Evidence map›Paper›PMID 41591159›Full record

ArticleToxins2025

Systematic Approach to Reducing Errors in Deoxynivalenol Quantification: Insights from Bulk Wheat Sampling and Sample Preparation.

Li Li, Bingjie Li, Jin Ye, Di Cai, Yu Wu, Peng Li, Bing Zhang, Jie Wang, Xiujuan Li, Yi Shao and 1 more

Abstract read
In one paragraph

Article in Toxins, 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
–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

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

11 authors.

Li LiAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.
Bingjie LiAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.
Jin YeAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.ORCID 0000-0001-9619-4943
Di CaiAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.
Yu WuAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.
Peng LiAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.
Bing ZhangAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.
Jie WangCollege of Food Science and Technology, Nanjing Agricultural University, 1 Weigang Road, Nanjing 210095, China.
Xiujuan LiGrain and Oil Product Quality Supervision and Inspection Station of Xinjiang Uygur Autonomous Region, Urumqi 830049, China.
Yi ShaoNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing 100021, China.
Songxue WangAcademy of National Food and Strategic Reserves Administration, NFSRA Key Laboratory of Grain and Oil Quality and Safety, Beijing 100037, China.ORCID 0000-0002-0555-5545

Funding

the Fundamental Research Funds for the Academy of National Food and Strategic Reserves Administration JY2406the National Natural Science Foundation of China Nos.31901806the Talent Project of National Food and Strategic Reserves Administration LJ2022201
6 · The paper itself

Abstract

Accurate quantification of Deoxynovalienol (DON) in wheat is critical for food safety, but current methods suffer from poor reproducibility due to inconsistent operational parameters across the sampling and analysis workflow. To address this issue, this study focused on truck-loaded bulk wheat and conducted a comprehensive analysis covering the entire process from sampling to laboratory testing. By examining parameters at each stage-test portion, laboratory sample, composite sample, and primary sample-and applying the Monte Carlo simple random sampling principle, the variability associated with the full-process parameters for DON detection in wheat was systematically analyzed. The errors introduced at each step were evaluated, leading to the development of a representative measurement procedure for DON in truck-loaded bulk wheat. The results indicate that for truck-loaded bulk wheat, sampling should be conducted using a random distribution method with no fewer than 11 sampling points, each providing a primary sample of at least 500 g. The composite sample should be homogenized three times using a cone-and-quartering divider before subsampling. The laboratory sample should weigh no less than 750 g and be ground to a particle size of 1 mm. After thorough mixing of the ground sample, 5 g should be accurately weighed for analysis. This measurement procedure introduces a total relative error of 12.9%. The proposed protocol for DON detection in truck-loaded wheat offers a practical approach that minimizes error contribution from each parameter while maintaining low economic and time costs, ensuring feasibility for field implementation.

Indexed as

Food ContaminationTrichothecenesTriticumReproducibility of ResultsdeoxynivalenolTrichothecenesdeoxynivalenolpotential errorssample preparationsamplingwheat

Identifiers

PMID41591159
PMCPMC12845785

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.