Headspace analysis of shelf life of postharvest arugula leaves using a SERS-active fiber

摘要: Abstract The increasing market demand for Ready-To-Eat fresh produce promotes the keen interest in developing a rapid, sensitive and reliable method determining shelf life of fresh-cut produce. In this study, we developed non-destructive headspace detection approach using gold nanoparticles (AuNPs) coated fibers coupled with surface-enhanced Raman spectroscopy (SERS), to detect volatile biochemical changes during postharvest storage arugula leaves. revealed significant spectral freshness decline, shifts around 500, 950 1030 cm−1. These were analyzed principal component analysis (PCA) classify establish prediction model remaining determination. Through analyzing reference standard organic compounds (VOCs), identified dimethyl disulfide (DMDS), methanethiol (MT) 1-propanethiol most likely account signature spectra at late period due growth spoilage bacteria. conclusion, based on SERS provides new strategy monitoring quality thus reducing food waste.