Quality control is mandatory in the food industry, and chemical sensors play a crucial role in this field.

Coffee is one of the most consumed and marketed food products in the world, and its quality characteristics are therefore of fundamental importance for the industry in this sector.

The aim of a recent study, carried out by a group of Italian researchers (Grasso et al., 2025), was to evaluate the ability of an intelligent electrochemical sensor to distinguish between different beverages prepared with coffee beans having different moisture content (0, 2 and > 4%) and ground to three particle sizes (fine, medium and coarse).

These parameters, in fact, reflect real scenarios in which this product is processed and its quality is affected.

A specific experimental configuration was designed for the tests, while the data was analysed using machine learning techniques.

The results obtained from principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) show the sensor’s ability to distinguish between samples of different quality, with a correct classification rate of 86.6%.