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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,*
Received: 10 May 2011; in revised form: 30 May 2011 / Accepted: 31 May 2011 / Published: 7 June 2011
(This article belongs to the Section Physical Sensors)
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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 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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.

AMA 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(6):6109-6124.

Chicago/Turabian Style

González-Caballero, Virginia; Pérez-Marín, Dolores; López, María-Isabel; Sánchez, María-Teresa. 2011. "Optimization of NIR Spectral Data Management for Quality Control of Grape Bunches during On-Vine Ripening." Sensors 11, no. 6: 6109-6124.



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