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Optimization of NIR Spectral Data Management for Quality Control of Grape Bunches during On-Vine Ripening
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
Department of Animal Production, University of Cordoba, Campus Rabanales, 14071 Cordoba, Spain
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; in revised form: 30 May 2011 / Accepted: 31 May 2011 / Published: 7 June 2011
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
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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.
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.
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.