Shelf life estimation and kinetic degradation modeling of chia seeds (Salvia hispanica) using principal component analysis based on NIR-hyperspectral imaging

A new methodology based on Near Infrared-hyperspectral imaging and Principal Components Analysis (PCA) was developed and accurately validated to model the degradations kinetics and to estimate the multivariate accelerated shelf life (MASLT) of chia seeds (Salvia hispanica). Chia seeds were stored 180 days at 25, 35 and 45 degrees C, observing fatty acid degradation and an increase in the acidity. PC1 scores and kinetic charts were built fitting the time-related PC1 scores versus time by a fused kinetic model (R-2 > 0.85). The spectra of chia seeds where acidity increased at 75% from initial value were used to calculate the cut-off value (-0.9853). The shelf life estimations were 1300, 798 and 90 days for chia seeds stored at 25, 35 and 45 degrees C, respectively. For the first time, a reliable methodology is proposed to validate that all samples were correctly predicted using PC1 scores.