Evidence map›Paper›PMID 40067526›Full record

ArticleEnvironmental monitoring and assessment2025

Ecological risk evaluation of heavy metals based on hyperspectral: a case study of rice paddy soil in Xiangtan County, China.

Undrakhtsetseg Tsogtbaatar, Lili Huo, Le Jiao, Sainbayar Dalantai, Yi An, Bayartungalag Batsaikhan, Unurnyam Jugnee, Boldbaatar Natsagdorj, Tsogtjargal Batsaikhan, Baasantsog Munkhchuluun

Abstract read
In one paragraph

Article in Environmental monitoring and assessment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Undrakhtsetseg Tsogtbaatar *Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia.
Lili Huo *Ministry of Agriculture and Rural Affairs, Agro-Environmental Protection Institute, Nankai District, No. 31, Fukang Road, Tianjin, 300191, People's Republic of China.
Le Jiao *Ministry of Agriculture and Rural Affairs, Agro-Environmental Protection Institute, Nankai District, No. 31, Fukang Road, Tianjin, 300191, People's Republic of China. jiaole@caas.cn.
Sainbayar DalantaiInstitute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia.
Yi AnMinistry of Agriculture and Rural Affairs, Agro-Environmental Protection Institute, Nankai District, No. 31, Fukang Road, Tianjin, 300191, People's Republic of China. simon8601@126.com.
Bayartungalag BatsaikhanInstitute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia. bayartungalag_b@mas.ac.mn.
Unurnyam JugneeInstitute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia.
Boldbaatar NatsagdorjInstitute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia.
Tsogtjargal BatsaikhanInstitute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia.
Baasantsog MunkhchuluunInstitute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, 15170, Mongolia.

Funding

Central Public-interest Scientific Institution Basal Research Fund 1102021600110042413Central Public-interest Scientific Institution Basal Research Fund JBKYYWF-hll-2022National Natural Science Foundation of China 42307507
6 · The paper itself

Abstract

Heavy metal pollution in agricultural soils pose significant risks to food safety and human health, necessitating effective monitoring and assessment techniques. Recognizing characteristic spectral features is essential for accurately assessing the ecological risks associated with heavy metal pollution. To explore the potential of utilizing the hyperspectrum to evaluate ecologial risks of heavy metals pollution in paddy soil, the study investigated ecological risks and spectral characteristics (350 ~ 2500 nm) of heavy metals (Cd, Pb, Cr, Cu) in rice paddy soil in Xiangtan County, Hunan Province, China. Potential ecological risk index (RI) was employed to evaluate pollution level, and derivative transformations (first derivative R' and second derivative R″) were applied to eliminate the hyperspectral noise. Results identified Cd as the primary pollutant in the paddy soil of Xiangtan County, followed by Pb, Cu, and Cr. Serious heavy metal pollution concentrated in riverine and cropland areas. After applying spectral transformations, the correlation between spectral reflectance and ecological risks significantly improved. The R″ transformation demonstrated the highest correlations for Cd (r = 0.95) at 2046 nm in high ecological risk category, while the R' transformation exhibited the strongest negative correlation for Cd (r =  - 0.94) at 2059 nm. This study highlights the potential of hyperspectral analysis as an effective tool for estimating ecological risks posed by heavy metal pollution in rice paddy soils. The findings provide valuable insights for improving monitoring practices and informing risk management strategies in agricultural environments.

Indexed as

Environmental MonitoringMetals, HeavySoil PollutantsAgricultureChinaOryzaRisk AssessmentSoilMetals, HeavySoilSoil PollutantsEcological riskHeavy metalHunan ProvinceHyperspectral inversionRice paddy soil

Identifiers

PMID40067526
PMCPMC11897112

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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.