Evidence map›Paper›PMID 38021261›Full record

ArticleCurrent research in food science2023

Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency.

Cristian Galaz Torres, Arianna Ricci, Giuseppina Paola Parpinello, Angelita Gambuti, Alessandra Rinaldi, Luigi Moio, Luca Rolle, Maria Alessandra Paissoni, Fulvio Mattivi, Daniele Perenzoni and 6 more

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In one paragraph

Article in Current research in food science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 42% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

16 authors at 5 institutions in 2 countries.

Cristian Galaz TorresDepartment of Agricultural and Food Sciences, University of Bologna, Italy.
Arianna RicciDepartment of Agricultural and Food Sciences, University of Bologna, Italy.
Giuseppina Paola ParpinelloDepartment of Agricultural and Food Sciences, University of Bologna, Italy.
Angelita GambutiDepartment of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.
Alessandra RinaldiDepartment of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.
Luigi MoioDepartment of Agricultural Sciences, Division of Vine and Wine Sciences, University of Napoli Federico II, 83100, Avellino, Italy.
Luca RolleDepartment of Agricultural, Forest and Food Sciences, University of Torino, 10095, Grugliasco, Italy.
Maria Alessandra PaissoniDepartment of Agricultural, Forest and Food Sciences, University of Torino, 10095, Grugliasco, Italy.
Fulvio MattiviMetabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.
Daniele PerenzoniMetabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.
Panagiotis ArapitsasMetabolomic Unit, Research and Innovation Centre, Fondazione Edmund Mach, 38010, San Michele all'Adige, Italy.
Matteo MarangonDepartment of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020, Legnaro, Italy.
Christine Mayr MarangonDepartment of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020, Legnaro, Italy.
Davide SlaghenaufiDepartment of Biotechnology, University of Verona, via della Pieve 70, San Pietro in Cariano, VR, Italy.
Maurizio UglianoDepartment of Biotechnology, University of Verona, via della Pieve 70, San Pietro in Cariano, VR, Italy.
Andrea VersariDepartment of Agricultural and Food Sciences, University of Bologna, Italy.
University of Bologna · ITFondazione Edmund Mach · ITUniversity of Padua · ITUniversity of Turin · ITUniversity of Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Astringency is an essential sensory attribute of red wine closely related to the saliva precipitation upon contact with the wine. In this study a data matrix of 52 physico-chemical parameters was used to predict the Saliva Precipitation Index (SPI) in 110 Italian mono-varietal red wines using partial least squares regression (PLSr) with variable selection by Variable Importance for Projection (VIP) and the significance of regression coefficients. The final PLSr model, evaluated using a test data set, had 3 components and yielded an R

Indexed as

Chemometric analysisGrape varietyPolyphenolic compoundsSensory analysisTannins

Identifiers

PMID38021261
PMCPMC10651451
OpenAlexW4388202345

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.