Evidence map›Paper›PMID 34254180›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2021

Gas chromatography/mass spectrometry-based metabolite profiling of coffee beans obtained from different altitudes and origins with various postharvest processing.

Fitri Amalia, Pingkan Aditiawati, Yusianto, Sastia Prama Putri, Eiichiro Fukusaki

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Article in Metabolomics : Official journal of the Metabolomic Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

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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

13 citing papers in PubMed, 46 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Fitri AmaliaDepartment of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Pingkan AditiawatiSchool of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No.10, Lb. Siliwangi, Coblong, Kota Bandung, Jawa Barat, 40132, Indonesia.
YusiantoIndonesian Coffee and Cocoa Research Institute, Jl. PB. Sudirman 90, Jember, Indonesia.
Sastia Prama PutriDepartment of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. sastia_putri@bio.eng.osaka-u.ac.jp.ORCID 0000-0002-3045-4252
Eiichiro FukusakiDepartment of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Bandung Institute of Technology · IDThe University of Osaka · JPIndonesian Coffee and Cocoa Research Institute · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCoffee is a popular beverage because of its pleasant aroma and distinctive flavor. The flavor of coffee results from chemical transformations influenced by various intrinsic and extrinsic factors, including altitude, geographical origin, and postharvest processing. Despite is the importance of grading coffee quality, there is no report on the dominant factor that influences the metabolomic profile of green coffee beans and the correlated metabolites for each factor.

objectiveThis study investigated the total metabolite profile of coffees from different altitudes and coffees subjected to different postharvest processing.

methodArabica green coffee beans obtained from different geographical origins and different altitudes (400 and 800 m) and produced by different postharvest processes (dry, honey, and washed process) were used in this study. Coffee samples obtained from altitudes of 400-1600 m above sea level from various origins that were produced by the washed method were used for further study with regard to altitudes. Samples were subjected to gas chromatography/mass spectrometry (GC/MS) analysis and visualized using principal component analysis (PCA) and orthogonal partial least squares (OPLS) regression analysis.

resultsThe PCA results showed sample separation based on postharvest processing in PC1 and sample separation based on altitude in PC2. A clear separation between samples from different altitudes was observed if the samples were subjected to the same postharvest processing method, and the samples were of the same origin. Based on this result, OPLS analysis was conducted using coffee samples obtained from various altitudes with the same postharvest processing. An OPLS model using altitude as a response variable and 79 metabolites annotated from the GC/MS analysis as an explanatory variable was constructed with good R

conclusionPostharvest processing was found to be the dominant factor affecting coffee metabolite composition; this was followed by geographical origin and altitude. The metabolites glutamic acid and galactinol were associated with the washed and honey process, while glycine, lysine, sorbose, fructose, glyceric acid, and glycolic acid were associated with the dry process. Two metabolites with high variable influence on projection scores in the OPLS model for altitude were inositol and serotonin, which showed positive and negative correlations, respectively. This is the first study to report characteristic coffee metabolites obtained from different altitudes.

Indexed as

AltitudeCoffeeMetabolomicsFlavoring AgentsGas Chromatography-Mass SpectrometryOdorantsCoffeeFlavoring AgentsAltitudeCoffeeGas chromatography/mass spectrometryOrthogonal partial least squaresPostharvest process

Identifiers

PMID34254180
OpenAlexW3179624904

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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.