Next Article in Journal
Simultaneous Second Harmonic Generation of Multiple Wavelength Laser Outputs for Medical Sensing
Previous Article in Journal
An Air-Ground Wireless Sensor Network for Crop Monitoring
Sensors 2011, 11(6), 6109-6124; doi:10.3390/s110606109
Article

Optimization of NIR Spectral Data Management for Quality Control of Grape Bunches during On-Vine Ripening

1
,
2,* , 1
 and
3,*
1 Centro de Investigación y Formación Agraria de ‘‘Cabra-Priego”, Instituto de Investigación y Formación Agraria y Pesquera (IFAPA), Consejería de Agricultura y Pesca, Junta de Andalucía, Cabra, Spain 2 Department of Animal Production, University of Cordoba, Campus Rabanales, 14071 Cordoba, Spain 3 Department of Bromatology and Food Technology, University of Cordoba, Campus Rabanales, 14071 Cordoba, Spain
* Authors to whom correspondence should be addressed.
Received: 10 May 2011 / Revised: 30 May 2011 / Accepted: 31 May 2011 / Published: 7 June 2011
(This article belongs to the Section Chemical Sensors)
View Full-Text   |   Download PDF [192 KB, uploaded 21 June 2014]   |  

Abstract

NIR spectroscopy was used as a non-destructive technique for the assessment of chemical changes in the main internal quality properties of wine grapes (Vitis vinifera L.) during on-vine ripening and at harvest. A total of 363 samples from 25 white and red grape varieties were used to construct quality-prediction models based on reference data and on NIR spectral data obtained using a commercially-available diode-array spectrophotometer (380–1,700 nm). The feasibility of testing bunches of intact grapes was investigated and compared with the more traditional must-based method. Two regression approaches (MPLS and LOCAL algorithms) were tested for the quantification of changes in soluble solid content (SSC), reducing sugar content, pH-value, titratable acidity, tartaric acid, malic acid and potassium content. Cross-validation results indicated that NIRS technology provided excellent precision for sugar-related parameters (r2 = 0.94 for SSC and reducing sugar content) and good precision for acidity-related parameters (r2 ranging between 0.73 and 0.87) for the bunch-analysis mode assayed using MPLS regression. At validation level, comparison of LOCAL and MPLS algorithms showed that the non-linear strategy improved the predictive capacity of the models for all study parameters, with particularly good results for acidity-related parameters and potassium content.
Keywords: NIR spectroscopy; quality parameters; on-vine; bunch analysis NIR spectroscopy; quality parameters; on-vine; bunch analysis
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
SciFeed

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
RIS
MDPI and ACS Style

González-Caballero, V.; Pérez-Marín, D.; López, M.-I.; Sánchez, M.-T. Optimization of NIR Spectral Data Management for Quality Control of Grape Bunches during On-Vine Ripening. Sensors 2011, 11, 6109-6124.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert