Advancing carotenoid Quantification: A new method for semi-quantitative assessment of β -Carotene and lycopene content in food extracts.

Autor: Aguilar-Espinosa M; Unidad de Bioquímica y Biología Molecular de Plantas, Centro de Investigación Científica de Yucatán, Mexico. Electronic address: mgf@cicy.mx., Ek-Ku JE; CONAHCYT, Laboratorio Regional para Estudio y Conservación de Germoplasma (GermoLab) del Centro de Investigación Científica de Yucatán, Parque Científico Tecnológico de Yucatán, Mexico. Electronic address: enrique100196@hotmail.com., Rivera-Madrid R; Unidad de Bioquímica y Biología Molecular de Plantas, Centro de Investigación Científica de Yucatán, Mexico. Electronic address: renata@cicy.mx., Vera-Ku M; CONAHCYT, Laboratorio Regional para Estudio y Conservación de Germoplasma (GermoLab) del Centro de Investigación Científica de Yucatán, Parque Científico Tecnológico de Yucatán, Mexico. Electronic address: marina.vera@cicy.mx.
Jazyk: angličtina
Zdroj: Journal of chromatography. B, Analytical technologies in the biomedical and life sciences [J Chromatogr B Analyt Technol Biomed Life Sci] 2023 Dec 01; Vol. 1231, pp. 123929. Date of Electronic Publication: 2023 Nov 22.
DOI: 10.1016/j.jchromb.2023.123929
Abstrakt: Carotenoids, such as lycopene and β-carotene, have been widely recognized for their antioxidant properties and potential health benefits. Accurate quantification of carotenoids in plant extracts is essential for nutritional assessment, quality control, and research investigations. This study introduces an innovative method for quantifying lycopene and β-carotene, in plant extracts and aims to bridge the gap between complex and expensive carotenoid quantification techniques and the need for accessible methods that can be widely adopted. The primary difference between HPLC and HPTLC lies in the medium used for separation. HPLC employs a liquid phase within columns, while HPTLC utilizes a thin layer of adsorbent on a plate. This distinction impacts factors like equipment, cost, and analysis time. The VisionCats software, combined with the CAMAG Visualizer-2, allows the semi-quantification of metabolites using an image-based evaluation method enabling the simultaneous assessment of qualitative and semi-quantitative information from the HPTLC images. Sample preparation involves washing and drying the vegetal material, followed by dichloromethane extraction. HPTLC analysis is performed using the CAMAG Advanced Herbal System, and the validation studies include establishing calibration curves and determining the detection threshold and minimum quantification threshold for lycopene and β-carotene. Specificity and precision were evaluated to ensure accurate identification and repeatability of the method. Data analysis involves selecting the regression method based on the nature of the data and assessing the goodness of fit using the R2 value. The results showed distinct peaks corresponding to lycopene and β-carotene in the chromatograms of the plant extract samples. The visualizer-based method demonstrates good specificity and precision, with no interfering peaks observed and low relative standard deviation. The method shows promising results regarding specificity, precision, and reliability. It has the potential for broader implementation in carotenoid research and rapid monitoring of carotenoid content in various agricultural and food products, particularly in resource-limited settings. Further optimization and validation on a wider range of samples would enhance the applicability of this method in carotenoid research. Sample preparation involves washing and drying the vegetal material, followed by dichloromethane extraction. HPTLC analysis is performed using the CAMAG Advanced Herbal System, and the validation studies include establishing calibration curves and determining the detection threshold and minimum quantification threshold for lycopene and β-carotene. Specificity and precision were evaluated to ensure accurate identification and repeatability of the method. Data analysis involves selecting the regression method based on the nature of the data and assessing the goodness of fit using the R2 value. The results showed distinct peaks corresponding to lycopene and β-carotene in the chromatograms of the plant extract samples. The visualizer-based method demonstrates good specificity and precision, with no interfering peaks observed and low relative standard deviation. The method shows promising results regarding specificity, precision, and reliability. It has the potential for broader implementation in carotenoid research and for rapid screening and monitoring of carotenoid content in various agricultural and food products, particularly in resource-limited settings. Further optimization and validation on a wider range of samples would enhance the applicability of this method in carotenoid research.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: