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Carbon dioxide treatment to reduce soluble tannins and astringency in persimmons is sometimes ineffective. Near-infrared spectroscopy was used to develop a predictive model for soluble tannin content and persimmon classification. A model using averaged spectra collected in the interactance mode showed better performance (correlation coefficient of prediction, r p = 0.95 and root mean square error of prediction, RMSEP = 0.17% w/w) than that from the transmittance mode (r p = 0.94 and RMSEP = 0.19% w/w). Models generated using spectra from the stem-end or middle plane flesh and whole fruit were comparable. Classification accuracy of 97.1% was achieved using stem-end flesh spectra. Therefore, near-infrared spectroscopy is a rapid and non-destructive technique with potential applications in the estimation of persimmon tannin content.

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