Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data
Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tes...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Doležalová-Weissmannová, Helena [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Journal of thermal analysis and calorimetry - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969, 148(2022), 4 vom: 02. Nov., Seite 1599-1611 |
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| Übergeordnetes Werk: |
volume:148 ; year:2022 ; number:4 ; day:02 ; month:11 ; pages:1599-1611 |
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| DOI / URN: |
10.1007/s10973-022-11709-6 |
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| 520 | |a Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. | ||
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| 700 | 1 | |a Kučerík, Jiří |0 (orcid)0000-0001-9083-4866 |4 aut | |
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10.1007/s10973-022-11709-6 doi (DE-627)SPR04933123X (SPR)s10973-022-11709-6-e DE-627 ger DE-627 rakwb eng Doležalová-Weissmannová, Helena verfasserin aut Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. Thermogravimetry (dpeaa)DE-He213 Soil microbiological characteristics (dpeaa)DE-He213 Arable (dpeaa)DE-He213 Grassland (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Malý, Stanislav aut Brtnický, Martin aut Holátko, Jiří aut Demyan, Michael Scott aut Siewert, Christian aut Tokarski, David aut Kameníková, Eliška aut Kučerík, Jiří (orcid)0000-0001-9083-4866 aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 148(2022), 4 vom: 02. Nov., Seite 1599-1611 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 https://dx.doi.org/10.1007/s10973-022-11709-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 148 2022 4 02 11 1599-1611 |
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10.1007/s10973-022-11709-6 doi (DE-627)SPR04933123X (SPR)s10973-022-11709-6-e DE-627 ger DE-627 rakwb eng Doležalová-Weissmannová, Helena verfasserin aut Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. Thermogravimetry (dpeaa)DE-He213 Soil microbiological characteristics (dpeaa)DE-He213 Arable (dpeaa)DE-He213 Grassland (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Malý, Stanislav aut Brtnický, Martin aut Holátko, Jiří aut Demyan, Michael Scott aut Siewert, Christian aut Tokarski, David aut Kameníková, Eliška aut Kučerík, Jiří (orcid)0000-0001-9083-4866 aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 148(2022), 4 vom: 02. Nov., Seite 1599-1611 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 https://dx.doi.org/10.1007/s10973-022-11709-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 148 2022 4 02 11 1599-1611 |
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10.1007/s10973-022-11709-6 doi (DE-627)SPR04933123X (SPR)s10973-022-11709-6-e DE-627 ger DE-627 rakwb eng Doležalová-Weissmannová, Helena verfasserin aut Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. Thermogravimetry (dpeaa)DE-He213 Soil microbiological characteristics (dpeaa)DE-He213 Arable (dpeaa)DE-He213 Grassland (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Malý, Stanislav aut Brtnický, Martin aut Holátko, Jiří aut Demyan, Michael Scott aut Siewert, Christian aut Tokarski, David aut Kameníková, Eliška aut Kučerík, Jiří (orcid)0000-0001-9083-4866 aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 148(2022), 4 vom: 02. Nov., Seite 1599-1611 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 https://dx.doi.org/10.1007/s10973-022-11709-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 148 2022 4 02 11 1599-1611 |
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10.1007/s10973-022-11709-6 doi (DE-627)SPR04933123X (SPR)s10973-022-11709-6-e DE-627 ger DE-627 rakwb eng Doležalová-Weissmannová, Helena verfasserin aut Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. Thermogravimetry (dpeaa)DE-He213 Soil microbiological characteristics (dpeaa)DE-He213 Arable (dpeaa)DE-He213 Grassland (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Malý, Stanislav aut Brtnický, Martin aut Holátko, Jiří aut Demyan, Michael Scott aut Siewert, Christian aut Tokarski, David aut Kameníková, Eliška aut Kučerík, Jiří (orcid)0000-0001-9083-4866 aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 148(2022), 4 vom: 02. Nov., Seite 1599-1611 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 https://dx.doi.org/10.1007/s10973-022-11709-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 148 2022 4 02 11 1599-1611 |
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10.1007/s10973-022-11709-6 doi (DE-627)SPR04933123X (SPR)s10973-022-11709-6-e DE-627 ger DE-627 rakwb eng Doležalová-Weissmannová, Helena verfasserin aut Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. Thermogravimetry (dpeaa)DE-He213 Soil microbiological characteristics (dpeaa)DE-He213 Arable (dpeaa)DE-He213 Grassland (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 Malý, Stanislav aut Brtnický, Martin aut Holátko, Jiří aut Demyan, Michael Scott aut Siewert, Christian aut Tokarski, David aut Kameníková, Eliška aut Kučerík, Jiří (orcid)0000-0001-9083-4866 aut Enthalten in Journal of thermal analysis and calorimetry Dordrecht [u.a.] : Springer Science + Business Media B.V., 1969 148(2022), 4 vom: 02. Nov., Seite 1599-1611 (DE-627)315295422 (DE-600)2017304-0 1572-8943 nnns volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 https://dx.doi.org/10.1007/s10973-022-11709-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 148 2022 4 02 11 1599-1611 |
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Enthalten in Journal of thermal analysis and calorimetry 148(2022), 4 vom: 02. Nov., Seite 1599-1611 volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 |
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Enthalten in Journal of thermal analysis and calorimetry 148(2022), 4 vom: 02. Nov., Seite 1599-1611 volume:148 year:2022 number:4 day:02 month:11 pages:1599-1611 |
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Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. 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Doležalová-Weissmannová, Helena |
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Doležalová-Weissmannová, Helena misc Thermogravimetry misc Soil microbiological characteristics misc Arable misc Grassland misc Correlation Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data |
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Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data Thermogravimetry (dpeaa)DE-He213 Soil microbiological characteristics (dpeaa)DE-He213 Arable (dpeaa)DE-He213 Grassland (dpeaa)DE-He213 Correlation (dpeaa)DE-He213 |
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Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data |
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Doležalová-Weissmannová, Helena Malý, Stanislav Brtnický, Martin Holátko, Jiří Demyan, Michael Scott Siewert, Christian Tokarski, David Kameníková, Eliška Kučerík, Jiří |
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practical applications of thermogravimetry in soil science: part 5. linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data |
| title_auth |
Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data |
| abstract |
Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet, which limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage, the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity, and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land-use management. © Akadémiai Kiadó, Budapest, Hungary 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Practical applications of thermogravimetry in soil science: Part 5. Linking the microbial soil characteristics of grassland and arable soils to thermogravimetry data |
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Malý, Stanislav Brtnický, Martin Holátko, Jiří Demyan, Michael Scott Siewert, Christian Tokarski, David Kameníková, Eliška Kučerík, Jiří |
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Malý, Stanislav Brtnický, Martin Holátko, Jiří Demyan, Michael Scott Siewert, Christian Tokarski, David Kameníková, Eliška Kučerík, Jiří |
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| score |
7.402936 |