Evidence map›Paper›PMID 34355292›Full record

ArticleEnvironmental monitoring and assessment2021

A simple method to determine the sampling numbers in decision-making units with unknown variations of soil cadmium.

Yajie Huang, Jumei Li, Yibing Ma, Fangbai Li, Deli Chen

Abstract read
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In one paragraph

Article in Environmental monitoring and assessment, 2021. 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

5 authors.

Yajie HuangInstitute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Jumei LiInstitute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Yibing MaGuangdong-Hongkong-Macao Joint Laboratory of Collaborative Innovation for Environmental Quality, Macao Environmental Research Institute, Macau University of Science and Technology, Macao, 999078, China. ybma@must.edu.mo.ORCID http://orcid.org/0000-0002-9340-8181
Fangbai LiGuangdong Institute of Eco-Environmental and Soil Sciences, Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Guangzhou, 510650, China.
Deli ChenSchool of Agriculture and Food, The University of Melbourne, Melbourne, VIC, 3010, Australia.

Funding

Research on Migration/ Transformation and Safety Threshold of Heavy Metals in Farmland Systems 2016YFD0800400the science and technology development fund, macau sar 0159/2019/A3
6 · The paper itself

Abstract

Sampling number is one critical issue to achieve credible results when surveying soil contamination and making remediation decisions. Traditional methods based on a normal distribution for determining numbers of samples are not always optimal because most distributions of soil heavy metal concentrations followed a log-normal distribution. Moreover, the variation of soil heavy metal concentrations is a prerequisite for previous methods to determine sampling numbers. Unfortunately, the variation is often unknown before soil sampling. Therefore, a simple method under the log-normal distribution without relying on variation to determine quickly the sampling number (QSN) was developed for soil cadmium and compared with other methods based on classical statistics and Chebyshev inequality. Results showed that an equation as a function of sampling areas could be used to determine QSN (QSN = 18.44 × A

Indexed as

Metals, HeavySoil PollutantsCadmiumEnvironmental MonitoringSoilCadmiumMetals, HeavySoilSoil PollutantsDecision-making unitsLog-normal distributionSampling numbersSimple methodSoil cadmiumVariation

Identifiers

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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.