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dc.contributor.author
Alvarez, Roberto  
dc.contributor.other
Adewuyi, Bolanle  
dc.contributor.other
Chukwu, Kayin  
dc.date.available
2021-07-28T18:12:09Z  
dc.date.issued
2012  
dc.identifier.citation
Alvarez, Roberto; Agricultural Management Changes in Pampean Soils Related to Rotation and Tillage: Impacts on Soil Organic Reservoirs; Nova Science Publishers; 2012; 29-54  
dc.identifier.isbn
978-1-62081-087-3  
dc.identifier.uri
http://hdl.handle.net/11336/137257  
dc.description.abstract
Pampean cropped area has doubled during the last four decades. A profound change in these agro-systems has been the introduction of soybean in crop rotations, replacing mainly corn, and at present it constitutes the most important grain crop. The significant increase in fertilizer rate and associated technological improvements resulted in crop yield increases that range between 100 and 200 %. Up to one meter depth, a soil organic carbon stock of 4.12 Gt was estimated using national soil survey information performed from 1960 and 1980. To asses the organic carbon stock at present, a soil sampling during 2007-2008 was performed at 386 sites distributed along the Pampas under contrasting vegetation types and land uses. With this information, an artificial neural network model was developed to predict organic carbon as a function of vegetation cover and land use. An organic carbon stock of 4.22 Gt was estimated using this model together with satellite imaging classification of common vegetation types and soil uses. Comparing these stocks leads to no great organic carbon changes in the last 40 years; nevertheless, significant decreases were observed at areas with high organic carbon; meanwhile, at areas with low organic carbon content no changes and even increases were detected. Microbial soil respiration was determined from seven long term field experiments and results were used to develop a neural network model that estimates organic carbon mineralization. Moreover, results of 113 experiments were used to formulate another neural network model to relate soybean, corn, and wheat yield to soil carbon inputs from crop residues. Combining the two latter models allowed the soil carbon balance estimation for different crop rotations and soils. In fact, soil carbon balances are less negative than 40 years ago or turned out positive in soils with low carbon, even though soybean was introduced in crop rotations. A feasible explanation is that yield increases and the related increase in carbon input from residues, in straw and roots, have compensated the lower biomass soybean production compared to corn. No-till adoption by farmers in the Pampas was massive and at the moment in 70 % of the cropped area this tillage system is applied. Information from 17 tillage experiments performed in the region was used to perform a meta-analysis that shows that under no-till management soil carbon at surface increases 5 % in rich organic matter soils and 15 % in low organic matter soils. The lower carbon residue input from soybean can be counterbalanced by the no-till system effect which helps soil carbon level maintenance. The neural network models predict that soil organic carbon content in some pampean areas will decrease in the future if the soybean proportion in crop rotations is not reduced. The soybean biological nitrogen fixation was accounted for by 10 field experiments were 15N was used and a model was developed that relates grain yield to fixed nitrogen. Agro-system nitrogen balance was calculated, fertilizer nitrogen and fixed nitrogen are inputs and nitrogen in harvested grains is the output. Biologically fixed nitrogen is 4-fold the amount of nitrogen that enters by fertilization. The nitrogen balance of soybean is slightly negative compared to corn, which is more negative. The inclusion of soybean in crop rotations results in an input-output ratio of nitrogen that approximates to one for the region.  
dc.format
application/pdf  
dc.language.iso
spa  
dc.publisher
Nova Science Publishers  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Suelos  
dc.subject
Fertilidad  
dc.subject
Red neuronal artificial  
dc.subject.classification
Ciencias del Suelo  
dc.subject.classification
Agricultura, Silvicultura y Pesca  
dc.subject.classification
CIENCIAS AGRÍCOLAS  
dc.title
Agricultural Management Changes in Pampean Soils Related to Rotation and Tillage: Impacts on Soil Organic Reservoirs  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.type
info:eu-repo/semantics/bookPart  
dc.type
info:ar-repo/semantics/parte de libro  
dc.date.updated
2021-07-26T17:11:30Z  
dc.journal.pagination
29-54  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Nueva York  
dc.description.fil
Fil: Alvarez, Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía; Argentina  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://novapublishers.com/shop/soil-fertility-characteristics-processes-and-management/  
dc.conicet.paginas
166  
dc.source.titulo
Soil Fertility: Characteristics, Processes and Management