Mobile Support System for Chemical Compounds Analysis of Specialty Coffee Farms in Chiriquí, Panama

The management of specialty coffee production represents a complex dynamical process characterized by highly nonlinear interconnections between environmental variables, agronomic practices, and chemical compositions. Traditionally, the classification of specialty coffee relies on sensory evaluations conducted by highly certified coffee experts Q-Graders, using a strict, standardized Specialty Coffee Association (SCA) protocol. However, scientific methods that generate spectral fingerprints provide a more reliable guarantee of quality while also ensuring traceability to the farm of origin. Panamanian Geisha coffee is one of the world's most expensive, award-winning microlots frequently exceeding $1,000 per pound, with a 2025 record-breaking price of over 30,000 American dollars per kilogram. This research introduces an integrated framework that combines Precision Agriculture Management Systems (PAMS) to support the identification of the spectral fingerprint using Near-Infrared (NIR) and Fourier Transform Infrared (FTIR) spectroscopy, enabling the objective characterization of chemical processes. A mathematical model is introduced to formally characterize the mobile application's behavior, distributed structure, and inherent constraints. Serving as a mathematical blueprint, this model identifies critical influencing factors and establishes strategic assumptions to distill complex real-world variables into a rigorous, manageable framework. Large-scale experiments conducted across more than 820 coffee farms in Chiriquí, Panama, demonstrate that the proposed decentralized architecture effectively coordinates the acquisition and synchronization of georeferenced chemical data. The decentralized architecture of the application utilizes private blockchain technology to facilitate autonomous operations, effectively decoupling the system from central authorities to ensure functional continuity in environments characterized by intermittent connectivity.