Non-invasive and rapid pH monitoring for meat quality assessment using a low-cost portable hyperspectral scanner

摘要

It has been demonstrated that optical spectroscopy is a powerful tool for the quantitative monitoring of the main chemical components in food. However, portable spectrometer for on-site food quality assessment has rarely been reported. Here, a low-cost and portable hyperspectral scanner is developed. Utilizing this hyperspectral scanner by handheld push-broom scanning, reflectance spectra of meat samples can be obtained non-invasively and rapidly. Support vector regression (SVR) model is used to predict the pH value. The prediction accuracy rate of the model is close to 90%, and the coefficient of determination is about 0.93, which shows the feasibility of this system in on-site monitoring pH of meat.