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A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis
BACKGROUND: Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765894/ https://www.ncbi.nlm.nih.gov/pubmed/23987502 http://dx.doi.org/10.1186/1752-153X-7-145 |
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author | Nica, Dragos V Bordean, Despina Maria Pet, Ioan Pet, Elena Alda, Simion Gergen, Iosif |
author_facet | Nica, Dragos V Bordean, Despina Maria Pet, Ioan Pet, Elena Alda, Simion Gergen, Iosif |
author_sort | Nica, Dragos V |
collection | PubMed |
description | BACKGROUND: Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic levels followed by their statistical analysis using exploratory multivariate methods can provide meaningful information on the status of environmental quality. In this context, the present paper proposes a novel chemometric approach to standard statistical methods by combining the Block clustering with Partial least square (PLS) analysis to investigate the accumulation patterns of metals in anthropized terrestrial ecosystems. The present study focused on copper, zinc, manganese, iron, cobalt, cadmium, nickel, and lead transfer along a soil-plant-snai food chain, and the hepatopancreas of the Roman snail (Helix pomatia) was used as a biological end-point of metal accumulation. RESULTS: Block clustering deliniates between the areas exposed to industrial and vehicular contamination. The toxic metals have similar distributions in the nettle leaves and snail hepatopancreas. PLS analysis showed that (1) zinc and copper concentrations at the lower trophic levels are the most important latent factors that contribute to metal accumulation in land snails; (2) cadmium and lead are the main determinants of pollution pattern in areas exposed to industrial contamination; (3) at the sites located near roads lead is the most threatfull metal for terrestrial ecosystems. CONCLUSION: There were three major benefits by applying block clustering with PLS for processing the obtained data: firstly, it helped in grouping sites depending on the type of contamination. Secondly, it was valuable for identifying the latent factors that contribute the most to metal accumulation in land snails. Finally, it optimized the number and type of data that are best for monitoring the status of metallic contamination in terrestrial ecosystems exposed to different kinds of anthropic polution. |
format | Online Article Text |
id | pubmed-3765894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37658942013-09-12 A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis Nica, Dragos V Bordean, Despina Maria Pet, Ioan Pet, Elena Alda, Simion Gergen, Iosif Chem Cent J Research Article BACKGROUND: Given the serious threats posed to terrestrial ecosystems by industrial contamination, environmental monitoring is a standard procedure used for assessing the current status of an environment or trends in environmental parameters. Measurement of metal concentrations at different trophic levels followed by their statistical analysis using exploratory multivariate methods can provide meaningful information on the status of environmental quality. In this context, the present paper proposes a novel chemometric approach to standard statistical methods by combining the Block clustering with Partial least square (PLS) analysis to investigate the accumulation patterns of metals in anthropized terrestrial ecosystems. The present study focused on copper, zinc, manganese, iron, cobalt, cadmium, nickel, and lead transfer along a soil-plant-snai food chain, and the hepatopancreas of the Roman snail (Helix pomatia) was used as a biological end-point of metal accumulation. RESULTS: Block clustering deliniates between the areas exposed to industrial and vehicular contamination. The toxic metals have similar distributions in the nettle leaves and snail hepatopancreas. PLS analysis showed that (1) zinc and copper concentrations at the lower trophic levels are the most important latent factors that contribute to metal accumulation in land snails; (2) cadmium and lead are the main determinants of pollution pattern in areas exposed to industrial contamination; (3) at the sites located near roads lead is the most threatfull metal for terrestrial ecosystems. CONCLUSION: There were three major benefits by applying block clustering with PLS for processing the obtained data: firstly, it helped in grouping sites depending on the type of contamination. Secondly, it was valuable for identifying the latent factors that contribute the most to metal accumulation in land snails. Finally, it optimized the number and type of data that are best for monitoring the status of metallic contamination in terrestrial ecosystems exposed to different kinds of anthropic polution. BioMed Central 2013-08-30 /pmc/articles/PMC3765894/ /pubmed/23987502 http://dx.doi.org/10.1186/1752-153X-7-145 Text en Copyright © 2013 Nica et al.; licensee Chemistry Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Nica, Dragos V Bordean, Despina Maria Pet, Ioan Pet, Elena Alda, Simion Gergen, Iosif A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis |
title | A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis |
title_full | A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis |
title_fullStr | A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis |
title_full_unstemmed | A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis |
title_short | A novel exploratory chemometric approach to environmental monitorring by combining block clustering with Partial Least Square (PLS) analysis |
title_sort | novel exploratory chemometric approach to environmental monitorring by combining block clustering with partial least square (pls) analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765894/ https://www.ncbi.nlm.nih.gov/pubmed/23987502 http://dx.doi.org/10.1186/1752-153X-7-145 |
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