NIR Spectroscopy for the Prediction of Moisture and Color in Roasted Coffee and the Study of Factors that Influence Brewing Time In Coffee Capsules.

This thesis focuses on the implementation of Near Infrared (NIR) calibration techniques for quality control of roasted coffee and the analysis of chemical variables influencing coffee brewing performance in capsules. The first aim of the research was the optimization of quality control during the roasting cycles by analyzing the color and moisture content of coffee. To obtain a calibration model for each feature, Partial Least Squares (PLS) regression with the use of spectral data preprocessed with first-derivative was chosen. The model was calibrated from the analysis of over 800 roasted coffee samples, characterized by different color and moisture levels. The tests were conducted at the Lavazza plant in Settimo Torinese, where this approach allowed for more efficient quality control on all roasting batches, reducing response times and increasing consistency in the final product. The second part of the research focused on studying the chemical characteristics of coffee and their influence on the coffee brewing performance in capsules. Numerous samples of different blends were collected, varying parameters such as moisture content and in which month of the year the product was prepared. The acquired NIR spectra were analyzed using Principal Component Analysis (PCA) to identify the main chemical variables affecting brewing time. The results revealed that moisture plays a key role for improving the brewing process: as moisture increases, time for coffee brewing tends to be shorter and more reproducible. Additionally, it was found that lipid content significantly impacts the extraction performance: samples with lower lipid content tend to yield faster extractions, suggesting that the presence of lipids slows down the flow of coffee during brewing. In conclusion, the findings of this research provide valuable insights for improving both quality control processes in coffee roasting and the chemical characteristics to monitor in order to optimize coffee extraction performance in capsules. NIR calibration, combined with advanced multivariate statistical analysis techniques such as PLS and PCA, proves a powerful tool for the coffee industry, with practical applications in both production processes and final product quality improvement.