On the public citation graph

Machine learning-assisted authentication of Arabica coffee under Robusta adulteration based on metabolomic fingerprints

https://doi.org/10.2139/ssrn.6913082
0 signed · 31 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/mas.21779openalex-snapshot
Mass spectrometry in food authentication and origin traceability
inferredcites →https://doi.org/10.1007/s12161-013-9717-2openalex-snapshot
UV-Visible Spectroscopy and Multivariate Classification as a Screening Tool to Identify Adulteration of Culinary Spices with Sudan I and Blends of Sudan I + IV Dyes
inferredcites →https://doi.org/10.1016/j.aca.2006.12.057openalex-snapshot
Mixture resolution according to the percentage of robusta variety in order to detect adulteration in roasted coffee by near infrared spectroscopy
inferredcites →https://doi.org/10.1016/j.afres.2021.100035openalex-snapshot
Detection of coconut oil in ghee using ATR-FTIR and chemometrics
inferredcites →https://doi.org/10.1016/j.foodchem.2004.01.020openalex-snapshot
Trigonelline and sucrose diversity in wild Coffea species
inferredcites →https://doi.org/10.1016/j.foodchem.2016.08.028openalex-snapshot
Low-field 1H NMR spectroscopy for distinguishing between arabica and robusta ground roast coffees
inferredcites →https://doi.org/10.1016/j.foodchem.2017.10.022openalex-snapshot
Metabolomics fingerprint of coffee species determined by untargeted-profiling study using LC-HRMS
inferredcites →https://doi.org/10.1016/j.foodchem.2017.12.034openalex-snapshot
16-O-methylcafestol is present in ground roast Arabica coffees: Implications for authenticity testing
inferredcites →https://doi.org/10.1016/j.foodcont.2016.12.019openalex-snapshot
NMR quantification of 16-O-methylcafestol and kahweol in Coffea canephora var. robusta beans from different geographical origins
inferredcites →https://doi.org/10.1016/j.foodres.2011.05.028openalex-snapshot
Functional properties of coffee and coffee by-products
inferredcites →https://doi.org/10.1016/j.foodres.2017.08.006openalex-snapshot
Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice
inferredcites →https://doi.org/10.1016/j.foodres.2019.03.063openalex-snapshot
Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity – A review
inferredcites →https://doi.org/10.1016/j.lwt.2012.07.016openalex-snapshot
Discrimination between roasted coffee, roasted corn and coffee husks by Diffuse Reflectance Infrared Fourier Transform Spectroscopy
inferredcites →https://doi.org/10.1016/j.lwt.2013.04.008openalex-snapshot
Performance of diffuse reflectance infrared Fourier transform spectroscopy and chemometrics for detection of multiple adulterants in roasted and ground coffee
inferredcites →https://doi.org/10.1016/j.talanta.2017.08.009openalex-snapshot
Portable near infrared spectroscopy applied to quality control of Brazilian coffee
inferredcites →https://doi.org/10.1021/jf9700900openalex-snapshot
Levels of Cafestol, Kahweol, and Related Diterpenoids in Wild Species of the Coffee Plant Coffea
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1038/s41598-019-46113-yopenalex-snapshot
Discovery of food identity markers by metabolomics and machine learning technology
inferredcites →https://doi.org/10.1038/s41598-024-67459-yopenalex-snapshot
Application of untargeted liquid chromatography-mass spectrometry to routine analysis of food using three-dimensional bucketing and machine learning
inferredcites →https://doi.org/10.1038/s41598-025-18981-0openalex-snapshot
Explainable machine learning framework for predicting cobalt ion removal by natural hematite
inferredcites →https://doi.org/10.1081/fri-100108532openalex-snapshot
DITERPENES AND DITERPENE ESTERS IN COFFEE
inferredcites →https://doi.org/10.1093/bib/bbs034openalex-snapshot
Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?
inferredcites →https://doi.org/10.1214/15-aos1321openalex-snapshot
Consistency of random forests
inferredcites →https://doi.org/10.1590/s0103-50532012000700020openalex-snapshot
Discrimination of commercial roasted and ground coffees according to chemical composition
inferredcites →https://doi.org/10.1590/s1677-04202006000100014openalex-snapshot
The lipid fraction of the coffee bean
inferredcites →https://doi.org/10.3390/foods11193122openalex-snapshot
Assessing the Levels of Robusta and Arabica in Roasted Ground Coffee Using NIR Hyperspectral Imaging and FTIR Spectroscopy
inferredcites →https://doi.org/10.3390/foods14183195openalex-snapshot
Detection of Adulterants in Powdered Foods Using Near-Infrared Spectroscopy and Chemometrics: Recent Advances, Challenges, and Future Perspectives
inferredcites →https://doi.org/10.3390/foods9010047openalex-snapshot
Validation of a Quantitative Proton Nuclear Magnetic Resonance Spectroscopic Screening Method for Coffee Quality and Authenticity (NMR Coffee Screener)
inferredcites →https://doi.org/10.3390/metabo14110633openalex-snapshot
Detection of Sugar Syrups in Honey Using Untargeted Liquid Chromatography–Mass Spectrometry and Chemometrics
inferredcites →https://doi.org/10.3390/molecules25173972openalex-snapshot
Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity
inferredcites →https://doi.org/10.3390/molecules26247565openalex-snapshot
Application of the Metabolomics Approach in Food Authentication
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.