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Non-destructive method to classify walnut kernel freshness from volatile organic compound (VOC) emissions using gas chromatography-differential mobility spectrometry (GC-DMS) and machine learning analysis

Applied Food Research(2023)10.1016/j.afres.2023.100308Source: DataRank Database

Non-destructive method to classify walnut kernel freshness from volatile organic compound (VOC) emissions using gas chromatography-differential mobility spectrometry (GC-DMS) and machine learning analysis is a research paper published in Applied Food Research (2023). On theSindex it has a DataRank of 0.292. It has been cited 6 times.

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0.292DataRank · unranked

Scored on demand from live citation data

Open Access6 citations

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Identification of affected human metabolites and exogenous compounds in breath of vapers · University of California Office of the President

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (23 grants)Impact (FWCI 0.47)OA: goldTopics (16)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, PMC, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.292

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (7)

Eva Borras ORCID,Maneeshin Y. Rajapakse ORCID,Mitchell M. McCartney ORCID,Matthew Bustamante,Elizabeth Mitcham ORCID

Live enrichment

PubMed:38566846 PMC:PMC10984333 OpenAlex:https://openalex.org/W4383612861

National Institutes of Health

Grant: 1P30ES023513–01A1

National Center for Advancing Translational Sciences

Grant: 4U18TR003795–02

Tobacco-Related Disease Research Program

Grant: T31IR1614

National Center for Advancing Translational Sciences

Grant: UL1 TR001860

NCATS NIH HHS

Grant: U18 TR003795

California Walnut Board

Grant: A21–4128–001

California Walnut Board

Grant: A23–2583

NIH HHS

Grant: UG3 OD023365

BLRD VA

Grant: I01 BX004965

U.S. Department of Veterans Affairs

Grant: I01 BX004965–01A1

NIEHS NIH HHS

Grant: P30 ES023513

NCATS NIH HHS

Grant: U01 TR004083

National Institutes of Health

Grant: UG3-OD023365

National Center for Advancing Translational Sciences

Grant: 1U01TR004083–01

National Nuclear Security Administration

Grant: DE-NA0003525

California Walnut Board

Grant: A19–4599–001

Office of the Secretary of Defense

Grant: W911NF-17-3-0003

National Science Foundation

Sandia National Laboratories

US Department of Defense

Laboratory Directed Research and Development

U.S. Department of Energy

California Walnut Board

FWCI

0.47

Citation Percentile

0.5%

Citation Trend

2024

2025

2026

goldLicense: cc-by-nc-nd

journalhttps://doi.org/10.1016/j.afres.2023.100308

publisherhttps://doi.org/10.1016/j.afres.2023.100308

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38566846

repositoryhttps://escholarship.org/uc/item/3h39w8vg

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/10984333

Fields of Study

Advanced Chemical Sensor TechnologiesIsotope Analysis in EcologySpectroscopy and Chemometric Analyses

Keywords

ChemistryGas chromatography–mass spectrometryGas chromatographyMass spectrometryVolatile organic compoundChromatographyPartial least squares regressionMathematicsOrganic chemistryRancidityMachine Learningperoxide valueDifferential Mobility Spectrometry

Identification of affected human metabolites and exogenous compounds in breath of vapers

10.17920/g9cg3kUniversity of California Office of the President