Abstract

A Fourier transform NIR (FT-NIR) method was developed combining chemometrics for prediction of organoleptic and phytochemical parameters of pomegranate arils using two different FT-NIR acquisition methods; namely, an integrating sphere (IS) and an emission head (EH) used over a spectral region 800–2500 nm. Several pre-processing methods were investigated. Pre-processing methods that yielded higher coefficient of determination (R2) and residual predictive deviation (RPD), lower root mean square error estimation (RMSEE) and root mean square error of prediction (RMSEP) values were used for model development. Model development using the EH gave the best prediction of total soluble solids (R2 = 87.55, RMSEP = 0.30%), pH (R2 = 85.18, RMSEP = 0.10), titratable acidity (R2 = 85.59, RMSEP = 0.10%), BrimA (R2 = 83.43, RMSEP = 0.43), aril hue (R2 = 88.59, RMSEP = 4.19), total phenolic concentration (R2 = 86.48, RMSEP = 0.11 g l−1), total anthocyanin concentration (R2 = 70.50, RMSEP = 0.13 g l−1) and vitamin C concentration (R2 = 84.86, RMSEP = 0.09 g l−1), while the IS provided the best results for TSS:TA (R2 = 82.20, RMSEP = 1.03), aril firmness (R2 = 68.40, RMSEP = 6.71 N), aril colour components (a* (R2 = 73.54, RMSEP = 1.67) and Chroma (R2 = 78.37, RMSEP = 2.31)). Good prediction was observed for both the models based on EH and IS data acquisition methods. However, better prediction performance was obtained with the model based on EH data acquisition method, resulting in accurate predictions of 8 quality parameters. This study demonstrated that FT-NIR and associated chemometric analysis can holistically evaluate the quality parameters of pomegranate arils.

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