Evidence map›Paper›PMID 39339592›Full record

ArticlePlants (Basel, Switzerland)2024

The Variability of Berry Parameters Could Be an Indicator of the Potential Quality of the Vineyard.

Zlavek Travanic-Fuentes, Gastón Gutiérrez-Gamboa, Yerko Moreno-Simunovic

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Zlavek Travanic-FuentesCentro Tecnológico de la Vid y el Vino, Facultad de Ciencias Agrarias, Universidad de Talca, 2 Norte 685, Casilla 747, Talca 3460000, Chile.
Gastón Gutiérrez-GamboaINIA Carillanca, Instituto de Investigaciones Agropecuarias, km 10 Camino Cajón-Vilcún s/n, Temuco Casilla Postal 929, Temuco 4880000, Chile.ORCID 0000-0003-3207-850X
Yerko Moreno-SimunovicCentro Tecnológico de la Vid y el Vino, Facultad de Ciencias Agrarias, Universidad de Talca, 2 Norte 685, Casilla 747, Talca 3460000, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBerry quality potential from a single vineyard is mainly defined based on some physicochemical parameters and subjective assessments. In this way, berry maturity variability would be a key factor affecting berry quality.

methodsThis trial aimed to study the effects of the maturity variability of berries harvested from plots of low (~37,080 kg ha

resultsThe berry heterogeneous maturity of soluble solids and berry weight in Cabernet Sauvignon was confirmed. The coefficient of variability (CV) of berry weight of high-quality plots was high at véraison and decreased as ripening progressed, reaching CV of 19.9% at harvest. Low-quality plots showed the lowest CV of berry weight in all the studied dates, whereas high-quality plots presented the lowest CV in soluble solids content of berries, reaching a 5.1% of variability at harvest. The physicochemical parameters showed that high-quality plots were characterized by high levels of soluble solids and phenolic maturity parameters, whereas samples from low-quality plots reached high berry weight and malic acid content. Berry differences among the physicochemical parameters determined wine quality, which allowed for plots to be classified by their potential quality at harvest.

conclusionsStudying maturity variability of soluble solids and berry weight will allow for sampling to be sectorized within a vineyard to reduce the extremes of maturity that would affect wine quality and productive goals of winemakers.

Indexed as

berry compositionCabernet Sauvignongrapeharvestripening heterogeneityvineyard managementviticulture

Identifiers

PMID39339592
PMCPMC11435239

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