Evidence map›Paper›PMID 36158454›Full record

ReviewFood and bioprocess technology2023

Phenolic Fraction from Peanut (

Guilherme Dallarmi Sorita, Fernanda Vitória Leimann, Sandra Regina Salvador Ferreira

Abstract readReview
In one paragraph

Review in Food and bioprocess technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Anti-DENV-2 Activity of Ethanolic Extracts fromPlants (Basel, Switzerland) · 2024
    Article
  8. Article
  9. 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

3 authors.

Guilherme Dallarmi SoritaChemical and Food Engineering Department, Federal University of Santa Catarina, CEP. 476, Florianópolis, SC 88040-900 Brazil.
Fernanda Vitória LeimannPost-Graduation Program of Food Technology (PPGTA), Federal University of Technology - Paraná - UTFPR, Campus Campo Mourão, via Rosalina Maria dos Santos, 1233, CEP 87301-899, Caixa Postal: 271, Campo Mourão, PR Brazil.
Sandra Regina Salvador FerreiraChemical and Food Engineering Department, Federal University of Santa Catarina, CEP. 476, Florianópolis, SC 88040-900 Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peanut skin is a by-product rich in bioactive compounds with high nutritional and pharmaceutical values. The phenolic fraction, rich in proanthocyanidins/procyanidins, is a relevant class of bioactive compounds, which has been increasingly applied as functional ingredients for food and pharmaceutical applications and is mostly recovered from peanut skins through low-pressure extraction methods. Therefore, the use of green high-pressure extractions is an interesting alternative to value this peanut by-product. This review addresses the benefits of the phenolic fraction recovered from peanut skin, with a focus on proanthocyanin/procyanidin compounds, and discusses the improvement of their activity, bioavailability, and protection, by methods such as encapsulation. Different applications for the proanthocyanidins, in the food and pharmaceutical industries, are also explored. Additionally, high-pressure green extraction methods, combined with micro/nanoencapsulation, using wall material derived from peanut industrial processing, may represent a promising biorefinery strategy to improve the bioavailability of proanthocyanidins recovered from underutilized peanut skins.

Indexed as

BioavailabilityEncapsulationGreen extractionsPeanut skinsProcyanidins

Identifiers

PMID36158454
PMCPMC9483447

What OpenQuestion holds

Textmetadata
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.