Vibrational spectroscopic techniques have gained significant attention in recent years for their potential in the rapid and efficient analysis of virgin olive oils, offering a distinct advantage over traditional methods. These techniques are particularly valuable for detecting and quantifying bio-active compounds that contribute to the nutritional and health benefits of virgin olive oils. This comprehensive review explores the latest advancements in vibrational spectroscopic techniques applied to virgin olive oils, focusing on the detection and measurement of key bio-active compounds such as unsaturated fatty acids, phenolic compounds, and other antioxidant compounds. The review highlights the improvements in vibrational spectroscopy, data processing, and chemometric techniques that have significantly enhanced the ability to accurately identify these compounds compared to conventional analytical methods. Additionally, it addresses current challenges, including the need for standardized methodologies and the potential for integrating vibrational spectroscopy with other analytical techniques to improve accuracy and reliability. Finally, findings over the last two decades, in which vibrational spectroscopy techniques were effectively used for the detailed characterization of bio-active compounds in virgin olive oils, are discussed.

In this work, the feasibility of simulating the thermal inactivation of Brochothrix thermosphacta in beef during heating processing based on hyperspectral imaging (HSI) in the wavelength range of 400–1000 nm was investigated. The Weibull and modified Gompertz kinetic models for the thermal inactivation of B. thermosphacta in beef heated in the range 40–60 °C were developed based on the full wavelength, featured spectral variables, and their principal component scores of HSI information, respectively. Notably, the specific wavebands at 412 nm and 735 nm showed a strong correlation with the surviving B. thermosphacta population during the beef heating process. The partial least squares regression models had a satisfactory ability in quantifying B. thermosphacta in beef, with an R_v² and RMSE of 0.826 and 0.341 log CFU/g, respectively. Furthermore, the Weibull model coupled with the HSI at 735 nm was suitable for kinetic modeling of the thermal inactivation of B. thermosphacta in beef, with an R² value of 0.937. Consequently, this work suggests the potential of the HSI technique for quantifying and monitoring microbes in meat during heating and can be applied for the thermal inactivation kinetic modeling of microorganisms.