open Access
    Fingerprinting of volatile organic compounds and discrimination of pear samples by gas chromatography-ion mobility spectrometry
    (Elsevier, 2025-05-20) Giménez Campillo, Claudia; Pastor Belda, Marta; Campillo Seva, Natalia; Arroyo Manzanares, Natalia; Viñas López-Pelegrin, Pilar; Química Analítica
    The pear contains many volatile organic compounds that are responsible for its distinctive aroma, flavour and texture. The aim of this work was to develop, optimise and validate an analytical method for the determination of volatile compounds in pears using headspace gas chromatography coupled to ion mobility spectrometry. A total of 254 samples from four cultivars were analysed, and a partial least squares discriminant analysis model using 93 markers allowed differentiation between cultivars with 100 % accuracy and a Q2 of 0.878. Additionally, a total of 227 Ercoline pears collected at different stages of ripening were analysed. For the first time, a predictive model based on 75 markers was used to determine pear ripeness, achieving 100 % accuracy and a Q2 of 0.856. A total of 22 compounds were identified and quantified in the samples and key compounds were determined for each cultivar and ripening stage.
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    Head-space gas chromatography coupled to mass spectrometry for the assessment of the contamination of mayonnaise by yeasts
    (Elsevier B.V., 2019-08-15) Arroyo-Manzanares, N.; Markiv, B.; Hernández, J.D.; López-García, I.; Guillén, I.; Vizcaíno, P.; Hernández Córdoba, Manuel; Viñas López-Pelegrín, Pilar; Química Analítica
    Head-space (HS) gas chromatography (GC) coupled to mass spectrometry (MS) is proposed for the assessment of the contamination of mayonnaise as an alternative to plate counting, which is the technique commonly used for evaluating microbial contamination. More specifically, this method was applied in the detection of Candida metapsilosis and Zygosaccharomyces bailii, both of great importance in term of food spoilage since they are resistant to many of the common methods of food preservation. Different chemometric models were investigated using the data obtained by GC-MS (m/z profile, area of the chromatographic peaks and entire chromatographic profile), in order to obtain the highest classification success. The best results were obtained using the chromatographic profile (success rate of 92%). Contaminated samples could also be classified according to the concentration of yeast, obtaining a success rate of 87.5%. Finally, a chemometric model was constructed in an attempt to differentiate between strains.
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    Ion mobility spectrometry and mass spectrometry coupled to gas chromatography for analysis of microbial contaminated cosmetic creams
    (Elsevier, 2020-07-11) García Nicolás, María; Arroyo Manzanares, Natalia; Hernández, Juan de Dios; Guillén, Isidro; Vizcaino, Pascuala; Sánchez Rubio, Marta; López García, Ignacio Francisco; Hernández Córdoba, Manuel; Viñas López-Pelegrin, Pilar; Química Analítica
    The most commonly used technique for monitoring microbial contamination in cosmetic products is plate counting. In this contribution, headspace - gas chromatography (HS-GC) coupled to mass spectrometry (MS) or ion mobility spectrometry (IMS) is proposed as a technique to evaluate rapidly and accurately the state of microbial colonies in cosmetic creams using the volatile organic compounds produced by microorganisms (MVOC). The work focuses on monitoring two of the microorganisms that most frequently occur in such creams, Candida albicans and Staphylococcus aureus. In addition, two different types of ingredient with antimicrobial properties (a chemical preservative and a natural preservative) were added to study the behaviour of these microorganisms under different conditions. The facial creams were elaborated and inoculated with the two above microorganisms, and then sampled weekly for 4 weeks, analysing the evolution of the MVOCs by HS-GC-MS and HS-GC-IMS. In addition, microbial contamination was determined by the classical plate counting method. The pH, colour, viscosity and water activity parameters were also measured. The use of chemometric tools is essential because of the large amount of data generated, and different models based on discriminant analysis with an orthogonal projection on latent structures (OPLS-DA) were constructed. The optimal models obtained by both analytical techniques allowed differentiation between contaminated and non-contaminated creams, with a validation success rate of 94.4%. In addition, MVOC monitoring also allowed assessment of the microbial concentration.
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    Ion mobility spectrometry as an emerging tool for characterization of the volatile profile and identification of microbial growth in pomegranate juice
    (Elsevier, 2021-12-17) Castell Martínez, Ana; Arroyo Manzanares, Natalia; Hernández, Juan de Dios; Guillén, Isidro; Vizcaíno, Pascuali; López García, Ignacio Francisco; Hernández Córdoba, Manuel; Viñas López-Pelegrin, Pilar; Química Analítica
    Headspace - gas chromatography (HS-GC) coupled to ion mobility spectrometry (IMS) is proposed as an alternative to plate counting to detect and quantify the microbial contamination in pomegranate juice. Thus, contaminated samples by the yeast Saccharomyces cerevisiae were monitored during 6 non-consecutive days over two weeks using two types of preservatives (a sorbate/benzoate mixture and a natural preservative from vegetable extracts). IMS is an emerging technique with high potential for volatile organic compounds (VOCs) monitoring because its high sensitivity and separation power of ions. The fingerprint of the samples allowed to establish difference in the volatile composition of contaminated and non-contaminated samples. Ethyl acetate, ethyl butyrate and limonene were characterized obtaining limits of detection and quantification below 0.029 and 0.097 μg/g, respectively. Furthermore, chemometric models were performed to detect contaminated pomegranate juice and to assess the concentration of yeast, obtaining a validation success of 100 and 90.91%, respectively.