Physicochemical composition of persimmons: A non-destructive determination approach

Autor/innen

  • João Neto Institute for Agricultural and Veterinary Research, Av. da República, Quinta do Marquês, 2780-157 Oeiras, Portugal
  • Livia Carvalho Federal Institute of Paraná, Rua José de Alencar, 1080, 85200-000 Pitanga-PR, Brazil
  • Verônica Fregonez University of Idaho, Kimberly Research and Extension Center, 3806 N 3600 E, Kimberly, ID, USA, 83341
  • Gustavo Teixeira University of Idaho, Kimberly Research and Extension Center, 3806 N 3600 E, Kimberly, ID, USA, 83341

DOI:

https://doi.org/10.35219/foodtechnology.2026.1.02

Schlagwörter:

Diospyros kaki, VIS-NIR spectroscopy; chemometrics, postharvest

Abstract

Fruit from eight persimmon (Diospyros kaki) cultivars were evaluated for physicochemical quality at physiological maturity, and classification models were developed using near-infrared spectroscopy (Vis-NIR). Physical traits (mass, diameter, height), color (L*, a*, b*, chromaticity), firmness, soluble solids content, pH, titratable acidity, moisture, and dry matter were evaluated. Vis-NIR Spectra (310–1100 nm) were collected on a subset of five cultivars (n = 20 fruits), preprocessed with SNV, MSC, and Savitzky–Golay derivatives, and analyzed by PCA and PLS-DA; ANOVA supported comparisons. Pomelo showed higher fruit mass and diameter. Giombo and Taubaté had higher L* values and SSC and TA did not differ significantly between cultivars. Moisture content was highest and DM lowest in hybrid 82, while Giombo showed the lowest firmness. PCA explained 91–97% of spectral variance without clear separation across cultivars. PLS-DA achieved the best validation for Rama Forte (R²V = 0.75; RMSEV = 0.21) and Giombo (R²V = 0.68; RMSEV = 0.25). Vis-NIR spectroscopy successfully classified two persimmon cultivars, which can possibly be used for authentication of the product offered to consumers.

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Veröffentlicht

2026-08-26

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ORIGINAL ARTICLES

Zitationsvorschlag

„Physicochemical composition of persimmons: A non-destructive determination approach“. 2026. The Annals of the University Dunarea de Jos of Galati. Fascicle VI - Food Technology 50 (1): 28-44. https://doi.org/10.35219/foodtechnology.2026.1.02.