Evidence map›Paper›PMID 41345768›Full record

ArticleScientific reports2025

Validation and comparison of GC-MS, FT-MIR, and FT-NIR techniques for rapid bromoform quantification in Asparagopsis taxiformis extracts.

Weihao Meng, Ming Zhao, Jiani Luo, Colm P O'Donnell, Raquel Cama-Moncunill, Hongnan Sun, Taihua Mu, Marco Garcia-Vaquero

Abstract readComparative StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Weihao MengSchool of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland.
Ming ZhaoSchool of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
Jiani LuoSchool of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
Colm P O'DonnellSchool of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
Raquel Cama-MoncunillSchool of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland.
Hongnan SunLaboratory of Food Chemistry and Nutrition Science, Institute of Food Science and Technology, Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, No.2 Yuan Ming Yuan West Road, Haidian District, P.O. Box 5109, Beijing, 100193, P. R. China. sunhongnan@caas.cn.
Taihua MuLaboratory of Food Chemistry and Nutrition Science, Institute of Food Science and Technology, Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, No.2 Yuan Ming Yuan West Road, Haidian District, P.O. Box 5109, Beijing, 100193, P. R. China. mutaihua@126.com.
Marco Garcia-VaqueroSchool of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland. marco.garciavaquero@ucd.ie.

Funding

Sustainable Blue Economy Partnership (SBEP) BIOVAL
6 · The paper itself

Abstract

Bromoform-rich extracts of Asparagopsis taxiformis represent a promising sustainable strategy for mitigating methane emissions in ruminants. Accurate quantification of bromoform is essential to ensure both efficacy and safety. Although gas chromatography-mass spectrometry (GC-MS) offers high accuracy, it is time-consuming, resource-intensive, and requires significant chemical reagents. This study pioneers the use of Fourier-transform near-infrared (FT-NIR), Fourier-transform mid-infrared (FT-MIR), and their data fusion (FT-MIR-NIR) combined with a recursive weighted partial least squares (rPLS) variable selection algorithm for rapid, non-destructive quantification of bromoform in seaweed extracts, validated against GC-MS. The partial least squares regression (PLSR) models employing rPLS based on FT-MIR spectra (R

Indexed as

Gas Chromatography-Mass SpectrometryPlant ExtractsSeaweedAnimalsLeast-Squares AnalysisRhodophytaSpectroscopy, Fourier Transform InfraredSpectroscopy, Near-InfraredPlant ExtractsAnti-methanogenicBromoformGreen chemistryProcess analytical technology

Identifiers

PMID41345768
PMCPMC12796197

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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.