101619 Can Soil Organic Matter Quantity and Quality Predict Potential Nitrogen Mineralization?.

Poster Number 346-218

See more from this Division: SSSA Division: Soil Biology and Biochemistry
See more from this Session: Soil Health in Agroecosystems/Rangelands Poster

Tuesday, November 8, 2016
Phoenix Convention Center North, Exhibit Hall CDE

William R. Osterholz1, Oshri Rinot2, Abraham Shaviv2, Matt Liebman1 and Michael J Castellano3, (1)Iowa State University, Ames, IA
(2)Environmental, Water and Agricultural Engineering, Technion - Israel Institute of Technology, Haifa, Israel
(3)Iowa State University, Iowa State University, Ames, IA
Poster Presentation
  • Osterholz SSSA Poster 2016 N min prediction.pdf (2.3 MB)
  • Abstract:
    Nitrogen mineralization is a critical source of N for crop nutrition as well as N pollution, and may play an important role in assessments of soil health. As N mineralization is the result of the breakdown of organic N by soil microbes, the quantity and quality of soil organic matter influence rates of both gross N mineralization and net N mineralization and can potentially serve as predictors of mineralization rates. Additionally, fluorescence properties of extracted soil organic matter that are now easily obtained by fluorescence spectroscopy may be related to net and gross N mineralization rates and could provide an easy to measure predictor of N mineralization. Identification and verification of easily measureable predictors of gross N mineralization and net N mineralization could enable insights into N mineralization dynamics without requiring the time and resource intensive measurement of gross N mineralization.

    Utilizing agricultural soils from the Midwest US and Israel, we measured gross N mineralization with the 15N pool dilution method and potentially mineralizable N with a 7-day anaerobic incubation. We compared the measures of N mineralization with soil organic matter measurements including particulate organic matter C and N, cold water extractable C and N, and hot water extractable C and N, as well as a multiple fluorescence indices of dissolved organic matter. There were a number of significant positive and negative correlations between gross N mineralization, net N mineralization, and soil organic matter properties that were consistent across the examined soils. The use of multiple linear regression techniques enabled the formulation of prediction equations for N mineralization with R2 > 0.8. Interestingly, the best combination of predictors was different for gross N mineralization and net N mineralization, suggesting these processes are controlled by different factors.

    See more from this Division: SSSA Division: Soil Biology and Biochemistry
    See more from this Session: Soil Health in Agroecosystems/Rangelands Poster

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