Abstract

Consuming caffeine in inappropriate amounts can disrupt various aspects, especially health. Controlling intake by knowing the caffeine levels in coffee is necessary to reduce the potential negative impacts. This research focuses on the detection of caffeine in Robusta coffee at two different concentrations (1:10 and 1:20 g/mL) and its relationship with yeast metabolism. An amperometric biosensor with a transimpedance amplifier to measure caffeine levels is used which has the advantages of sensitivity, cost-effectiveness, real time monitoring, biocompatibility, and reliable measurements. The data were statistically analyzed using ANOVA and visualized using Principal Component Analysis (PCA). The results revealed a concentration -dependent decrease in biosensor readings as caffeine levels increased (0.1, 0.5, 1, 1.5, and 2 mM), indicating caffeine's ability to inhibit yeast oxygen consumption and oxygen-dependent metabolic processes. The sensitivity of the biosensor in detecting caffeine is 36.66 mV/mM. PCA uncovered complex patterns, relationships, and variations within the caffeine data. PC1 and PC2, the first two principal components, collectively explained 86.3% of the data's variance. Eigenvalues for both PCs were greater than 1, highlighting their significance in understanding the dataset's complexity. This research enhances our understanding of caffeine content in Robusta coffee and its effects on yeast metabolism, providing valuable insights for the coffee industry. This use of yeast biosensors offers efficiency, and adaptability that make that biosensor valuable in a variety of scientific and industrial contexts.

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