Evidence map›Paper›PMID 30502133›Full record

ArticleFood chemistry2019

Spatial changes in leaf biochemical profile of two tea cultivars following cold storage under two different vapour pressure deficit (VPD) conditions.

Emma R Collings, M Carmen Alamar, Sally Redfern, Katherine Cools, Leon A Terry

Open access · hybridAbstract read
In one paragraph

Article in Food chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
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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

5 authors at 2 institutions in 1 country.

Emma R CollingsPlant Science Laboratory, Cranfield University, Bedfordshire MK43 0AL, UK.
M Carmen AlamarPlant Science Laboratory, Cranfield University, Bedfordshire MK43 0AL, UK.
Sally RedfernUnilever R&D Colworth, Sharnbrook, Bedfordshire MK44 1LQ, UK.
Katherine CoolsPlant Science Laboratory, Cranfield University, Bedfordshire MK43 0AL, UK.
Leon A TerryPlant Science Laboratory, Cranfield University, Bedfordshire MK43 0AL, UK. Electronic address: l.a.terry@cranfield.ac.uk.
Cranfield University · GBUnilever (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Withering is considered a crucial stage of black tea processing. In this study, tea shoots from two cultivars (cvs. Yabukita and Clone 2) were stored at 5 °C, in either a low or high vapour pressure deficit (VPD) environment, to determine the impact of different withering rates on physiology (viz. respiration rate [RR], colour and moisture loss) and biochemical profile (viz. individual catechins, methylxanthines) of tea shoots (Camellia sinensis). Low VPD and high VPD conditions during withering increased caffeine levels in Clone 2 and Yabukita, respectively (p < 0.05). Caffeine levels steadily increased over time in both cultivars (p < 0.05), coinciding with a rapid decline in theobromine (TB). Furthermore, stems contained lower epigallocatechin gallate (EGCG) and caffeine (ca. 75 and 56%, respectively) compared to bud and larger leaf (LL) (p < 0.05). Overall, the results of this study highlight factors such as mechanical harvesting, and hard or soft withering, which could affect final tea beverage quality.

Indexed as

Cold TemperatureVapor PressureCaffeineCamellia sinensisCatechinFood StoragePlant LeavesTheobromineCaffeineCatechinepigallocatechin gallateTheobromineCaffeineCatechinsColourMetabolic rateMethylxanthinesTheobromine

Identifiers

PMID30502133
PMCPMC6283014
OpenAlexW2898045579

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.