Evidence map›Paper›PMID 35684450›Full record

ArticleMolecules (Basel, Switzerland)2022

Application of MOS Gas Sensors Coupled with Chemometrics Methods to Predict the Amount of Sugar and Carbohydrates in Potatoes.

Ali Khorramifar, Mansour Rasekh, Hamed Karami, James A Covington, Sayed M Derakhshani, Jose Ramos, Marek Gancarz

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. 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
–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

6 citing papers in PubMed.

  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

7 authors.

Ali KhorramifarDepartment of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.ORCID 0000-0002-9527-632X
Mansour RasekhDepartment of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.
Hamed KaramiDepartment of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.ORCID 0000-0002-0654-6149
James A CovingtonSchool of Engineering, University of Warwick, Coventry CV4 7AL, UK.
Sayed M DerakhshaniWageningen Food and Biobased Research, Bornse Weilanden 9, P.O. Box 17, 6700AA Wageningen, The Netherlands.ORCID 0000-0002-7867-2064
Jose RamosCollege of Computing and Engineering, Nova Southeastern University (NSU), 3301 College Avenue, Fort Lauderdale, FL 33314-7796, USA.
Marek GancarzInstitute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland.ORCID 0000-0003-4719-2954

Funding

The University of Mohaghegh Ardabili supported this work. 01
6 · The paper itself

Abstract

Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic nose. The signals obtained indicated the concentration of various chemical components. In addition to support vector machines (SVMs that were used for the classification of the samples, chemometric methods, such as the partial least squares regression (PLSR) method, the principal component regression (PCR) method, and the multiple linear regression (MLR) method, were used to create separate regression models for sugar and carbohydrates. The predictive power of the regression models was characterized by a coefficient of determination (R

Indexed as

Solanum tuberosumCarbohydratesChemometricsLeast-Squares AnalysisSugarsCarbohydratesSugarschemometricsclassificationelectronic nosemodeling

Identifiers

PMID35684450
PMCPMC9182414

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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.