Innovative lab-on-chip for the rapid detection of polyphenolic compounds in olives and their derivatives

Polyphenols are key quality markers in olives and extra virgin olive oil (EVOO), influencing antioxidant potential, sensory traits, and shelf-life. Measuring polyphenol levels in fruits provides insight into the physiological condition of the plant, environmental interactions, and the overall quality of the harvest. This study aimed to develop a portable Lab-On-Chip platform integrating Quartz Crystal Microbalance with Dissipation monitoring (QCM-D) for the rapid assessment of olive phenolic content at various ripening stages, minimizing the need for expensive and time-consuming laboratory procedures. Sixty olive samples were collected at different ripening stages (green to fully ripe) across three cultivars, and thirty corresponding oil samples were analyzed. Olive phenolics were quantified using both aQCM-D device and the Folin–Ciocalteu (FC) method, allowing for direct comparison. Sensor surfaces were functionalized with bio-derived polymers (thiolated chitosan and carboxymethylcellulose), enabling selective binding of polyphenols. Standard solutions of hydroxytyrosol and tyrosol were used for calibration. QCM-D responses (Δf and ΔD) showed a strong correlation (R² = 0.91) with total polyphenol content measured using the FC method (range: 250–1300 mg GAE/kg). The repeatability of the QCM-D method showed an RSD < 5%, with the analysis time under 10 minutes per sample. Compared to FC, the QCM-D method required only a non-toxic hydroalcoholic solvent (20% ethanol), offering faster turnaround and potential in situ application. The system successfully differentiated samples according to ripening stage, with early-harvest olives exhibiting the highest polyphenolic load and QCM-D signal. A multivariate predictive model (PLS regression) is being developed to correlate QCM-D fingerprints with the phenolic profiles and sensory parameters of the resulting oils. This integrated platform represents a valuable tool for quick and accurate phenolic analysis, enabling improved decision-making regarding harvest timing. Ultimately, it supports quality control practices that align with market trends and consumer preferences.