Journal
JOURNAL OF FOOD ENGINEERING
Volume 214, Issue -, Pages 29-39Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jfoodeng.2017.06.031
Keywords
Stone fruit; Internal quality; Ripeness; Monitoring; Hyperspectral image; Computer vision
Categories
Funding
- Institute Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) [RTA2015-00078-00-00]
- European FEDER funds
- INIA [43 (CPR2014-0082)]
- European Union FSE funds
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Visible near-infrared (450-1040 nm) hyperspectral reflectance imaging was studied in order to assess the internal physicochemical properties and sensory perception of 'Big Top' and 'Magique' nectarines (Prunus persica L Batsch var. nucipersica) (yellow and white-flesh cultivar, respectively) during ripening using the Ripening Index (RPI) and the Internal Quality Index (IQI). Hyperspectral images of the intact fruits were acquired during the ripeness under controlled conditions, and their physicochemical properties (flesh firmness, total soluble solids, titratable acidity and flesh colour) were analysed. IQI and RPI were used to relate the spectral information obtained from nectarines with the physicochemical properties and the sensory perception of their maturity using Partial Least Square (PLS) regression with proper variable selection. Optimal results were obtained with R-2 values higher than 0.87 for the two indices and the two cultivars. The ripeness of each fruit could be visualised by projecting the PLS models of the IQI on the pixels of the fruits in the images, showing great potential for further monitoring of the evolution of intact nectarine ripeness in industrial setups. (C) 2017 Elsevier Ltd. All rights reserved.
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