Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples
Cider is a fermented drink obtained from apple juice. As a function of the used apple cultivar, cider can be classified in four different categories (dry, semi-dry, semi-sweet, sweet), distinguished by the attribute of “dryness,” which reflects the sweetness and softness perceived. The dryness level...
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MDPI AG
2023-05-01
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author | Monica Picchi Paola Domizio Matt Wilson Josè Santos Frederick Orrin Bruno Zanoni Valentina Canuti |
author_facet | Monica Picchi Paola Domizio Matt Wilson Josè Santos Frederick Orrin Bruno Zanoni Valentina Canuti |
author_sort | Monica Picchi |
collection | DOAJ |
description | Cider is a fermented drink obtained from apple juice. As a function of the used apple cultivar, cider can be classified in four different categories (dry, semi-dry, semi-sweet, sweet), distinguished by the attribute of “dryness,” which reflects the sweetness and softness perceived. The dryness level is defined by scales (IRF, NYCA scales) based on the residual sugar, titratable acidity and tannin contents. Despite some adjustments, these scales show limitations in the prediction of actual perceived dryness, as they cannot consider the complicated interrelation between combined chemical compounds and sensory perception. After defining the perceived sensory dryness and its sensory description by using the quantitative descriptive analysis (QDA) method, a multivariate approach (PLS) was applied to define a predictive model for the dryness and to identify the chemical compounds with which it was correlated. Three models were developed, based on three different sets of chemical parameters, to provide a method that is easily applicable in the ordinary production process of cider. The comparison between the predicted rating and the relative scales scores showed that the models were able to predict the dryness rating in a more effective way. The multivariate approach was found to be the most suitable to study the relation between chemical and sensory data. |
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language | English |
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spelling | doaj.art-c0dac9bfd61d42ef90a35f54a749a6292023-11-18T07:51:31ZengMDPI AGFoods2304-81582023-05-011211219110.3390/foods12112191Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State ApplesMonica Picchi0Paola Domizio1Matt Wilson2Josè Santos3Frederick Orrin4Bruno Zanoni5Valentina Canuti6DAGRI—Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, ItalyDAGRI—Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, ItalyEnartis, 7795 Bell Road, Windsor, CA 95492, USAEnartis, 7795 Bell Road, Windsor, CA 95492, USAEnartis, 7795 Bell Road, Windsor, CA 95492, USADAGRI—Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, ItalyDAGRI—Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, ItalyCider is a fermented drink obtained from apple juice. As a function of the used apple cultivar, cider can be classified in four different categories (dry, semi-dry, semi-sweet, sweet), distinguished by the attribute of “dryness,” which reflects the sweetness and softness perceived. The dryness level is defined by scales (IRF, NYCA scales) based on the residual sugar, titratable acidity and tannin contents. Despite some adjustments, these scales show limitations in the prediction of actual perceived dryness, as they cannot consider the complicated interrelation between combined chemical compounds and sensory perception. After defining the perceived sensory dryness and its sensory description by using the quantitative descriptive analysis (QDA) method, a multivariate approach (PLS) was applied to define a predictive model for the dryness and to identify the chemical compounds with which it was correlated. Three models were developed, based on three different sets of chemical parameters, to provide a method that is easily applicable in the ordinary production process of cider. The comparison between the predicted rating and the relative scales scores showed that the models were able to predict the dryness rating in a more effective way. The multivariate approach was found to be the most suitable to study the relation between chemical and sensory data.https://www.mdpi.com/2304-8158/12/11/2191apple ciderdrynesssensory perceptionchemical characterizationPLS modelmultivariate analysis |
spellingShingle | Monica Picchi Paola Domizio Matt Wilson Josè Santos Frederick Orrin Bruno Zanoni Valentina Canuti Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples Foods apple cider dryness sensory perception chemical characterization PLS model multivariate analysis |
title | Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples |
title_full | Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples |
title_fullStr | Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples |
title_full_unstemmed | Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples |
title_short | Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples |
title_sort | chemical characterization sensory definition and prediction model of the cider dryness from new york state apples |
topic | apple cider dryness sensory perception chemical characterization PLS model multivariate analysis |
url | https://www.mdpi.com/2304-8158/12/11/2191 |
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