Evidence map›Paper›PMID 39582642›Full record

ArticleFood chemistry: X2024

Replacing traditional coffee appraisers with inductively coupled plasma - mass spectrometry (ICP-MS): From manual sensory evaluation to scientific analysis.

Xiaowei Pan, Wenjing Yan, Xiaopeng Wu, Jianzhi Ye, Yaohui Liang, Guoyan Zhan, Hao Dong, Wenzhen Liao, Xingfen Yang, Qi He

Abstract read
In one paragraph

Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Xiaowei PanAgricultural Product Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guangdong Province 524001, China.
Wenjing YanSchool of Public Health/Food Safety and Health Research Center/Guangdong Provincial Key Laboratory of Tropical Disease Research /BSL-3 Laboratory, Southern Medical University, Guangzhou, Guangdong Province 510515, China.
Xiaopeng WuAnalysis and Testing Center, Chinese Academy of Tropical Agriculture Sciences, Haikou, Hainan Province 571101, China.
Jianzhi YeAgricultural Product Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guangdong Province 524001, China.
Yaohui LiangAgricultural Product Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guangdong Province 524001, China.
Guoyan ZhanAgricultural Product Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, Guangdong Province 524001, China.
Hao DongCollege of Light Industry and Food Sciences, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong Province 510225, China.
Wenzhen LiaoSchool of Public Health/Food Safety and Health Research Center/Guangdong Provincial Key Laboratory of Tropical Disease Research /BSL-3 Laboratory, Southern Medical University, Guangzhou, Guangdong Province 510515, China.
Xingfen YangSchool of Public Health/Food Safety and Health Research Center/Guangdong Provincial Key Laboratory of Tropical Disease Research /BSL-3 Laboratory, Southern Medical University, Guangzhou, Guangdong Province 510515, China.
Qi HeSchool of Public Health/Food Safety and Health Research Center/Guangdong Provincial Key Laboratory of Tropical Disease Research /BSL-3 Laboratory, Southern Medical University, Guangzhou, Guangdong Province 510515, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scientific development provides opportunities to replace many traditional manual methods to achieve more accurate results and higher efficiency. To scientifically ascertain the geographical origin of coffee, this study develops a method for the rapid determination of 16 inorganic elements in coffee using microwave digestion combined with the ICP-MS internal standard method. Principal component analysis (PCA), Fisher discriminant analysis (FDA), and Partial least squares discriminant analysis (PLS-DA) are employed to analyze 40 coffee samples from three production areas of Pu'er, Baoshan, and Wanning. The results show that the linear correlation coefficients of the 16 elements in this method are above 0.999, the detection limits are in the range of 0.0004-0.63 mg/kg, the RSD of the precision experiments are 4.5 %-13.5 %, the recovery rate of the peak experiment is 86.0 %-96.3 % with the RSD of 1.1 %-8.8 %, and the results of the standard substances are within the range of standard values. Using the discriminant analysis of inorganic elements in coffee (FDA and PLS-DA), coffee origin discrimination was realized, and six key elements (Al, Mn, Fe, Cu, Na, and Ba) are identified as effective discriminatory indexes. Accordingly, a coffee origin discrimination model is established, and the overall accuracy discrimination rate of the discrimination model are all more than 90.0 %, and FDA > PLS-DA. The findings indicated that the method has good accuracy and reliability, is suitable for analyzing and determining multiple elements in sample components as targets, and may have a positive impact on the development of related industries.

Indexed as

CoffeeFisher discriminant analysis (FDA)Geographic originPlasma mass spectrometry (ICP-MS)Principal component analysis

Identifiers

PMID39582642
PMCPMC11585831

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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.