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2016•Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)Open access

Rapid and environmentally friendly wine analysis using Vis/NIR Spectroscopy and Support Vector Machine regression.

E. J. N. Marques, A. C. T. Biasoto, Sérgio Tonetto de Freitas, T. R. de Menezes, G. E. Pereira, R. de C. M. R. Nassur, E. P. de Medeiros

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Abstract

The aim of this study was to calibrate and validate models that can be used to determine quality parameters in red wine using Vis/NIR spectroscopy and the Least Squares Support Vector Machine (LS-SVM) regression.

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What this paper is about

The aim of this study was to calibrate and validate models that can be used to determine quality parameters in red wine using Vis/NIR spectroscopy and the Least Squares Support Vector Machine (LS-SVM) regression.

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Available abstract

The aim of this study was to calibrate and validate models that can be used to determine quality parameters in red wine using Vis/NIR spectroscopy and the Least Squares Support Vector Machine (LS-SVM) regression.

Key concepts: Support vector machine, Wine, Partial least squares regression, Least squares support vector machine, Regression analysis, Regression, Quality (philosophy), Spectroscopy

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Rapid and environmentally friendly wine analysis using Vis/NIR Spectroscopy and Support Vector Machine regression. — Research Paper | ScholarLens