Looking for biological indicators of soil using hierarchical clustering
Soil microbial activity (SMA) is related to the use and management of soil we hypothesized that a single change in the sequence of crop rotation could be detected through changes in the biological and microbial activity of the soil. We analyzed SMA from and agricultural typic argiudoll soil under no...
| Autores principales: | , , |
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| Formato: | Conferencia |
| Lenguaje: | Español |
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Asociación Argentina de la Ciencia del Suelo
2024
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/18019 |
| _version_ | 1855486087045054464 |
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| author | Rossi, Maria Sol Michelena, Roberto Casas, Roberto Raul |
| author_browse | Casas, Roberto Raul Michelena, Roberto Rossi, Maria Sol |
| author_facet | Rossi, Maria Sol Michelena, Roberto Casas, Roberto Raul |
| author_sort | Rossi, Maria Sol |
| collection | INTA Digital |
| description | Soil microbial activity (SMA) is related to the use and management of soil we hypothesized that a single change in the sequence of crop rotation could be detected through changes in the biological and microbial activity of the soil. We analyzed SMA from and agricultural typic argiudoll soil under no-tillage (NT) with different crop rotation (corn-oat-soybean(COS), corn-soybean (C-S) and undisturbed soil as control (N.C)). We measured dehydrogenase activity, B glucosidade activity, community level physiological profiles, taxonomic microbial grops and the physiologycal broup involved in the carbon cycle (cellulose-and_amylose-decomposing micro-organisms) to detect changes in microbial activity. We also measured carbon from microbial biomass, total organic carbon, soil respiration, sustrate induced respiration, biological quotient and metabolic quotient (QCO2) to detect changes in biological activity. Dependence on the variables analyzed by Bartlett's test allowed us the apply correspondence analysis and principal components analysis (PCA). PCA showed three different soil conditions and a negative correlation between qCO2 and the other variables. Hierarchical clustering analysis using ward algorithm confirmed that qCO2 and BMC showed the three soil conditions. In fact qCO2 and BMC explained the maximum sensitivity against contrasting management situations. Increased enzymatic activities in rotation with the highest crop residues expedite mineralization and mobilization of available nutritient. We observed a quick response of the SMA to a single change in the crop rotation. |
| format | Conferencia |
| id | INTA18019 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Español |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Asociación Argentina de la Ciencia del Suelo |
| publisherStr | Asociación Argentina de la Ciencia del Suelo |
| record_format | dspace |
| spelling | INTA180192024-06-04T11:37:05Z Looking for biological indicators of soil using hierarchical clustering Rossi, Maria Sol Michelena, Roberto Casas, Roberto Raul Crop Rotation Enzyme Activity Soil Rotación de Cultivos Actividad Enzimática Suelo Metabolic Quotient Soil Microbial Biomass Cociente Metabólico Biomasa Microbiana del Suelo Soil microbial activity (SMA) is related to the use and management of soil we hypothesized that a single change in the sequence of crop rotation could be detected through changes in the biological and microbial activity of the soil. We analyzed SMA from and agricultural typic argiudoll soil under no-tillage (NT) with different crop rotation (corn-oat-soybean(COS), corn-soybean (C-S) and undisturbed soil as control (N.C)). We measured dehydrogenase activity, B glucosidade activity, community level physiological profiles, taxonomic microbial grops and the physiologycal broup involved in the carbon cycle (cellulose-and_amylose-decomposing micro-organisms) to detect changes in microbial activity. We also measured carbon from microbial biomass, total organic carbon, soil respiration, sustrate induced respiration, biological quotient and metabolic quotient (QCO2) to detect changes in biological activity. Dependence on the variables analyzed by Bartlett's test allowed us the apply correspondence analysis and principal components analysis (PCA). PCA showed three different soil conditions and a negative correlation between qCO2 and the other variables. Hierarchical clustering analysis using ward algorithm confirmed that qCO2 and BMC showed the three soil conditions. In fact qCO2 and BMC explained the maximum sensitivity against contrasting management situations. Increased enzymatic activities in rotation with the highest crop residues expedite mineralization and mobilization of available nutritient. We observed a quick response of the SMA to a single change in the crop rotation. Instituto de Suelos Fil: Rossi, María Sol. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina Fil: Michelena, Roberto Oscar. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina Fil: Casas, Roberto Raúl. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina 2024-06-04T11:31:42Z 2024-06-04T11:31:42Z 2010-05-31 info:ar-repo/semantics/documento de conferencia info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/18019 spa info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Asociación Argentina de la Ciencia del Suelo 22o. Congreso Argentino de la Ciencia del Suelo. "El suelo pilar de la agroindustria en la pampa Argentina. Rosario, Argentina del 31 de mayo al 04 de junio de 2010. |
| spellingShingle | Crop Rotation Enzyme Activity Soil Rotación de Cultivos Actividad Enzimática Suelo Metabolic Quotient Soil Microbial Biomass Cociente Metabólico Biomasa Microbiana del Suelo Rossi, Maria Sol Michelena, Roberto Casas, Roberto Raul Looking for biological indicators of soil using hierarchical clustering |
| title | Looking for biological indicators of soil using hierarchical clustering |
| title_full | Looking for biological indicators of soil using hierarchical clustering |
| title_fullStr | Looking for biological indicators of soil using hierarchical clustering |
| title_full_unstemmed | Looking for biological indicators of soil using hierarchical clustering |
| title_short | Looking for biological indicators of soil using hierarchical clustering |
| title_sort | looking for biological indicators of soil using hierarchical clustering |
| topic | Crop Rotation Enzyme Activity Soil Rotación de Cultivos Actividad Enzimática Suelo Metabolic Quotient Soil Microbial Biomass Cociente Metabólico Biomasa Microbiana del Suelo |
| url | http://hdl.handle.net/20.500.12123/18019 |
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