Research on white and red wine blending in the production of rosé wines by means of the partial least squares method | Zendy

GarcíaJares Carmen | Zendy; Médina Bernard | Zendy

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Research on white and red wine blending in the production of rosé wines by means of the partial least squares method

Author(s) -

GarcíaJares Carmen,

Médina Bernard

Publication year - 1993

Publication title -

journal of the science of food and agriculture

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.782

H-Index - 142

eISSN - 1097-0010

pISSN - 0022-5142

DOI - 10.1002/jsfa.2740630313

Subject(s) - wine , white wine , partial least squares regression , principal component analysis , mathematics , food science , principal component regression , white (mutation) , chemistry , statistics , set (abstract data type) , chromatography , biological system , computer science , biology , biochemistry , programming language , gene

The difficult problem of recognizing wine blends in rosé wines is assessed using a powerful statistical method called partial least squares. Genuine rosé wines are first detected using a 280 nm/320 nm spectrophometric ratio. Blends of white and red wine are used as a calibration set and for an evaluation set of known composition. The proposed method evaluates the respective percentage of red and white wine in a blend and the error associated with the prediction. A comparison is made with principal component regression.

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