|Ph.D Student||Rinot Oshri|
|Subject||Improved Prediction of Nitrogen Mineralization and|
Nitrification Rates in Soils
|Department||Department of Civil and Environmental Engineering||Supervisors||Professor Emeritus Abraham Shaviv|
|Professor Raphael Linker|
|Full Thesis text|
Organic nitrogen (N) increases soil N inputs for crop demand, on the other hand, it may induce water contamination and air pollution. There is great importance for more precise and handy methods to predict soil N dynamics. Ion exchange resins (IERs) became an optional approach for measuring N fluxes in agro-ecosystems. Mineral N is adsorbed by IERs, so that they serve as strong sinks for it. Uniform mixing of IER beads minimize diffusion constrains and effectively "mimic" plant roots. Another possible method to predict N mineralization rates (NMR) is by water extraction combined with Excitation-Emission Matrix (EEM) spectroscopy. Chemometric tools such Parallel Factors Analysis (PARAFAC) for EEM may assist in characterizing water extractable organic matter (WEOM) components and improve its reliability as N availability indicator. The main research hypothesis is that sensible utilization of IER or alternatively water extraction combined with EEM measurements may provide an effective solution for obtaining realistic rates for mineralization and nitrification in soils. The main research objectives and the performed experiments are: 1. testing the utilization of IER beads for improved evaluation of mineralization and nitrification rates; 2. Examining the utilization of water extraction along with EEM analysis during soil incubations for evaluation of changes in WEOM and N availability; 3. Prediction of NMR in various agro-eco systems by EEM spectra of soil water extracts; 4. Comparison between N dynamics obtained by IERs utilization and plant N uptake in a greenhouse planters experiment. Our research results show that denitrification losses are significantly reduced and nitrification rates are enhanced by uniformly distributing anion exchange resin (AERs) beads in soils. In addition, NMR are higher in the AER treatments (under lower N loads). Mixed bed IERs (H/ OH- loaded) treatments provide higher NMR than AER treatments, in most examined soils. This is related, both, to N adsorption on IERs and to higher availability of soil organic matter. However, some factors such IER effect on soil structure as well as N adsorption efficiency by IERs must be considered. The relative change of EEM-PARAFAC components in WEOM during incubation time assist in detecting changes induced by bio-processes and IER utilization. In addition, linear combination between WEOM quantitative parameters and/or PARAFAC components enables reliable prediction of NMR. EEM analysis of WEOM from different agro-ecosystems (Midwest - USA and Israel) enables detection of changes between characteristic organic components and effects of environmental and agronomic practices. Additionally, EEM data of WEOM provide effective and rapid prediction of gross and potential NMR by utilization of N-way partial least squares (NPLS) model. A comparison between N dynamics under IER treatments and Basil growth in a greenhouse planter experiment show the potential of effective distribution of IERs beads to better “mimic” N mineralization under cropping systems.