Literature DB >> 24444979

Determination of technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars during ripening by near infrared hyperspectral image: a preliminary approach.

Julio Nogales-Bueno1, José Miguel Hernández-Hierro1, Francisco José Rodríguez-Pulido1, Francisco José Heredia2.   

Abstract

Hyperspectral images of intact grapes during ripening were recorded using a near infrared hyperspectral imaging system (900-1700 nm). Spectral data have been correlated with grape skin total phenolic concentration, sugar concentration, titratable acidity and pH by modified partial least squares regression (MPLS) using a number of spectral pre-treatments and different sets of calibration. The obtained results (RSQ and SEP, respectively) for the global model of red and white grape samples were: 0.89 and 1.23 mg g(-1) of grape skin for total phenolic concentration, 0.99 and 1.37 °Brix for sugar concentration, 0.98 and 3.88 g L(-1) for titratable acidity and for pH 0.94 and 0.12. Moreover, separate calibration models for red and white grape samples were also developed. The obtained results present a good potential for a fast and reasonably inexpensive screening of these parameters in intact grapes and therefore, for a fast control of technological and phenolic maturity.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Chemometrics; Grapes; H; MPLS; MSC; Mahalanobis distance; NIRS; Near infrared hyperspectral imaging; PC; PCA; PLS; Phenolic maturity; RSQ; SEC; SECV; SEP; SNV; Technological maturity; coefficient of determination; modified partial least squares; multiplicative scatter correction; near infrared spectroscopy; partial least squares; principal component; principal component analysis; standard error of calibration; standard error of cross-validation; standard error of prediction; standard normal variate

Mesh:

Substances:

Year:  2013        PMID: 24444979     DOI: 10.1016/j.foodchem.2013.12.030

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  12 in total

1.  Measurement of ripening of raspberries (Rubus idaeus L) by near infrared and colorimetric imaging techniques.

Authors:  Francisco J Rodríguez-Pulido; María Gil-Vicente; Belén Gordillo; Francisco J Heredia; M Lourdes González-Miret
Journal:  J Food Sci Technol       Date:  2017-06-16       Impact factor: 2.701

2.  Selection and Optimization of an Innovative Polysaccharide-Based Carrier to Improve Anthocyanins Stability in Purple Corn Cob Extracts.

Authors:  Lucia Ferron; Chiara Milanese; Raffaella Colombo; Raffaele Pugliese; Adele Papetti
Journal:  Antioxidants (Basel)       Date:  2022-05-06

3.  Reduction of the Number of Samples for Cost-Effective Hyperspectral Grape Quality Predictive Models.

Authors:  Julio Nogales-Bueno; Francisco José Rodríguez-Pulido; Berta Baca-Bocanegra; Dolores Pérez-Marin; Francisco José Heredia; Ana Garrido-Varo; José Miguel Hernández-Hierro
Journal:  Foods       Date:  2021-01-23

4.  Comparison of Benchtop Fourier-Transform (FT) and Portable Grating Scanning Spectrometers for Determination of Total Soluble Solid Contents in Single Grape Berry (Vitis vinifera L.) and Calibration Transfer.

Authors:  Hui Xiao; Ke Sun; Ye Sun; Kangli Wei; Kang Tu; Leiqing Pan
Journal:  Sensors (Basel)       Date:  2017-11-22       Impact factor: 3.576

5.  Relationship between hyperspectral indices, agronomic parameters and phenolic composition of Vitis vinifera cv Tempranillo grapes.

Authors:  Ignacio García-Estévez; Natalia Quijada-Morín; Julián C Rivas-Gonzalo; José Martínez-Fernández; Nilda Sánchez; Carlos M Herrero-Jiménez; M Teresa Escribano-Bailón
Journal:  J Sci Food Agric       Date:  2017-06-02       Impact factor: 3.638

6.  Response of Mycorrhizal 'Touriga Nacional' Variety Grapevines to High Temperatures Measured by Calorespirometry and Near-Infrared Spectroscopy.

Authors:  Amaia Nogales; Hugo Ribeiro; Julio Nogales-Bueno; Lee D Hansen; Elsa F Gonçalves; João Lucas Coito; Ana Elisa Rato; Augusto Peixe; Wanda Viegas; Hélia Cardoso
Journal:  Plants (Basel)       Date:  2020-11-05

7.  Application of Hyperspectral Imaging and Deep Learning for Robust Prediction of Sugar and pH Levels in Wine Grape Berries.

Authors:  Véronique Gomes; Ana Mendes-Ferreira; Pedro Melo-Pinto
Journal:  Sensors (Basel)       Date:  2021-05-15       Impact factor: 3.576

8.  Monitoring the Phenolic Ripening of Red Grapes Using a Multisensor System Based on Metal-Oxide Nanoparticles.

Authors:  Celia Garcia-Hernandez; Cristina Medina-Plaza; Cristina Garcia-Cabezon; Yolanda Blanco; Jose A Fernandez-Escudero; Enrique Barajas-Tola; Miguel A Rodriguez-Perez; Fernando Martin-Pedrosa; Maria L Rodriguez-Mendez
Journal:  Front Chem       Date:  2018-04-24       Impact factor: 5.221

9.  Estimation of Total Phenols, Flavanols and Extractability of Phenolic Compounds in Grape Seeds Using Vibrational Spectroscopy and Chemometric Tools.

Authors:  Berta Baca-Bocanegra; Julio Nogales-Bueno; Francisco José Heredia; José Miguel Hernández-Hierro
Journal:  Sensors (Basel)       Date:  2018-07-26       Impact factor: 3.576

Review 10.  Applications and Developments on the Use of Vibrational Spectroscopy Imaging for the Analysis, Monitoring and Characterisation of Crops and Plants.

Authors:  Daniel Cozzolino; Jessica Roberts
Journal:  Molecules       Date:  2016-06-10       Impact factor: 4.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.