Assessment of integrated freshness index of different varieties of eggs using the visible and near-infrared spectroscopy

This study aimed to determine the integrated freshness index (IFI) of eggs using Vis-NIR spectroscopy and optimized support vector regression, which gave first insight into quality from biochemical essence changes. In this work, transmission spectra brown-shell pink-shell egg samples were analyzed between 500 nm 900 nm. Standard normal variables (SNV) used normalize spectral data, Shuffled Frog Leaping Algorithm (SFLA) Competitive Adaptive Reweighted Sampling (CARS) choose optimal wavelengths. The quantitative analysis model IFI was developed a regression (SVR) that Grid Search (GS), Genetic (GA), Particle Swarm Optimization (PSO). After conducting comparative analysis, it determined GA-SVR based on 63 wavelengths screened by SFLA best predicted with training set coefficient determination (Rc2) 0.900, root means square error (RMSEC) 0.005, prediction (Rp2) 0.816, mean (RMSEP) 0.012 relative (RPD) 2.077. results demonstrate can be simultaneously perform nondestructive detection two distinct variants, suggesting broader applicability enhanced reliability.