| Literature DB >> 28928519 |
Francisco J Rodríguez-Pulido1, María Gil-Vicente1, Belén Gordillo1, Francisco J Heredia1, M Lourdes González-Miret1.
Abstract
This work includes the evaluation of 168 samples of raspberries 'Glen Lyon', representing whole maturation period, by colorimetric and near infrared imaging techniques, as well as the quantification of total phenols, total anthocyanins and antioxidant activity by chemical methods. Samples showed significant differences depending on the maturation stage using CIELAB colour parameters and total anthocyanins content. The application of partial least squares regression allowed predicting the chemical features from image analysis data, with coefficients of determination (R2) up to 0.75. The best prediction for total anthocyanins including colorimetric data was observed. The proposed methodology can be used as a reference method for assessing important quality attributes of raspberries. Moreover, it is useful, rapid and accurate automatic inspection method.Entities:
Keywords: Hyperspectral image analysis; Image analysis; Partial least squares regression; Phenolics; Raspberry ‘Glen Lyon’ (Rubus idaeus L)
Year: 2017 PMID: 28928519 PMCID: PMC5583109 DOI: 10.1007/s13197-017-2716-3
Source DB: PubMed Journal: J Food Sci Technol ISSN: 0022-1155 Impact factor: 2.701