Potential of Arabica Coffee Beans from Northern Thailand: Exploring Antidiabetic Metabolites through Liquid Chromatography with Tandem Mass Spectrometry (LC-MS/MS) Metabolomic Profiling across Diverse Postharvest Processing Techniques

泰国北部阿拉比卡咖啡豆的潜力:通过液相色谱-串联质谱(LC-MS/MS)代谢组学分析探索不同采后加工技术下的抗糖尿病代谢物

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Abstract

Coffee, a widely consumed beverage worldwide, undergoes postharvest methods that influence its physicochemical characteristics, while roasting modulates its composition, affecting sensory attributes. This study investigates the impact of distinct postharvest methods (washed and natural) on the antidiabetic activities, including α-amylase and DPP4, as well as the phytochemical profiling of geological indicator (GI) coffee beans (Coffea arabica L.). The results indicate notable differences in antidiabetic activity and phytochemical profiles between washed and natural processing methods. Coffee beans processed naturally exhibit significant suppression of DPP4 and α-amylase activities (p-value < 0.01) compared to beans processed using the washed technique. TLC profiling using the ratios of the solvent systems of ethyl acetate/dichloromethane (DCM) and acetone/DCM as separation solvents reveals dominant spots for the washed technique. LC-MS/MS-based untargeted metabolomics analysis using principle component analysis (PCA) clearly segregates samples processed by the natural and washed techniques without any overlap region. A total of 1114 phytochemicals, including amino acids and short peptides, are annotated. The natural processing of coffee beans has been shown to yield a slightly higher content of chlorogenic acid (CGA) compared to the washed processing method. Our findings highlight the distinct bioactivities and phytochemical compositions of GI coffee beans processed using different techniques. This information can guide consumers in choosing coffee processing methods that offer potential benefits in terms of alternative treatment for diabetes.

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