Chemistry Department, American University in Cairo, New Cairo, Egypt.
College of Marine Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China; Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition, Ministry of Education, Fuzhou 350002, China.
Food Chem. 2022 Nov 15;394:133529. doi: 10.1016/j.foodchem.2022.133529. Epub 2022 Jun 18.
Green analysis is defined as the analysis of chemicals in a manner where sample extraction and analysis are performed with least amounts of steps, low hazardous materials, while maintaining efficiency in terms of analytes detection. Coffee and cocoa represent two of the most popular and valued beverages worldwide in addition to their several products i.e., cocoa butter, chocolates. This study presents a comprehensive overview of green methods used to evaluate cocoa and coffee seeds quality compared to other conventional techniques highlighting advantages and or limitations of each. Green techniques discussed in this review include solid phase microextraction, spectroscopic techniques i.e., infra-red (IR) spectroscopy and nuclear magnetic resonance (NMR) besides, e-tongue and e-nose for detection of flavor. The employment of multivariate data analysis in data interpretation is also highlighted in the context of identifying key components pertinent to specific variety, processing method, and or geographical origin.
绿色分析被定义为以最少的步骤、低危险材料进行化学物质分析的方法，同时保持分析物检测的效率。咖啡和可可除了它们的几种产品，如可可脂、巧克力之外，还代表了全球最受欢迎和最有价值的两种饮料。本研究全面概述了用于评估可可和咖啡豆质量的绿色方法，与其他常规技术相比，突出了每种方法的优点和/或局限性。本文综述中讨论的绿色技术包括固相微萃取、光谱技术，如红外（IR）光谱和核磁共振（NMR），以及电子舌和电子鼻用于检测风味。多元数据分析在数据解释中的应用也在识别与特定品种、加工方法和/或地理来源相关的关键成分方面得到了强调。
