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dc.contributor.authorJankauskas, Benediktas
dc.contributor.authorSlepetiene, Alvyra
dc.contributor.authorJankauskiene, Genovaite
dc.contributor.authorFullen, Michael A.
dc.contributor.authorBooth, Colin A.
dc.date.accessioned2011-06-10T13:35:44Z
dc.date.available2011-06-10T13:35:44Z
dc.date.issued2006
dc.identifier.citationGeoderma 136: 763–773
dc.identifier.issn0016-7061
dc.identifier.urihttp://hdl.handle.net/2436/132960
dc.description.abstractLarge archive databases of soil organic matter (SOM) widely exist in Lithuania and the other countries of Central and Eastern Europe. Despite the demise of the former Soviet Union over 16 years ago, and Lithuania's integration as a full European Union state, difficulties of SOM data acceptance remain where these results are presented for publication in international journals, due to methodological differences between laboratory protocols. Therefore, the scientific pilot project ‘Carbon sequestration in Lithuanian soils’, supported by the Leverhulme Trust (U.K.), included an objective to correlate soil carbon methodologies, using Lithuanian Eutric Albeluvisols. A comparison of SOM content data acquired using five different analytical methods is reported. The research programme included a specific objective to correlate analytical methods for SOM analyses. A total of 92 Eutric Albeluvisol samples were collected from topsoil (0–0.2 m: Ap, n=36; Ah, n=10) and subsoil (0.2–0.4 m: Bt, n=46) horizons of 46 long-term experimental field plots at the Kaltinenai Research Station of the Lithuanian Institute of Agriculture. Each sample was then subsampled and analysed for SOM using dry combustion (by automatic elemental analyser), Walkley–Black (USDA), Tyurin photometrical, Tyurin titrimetrical and loss-on-ignition (LoI) methods (the later performed, in parallel, in both Lithuania and U.K. laboratories). Linear correlation and paired regression equations were calculated. Correlation coefficients between the sets of results varied between r=0.81–0.96 (from 0–0.2 m, n=46, P<0.001) and r=0.76–0.98 (from 0.2–0.4 m, n=46, P<0.001). Based on the strength and significance of these relationships, it is proposed that simple linear or more complex paired regression equations can be confidently employed to recalculate SOM data between various analytical methodologies. Future work will continue these investigations on other soil units and environments, hereby enhancing the database.
dc.language.isoen
dc.relation.urlhttp://www.swetswise.com/link/access_db?issn=0016-7061&mode=A_MLL
dc.subjectArable soils
dc.subjectSoil organic matter
dc.subjectAnalytical methods
dc.subjectSoil particle size
dc.subjectCorrelation–regression
dc.subjectCarbon sequestration
dc.titleA comparative study of analytical methodologies to determine the soil organic matter content of Lithuanian Eutric Albeluvisols
dc.typeJournal article
dc.identifier.journalGeoderma
html.description.abstractLarge archive databases of soil organic matter (SOM) widely exist in Lithuania and the other countries of Central and Eastern Europe. Despite the demise of the former Soviet Union over 16 years ago, and Lithuania's integration as a full European Union state, difficulties of SOM data acceptance remain where these results are presented for publication in international journals, due to methodological differences between laboratory protocols. Therefore, the scientific pilot project ‘Carbon sequestration in Lithuanian soils’, supported by the Leverhulme Trust (U.K.), included an objective to correlate soil carbon methodologies, using Lithuanian Eutric Albeluvisols. A comparison of SOM content data acquired using five different analytical methods is reported. The research programme included a specific objective to correlate analytical methods for SOM analyses. A total of 92 Eutric Albeluvisol samples were collected from topsoil (0–0.2 m: Ap, n=36; Ah, n=10) and subsoil (0.2–0.4 m: Bt, n=46) horizons of 46 long-term experimental field plots at the Kaltinenai Research Station of the Lithuanian Institute of Agriculture. Each sample was then subsampled and analysed for SOM using dry combustion (by automatic elemental analyser), Walkley–Black (USDA), Tyurin photometrical, Tyurin titrimetrical and loss-on-ignition (LoI) methods (the later performed, in parallel, in both Lithuania and U.K. laboratories). Linear correlation and paired regression equations were calculated. Correlation coefficients between the sets of results varied between r=0.81–0.96 (from 0–0.2 m, n=46, P<0.001) and r=0.76–0.98 (from 0.2–0.4 m, n=46, P<0.001). Based on the strength and significance of these relationships, it is proposed that simple linear or more complex paired regression equations can be confidently employed to recalculate SOM data between various analytical methodologies. Future work will continue these investigations on other soil units and environments, hereby enhancing the database.


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