Evidence map›Paper›PMID 37297437›Full record

ArticleFoods (Basel, Switzerland)2023

Chemical Characterization, Sensory Definition and Prediction Model of the Cider Dryness from New York State Apples.

Monica Picchi, Paola Domizio, Matt Wilson, Josè Santos, Frederick Orrin, Bruno Zanoni, Valentina Canuti

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Monica PicchiDAGRI-Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, Italy.
Paola DomizioDAGRI-Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, Italy.ORCID 0000-0003-4011-4929
Matt WilsonEnartis, 7795 Bell Road, Windsor, CA 95492, USA.
Josè SantosEnartis, 7795 Bell Road, Windsor, CA 95492, USA.
Frederick OrrinEnartis, 7795 Bell Road, Windsor, CA 95492, USA.
Bruno ZanoniDAGRI-Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, Italy.ORCID 0000-0002-9020-6883
Valentina CanutiDAGRI-Department of Agriculture, Food, Environment and Forestry, University of Florence, Via Donizetti, 6, 50144 Firenze, Italy.ORCID 0000-0002-8345-8257

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

apple ciderchemical characterizationdrynessmultivariate analysisPLS modelsensory perception

Identifiers

PMID37297437
PMCPMC10252411

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.