Evidence map›Paper›PMID 42746973›Full record

ArticleJournal of food science2026

Chemical Drivers of Sweetness, Sourness, and Astringency in Apple Juice Identified Using Support Vector Machine Regression.

Annachiara Berardinelli, Danny Cliceri, Isabella Endrizzi, Flavia Gasperi, Urska Vrhovsek, Eugenio Aprea

Abstract read
In one paragraph

Article in Journal of food science, 2026. 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
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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.

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

6 authors.

Annachiara BerardinelliDepartment of Industrial Engineering, University of Trento, Povo, Trento, Italy.
Danny CliceriCenter Agriculture Food Environment, University of Trento, San Michele all Adige, Trento, Italy.
Isabella EndrizziEdmund Mach Foundation, Research and Innovation Centre, San Michele all Adige, Trento, Italy.
Flavia GasperiCenter Agriculture Food Environment, University of Trento, San Michele all Adige, Trento, Italy.
Urska VrhovsekEdmund Mach Foundation, Research and Innovation Centre, San Michele all Adige, Trento, Italy.ORCID https://orcid.org/0000-0002-7921-3249
Eugenio ApreaCenter Agriculture Food Environment, University of Trento, San Michele all Adige, Trento, Italy.ORCID https://orcid.org/0000-0003-3648-0459

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of the main apple compositional parameters (sugars, organic acids, polyphenols, and volatile organic compounds) and their interactions on the perceived sensory attributes of Sweetness, Sourness, and Astringency was investigated in apple juice. Bivariate correlations and Support Vector Machine Regression (SVMR) analyses were used to examine the relationships between all the analyzed features and their relative importance in an interactive mode. By analyzing the contribution of the features to the SVMR models using Shapley values, we found that sweetness was strongly influenced by sucrose and by a few volatile organic compounds (VOCs), including acetate and butyl esters associated with fruity odors and flavors. For sourness, as expected, a strong contribution is given by malic acid, while VOCs associated with fruity odor contribute negatively. Regarding astringency, the major contributions were given by malic acid, procyanidins, sorbitol, and chlorogenic acid; the VOCs (few esters, hexanol, and (E)-2-hexenal) show a suppressing effect on astringency. In our investigation, SVMR confirms the role and the importance of the evidenced compositional parameters in driving the perception of the three analyzed sensory attributes in apple juices. PRACTICAL APPLICATIONS: This research could help provide apple breeders with new varieties with more predictable flavor, such as sweeter apples for juice or more tannic apples for cider. It could also help juice and cider producers select, blend, and process apples more consistently by using chemical measurements to estimate how a product may taste. The work may support better quality control, reduces variability, and strengthen product differentiation in markets where flavor consistency and clean-label formulations are increasingly important.

Indexed as

Fruit and Vegetable JuicesMalusSupport Vector MachineTasteFruitHumansMalatesOdorantsSucroseVolatile Organic Compoundsmalic acidSucroseVolatile Organic Compounds

Identifiers

PMID42746973
PMCPMC13579707

What OpenQuestion holds

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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.