Articles producció científicaQuímica Analítica i Química Orgànica

FT-NIRS Coupled with PLS Regression as a Complement to HPLC Routine Analysis of Caffeine in Tea Samples

  • Datos identificativos

    Identificador:  imarina:9332751
    Autores:  Ur Rehman N; Al-Harrasi A; Boqué R; Mabood F; Al-Broumi M; Hussain J; Alameri S
    Resumen:
    Daily consumption of caffeine in coffee, tea, chocolate, cocoa, and soft drinks has gained wide and plentiful public and scientific attention over the past few decades. The concentration of caffeine in vivo is a crucial indicator of some disorders-for example, kidney malfunction, heart disease, increase of blood pressure and alertness-and can cause some severe diseases including type 2 diabetes mellitus (DM), stroke risk, liver disease, and some cancers. In the present study, near-infrared spectroscopy (NIRS) coupled with partial least-squares regression (PLSR) was proposed as an alternative method for the quantification of caffeine in 25 commercially available tea samples consumed in Oman. This method is a fast, complementary technique to wet chemistry procedures as well as to high-performance liquid chromatography (HPLC) methods for the quantitative analysis of caffeine in tea samples because it is reagent-less and needs little or no pre-treatment of samples. In the current study, the partial least-squares (PLS) algorithm was built by using the near-infrared NIR spectra of caffeine standards prepared in tea samples scanned by a Frontier NIR spectrophotometer (L1280034) by PerkinElmer. Spectra were collected in the absorption mode in the wavenumber range of 10,000-4000 cm-1, using a 0.2 mm path length and CaF2 sealed cells with a resolution of 2 cm-1. The NIR results for the contents of caffeine in tea samples were also compared with results obtained by HPLC analysis. Both techniques provided good results for predicting the caffeine contents in commercially available tea samples. The results of the proposed study show that the suggested FT-NIRS coupled with PLS regression algorithun has a high potential to be routinely used for the quick and reproducible analysis of caffeine contents in tea samples. For the NIR method, the limit of quantification (LOQ) was estimated as 10 times the error of calibration (root mean square error of calibration (RMSECV)) of the model; thus, RMSEC was calculated as 0.03 ppm and the LOQ as 0.3 ppm.
  • Otros:

    Enlace a la fuente original: https://www.mdpi.com/2304-8158/9/6/827
    Referencia de l'ítem segons les normes APA: Ur Rehman N; Al-Harrasi A; Boqué R; Mabood F; Al-Broumi M; Hussain J; Alameri S (2020). FT-NIRS Coupled with PLS Regression as a Complement to HPLC Routine Analysis of Caffeine in Tea Samples. Foods, 9(6), E827-. DOI: 10.3390/foods9060827
    Referencia al articulo segun fuente origial: Foods. 9 (6): E827-
    DOI del artículo: 10.3390/foods9060827
    Año de publicación de la revista: 2020
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2024-01-27
    Autor/es de la URV: Boqué Martí, Ricard
    Departamento: Química Analítica i Química Orgànica
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    Autor según el artículo: Ur Rehman N; Al-Harrasi A; Boqué R; Mabood F; Al-Broumi M; Hussain J; Alameri S
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Plant science, Microbiology, Health professions (miscellaneous), Health (social science), Food science & technology, Food science
    Direcció de correo del autor: ricard.boque@urv.cat
  • Palabras clave:

    Tea samples
    Pls regression
    Nir spectroscopy
    Hplc analysis
    Caffeine
    Food Science
    Food Science & Technology
    Health (Social Science)
    Health Professions (Miscellaneous)
    Microbiology
    Plant Science
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