137-25
Assessing Indices for Predicting Nitrogen Mineralization in Soils Under Sugarcane.

Poster Number 2101

Monday, November 4, 2013
Tampa Convention Center, East Hall, Third Floor

Eduardo Mariano1, Rafael Otto1, Jussara de Fátima Pereira2 and Paulo Cesar Ocheuze Trivelin2, (1)Department of Soil Science, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, Brazil
(2)Laboratory of Stable Isotopes, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, SP, Brazil
A realistic estimate of N mineralized from soil organic matter is essential for determining the rate of N fertilizer application required to optimize crop yield and quality and minimize adverse impacts of excessive N on the environment. We compared several indices (soil properties and chemical methods) against net-N mineralization determined by anaerobic incubation (AIN) to predict N mineralization over a range of soils under sugarcane. Soil sampling (0-20 and 20-40 cm) was carried out in 21 N-response sugarcane trials in São Paulo State, Brazil. The AIN was performed during 7 d at 40°C. Soil properties evaluated to estimate soil N mineralization were pH (0.01 mol L-1 CaCl2), sand, silt, clay, soil organic C (SOC) and soil total N (STN). Chemical methods assessed were phosphate-borate buffer at pH 11.2 (PBB), direct steam distillation with NaOH (DSD) and hot KCl-extractable N (HKCl). The PBB and HKCl indices were determined by counting the preexisting soil NH4+-N. All indices were significant correlated with AIN. The SOC, STN, PBB, DSD and HKCl were moderately correlated to AIN (r ranging from 0.60 to 0.69) and had linear regressions with r2 ranging from 0.36 to 0.47. The pH, sand, silt and clay provided poor correlations with AIN (r < 0.58; r2 < 0.33). The pH, sand, SOC, STN, PBB and DSD produced the best linear multiple regression by stepwise procedure for predicting AIN (r2 = 0.79). For this study, no single N availability index has proven robust enough for broad acceptance. However, our results suggest that a combination of laboratory methods can be useful for predicting net-N mineralization for sugarcane cropped soils.
See more from this Division: SSSA Division: Soil Fertility & Plant Nutrition
See more from this Session: Nitrogen Soil Fertility and Management

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