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使用薄层色谱-表面增强拉曼光谱法分离和测定可可豆提取物中的可可碱和咖啡因:鉴定与计算洞察

Separation and Determination of Theobromine and Caffeine in Cocoa Beans Extract Using TLC-SERS: Identification and Computational Insights.

作者信息

Rodriguez Maria, Arteaga Ray, Katan Briggit, Figueira Maria, Guzman Romel, Jimmy Castillo

机构信息

Escuela De Quimica Universidad Central de Venezuela Los Chaguaramos, Caracas DC Venezuela.

Instituto De Ciencia y Tecnología De Alimentos Escuela De Biologia Universidad Central de Venezuela Los Chaguaramos, Caracas DC Venezuela.

出版信息

Anal Sci Adv. 2025 Jul 28;6(2):e70033. doi: 10.1002/ansa.70033. eCollection 2025 Dec.

Abstract

In recent years there has been a growing interest in cocoa and their sub products in the world, given the beneficial properties of these products. This interest has led to increased research in the study of the composition of cocoa and its relationship with its varieties, mainly the principal alkaloids, theobromine and caffeine. Venezuela, although a small-scale producer, is recognised worldwide for the quality of its cocoa. This work presents a robust, unambiguous and cost-effective methodology for the rapid and accurate quantification of theobromine and caffeine in cocoa beans extracts from Venezuelan cocoa. Thin layer chromatography (TLC) is used for separation, and alkaloids are identified by their Rf values and by their Raman spectra obtained by surface-enhanced Raman spectroscopy (SERS). In the SERS technique, the spots of separated compounds by TLC were impregnated with a solution of silver nanoparticles and the SERS spectra record. Given the great structural similarity of these alkaloids, principal component analysis (PCA) was used to show that despite the similarities of the Raman spectra, they are perfectly distinguishable. Theoretical calculations were performed using Orca software, obtaining Raman and FTIR spectra, and similarities were found between the theoretical and experimental responses, validating the computational approach. The synergistic integration of TLC for separation, SERS for sensitive detection, PCA for robust differentiation and DFT for theoretical validation offers a cost-effective, rapid and robust analytical platform for the unambiguous identification of theobromine and caffeine in complex matrices. This methodology lays the foundation for future quantitative applications in the evaluation of cocoa quality and origin.

摘要

近年来,鉴于可可及其副产品具有有益特性,全球对其兴趣与日俱增。这种兴趣促使人们对可可成分及其与品种的关系展开更多研究,主要涉及主要生物碱、可可碱和咖啡因。委内瑞拉虽是小规模生产国,但其可可质量在全球备受认可。本文介绍了一种稳健、明确且经济高效的方法,用于快速准确地定量分析委内瑞拉可可豆提取物中的可可碱和咖啡因。采用薄层色谱法(TLC)进行分离,通过比移值(Rf)及其表面增强拉曼光谱(SERS)获得的拉曼光谱来鉴定生物碱。在SERS技术中,用银纳米颗粒溶液浸渍TLC分离出的化合物斑点并记录SERS光谱。鉴于这些生物碱结构高度相似,使用主成分分析(PCA)表明,尽管拉曼光谱相似,但它们完全可区分。使用Orca软件进行理论计算,获得拉曼光谱和傅里叶变换红外光谱(FTIR),并发现理论响应与实验响应之间存在相似性,验证了计算方法。TLC用于分离、SERS用于灵敏检测、PCA用于稳健区分以及DFT用于理论验证这一协同整合,为在复杂基质中明确鉴定可可碱和咖啡因提供了一个经济高效、快速且稳健的分析平台。该方法为未来可可质量和产地评估的定量应用奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a2b6/12303255/23479646f361/ANSA-6-e70033-g006.jpg

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