Evidence map›Paper›PMID 34589622›Full record

ArticleHeliyon2021

Nondestructive estimation of three apple fruit properties at various ripening levels with optimal Vis-NIR spectral wavelength regression data.

Razieh Pourdarbani, Sajad Sabzi, Juan I Arribas

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
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 at 2 institutions in 2 countries.

Razieh PourdarbaniDepartment of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.
Sajad SabziDepartment of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.
Juan I ArribasDepartment of Electrical Engineering, University of Valladolid, 47011 Valladolid, Spain.
University of Mohaghegh Ardabili · IRUniversidad de Valladolid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nondestructive estimation of fruit properties during their ripening stages ensures the best value for producers and vendors. Among common quality measurement methods, spectroscopy is popular and enables physicochemical properties to be nondestructively estimated. The current study aims to nondestructively predict tissue firmness (kgf/cm), acidity (pH level) and starch content index (%) in apples (

Indexed as

AcidityAppleArtificial neural networkFirmnessFruitPhysicochemical propertiesStarch

Identifiers

PMID34589622
PMCPMC8461351
OpenAlexW3196738580

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.