Real-time and non-destructive control of the freshness and viability of live mussels through portable near-infrared spectroscopy

Abstract

This study introduces the application of a novel, rapid, and non-destructive method employing portable near-infrared (NIR) spectroscopy to assess the freshness and viability of live mussels throughout their shelf-life. NIR spectra ranging from 908 to 1676 nm were collected from 150 Mediterranean mussels (Mytilus galloprovincialis, L.) over a 10-day storage period. Simultaneously, measurements of weight loss, intravalvular liquid pH, and nonprotein nitrogen levels were taken. A predictive model was established by correlating the multivariate information derived from NIR spectral data with days of storage under refrigerated conditions using orthogonal partial least squares regression (OPLSR) analysis. While physical and chemical parameters (except for gradual weight loss due to water leakage) showed no distinct trends throughout storage, the fourth derivative-preprocessed NIR spectra enabled the construction of an OPLSR model that, following cross-validation, exhibited a correlation coefficient of 0.86 and, following external validation with new mussel samples, an average accuracy (root mean square error of prediction) of just 1.3 days. The predictive power of the model was primarily attributed to specific NIR wavelengths associated with key chemical features, including unsaturated fatty acids, nitrogen compounds, water content, glycerol, and ATP-related compounds that, collectively, constituted a distinctive fingerprint for forecasting mussel storage duration. The performance of the tool, along with its environmentally friendly, non-invasive, real-time, and cost-effective characteristics, align with industry control procedures and inspection needs, allowing effective freshness and viability assessment of live mussels across the food supply chain.