Nitrogen mineralisation in sugarcane soils in Queensland, Australia: I. evaluation of soil tests for predicting nitrogen mineralisation
D. E. Allen
A F , P. M. Bloesch A , T. G. Orton A B , B. L. Schroeder C , D. M. Skocaj D , W. Wang A , B. Masters E and P. M. Moody A
+ Author Affiliations
- Author Affiliations
A Landscape Sciences, Ecosciences Precinct, Department of Environment and Science, Queensland Government, GPO Box 2454, Brisbane, Qld 4001, Australia.
B The University of Queensland, School of Agriculture and Food Sciences, St Lucia, Qld 4072, Australia.
C University of Southern Queensland, West Street, Toowoomba, Qld 4350, Australia.
D Sugar Research Australia, Tully, Qld 4854, Australia.
E Land and Water Science, Department of Natural Resources, Mines and Energy, Queensland Government, Mareeba, Qld 4880, Australia.
F Corresponding author. Email: Diane.Allen@des.qld.gov.au
Soil Research 57(7) 738-754 https://doi.org/10.1071/SR19031
Submitted: 13 February 2019 Accepted: 1 July 2019 Published: 23 September 2019
Abstract
We explored soil properties as indices of mineralisable nitrogen (N) in sugarcane soils and whether we could increase the accuracy of predicting N mineralisation during laboratory incubations. Utilising historical data in combination with samples collected during 2016, we: (i) measured mineralised N over the course of short-term (14 days) and long-term (301 days) laboratory incubations; (ii) compared models representing mineralisation; then (iii) related model parameters to measured soil properties. We found measures representing the labile organic N pool (Hydrolysable NaOH organic N; amino sugar Illinois soil N test) best related to short-term mineralised N (R2 of 0.50–0.57, P < 0.001), while measures of CO2 production (3, 7, 10 and 14 days) best related to longer-term mineralised N (R2 of 0.75–0.84, P < 0.001). Indices were brought together to model the active and slow pools of a two-pool mineralisation model in the statistical framework of a mixed-effects model. Of the models that relied on measurement of one soil property, cumulative CO2 production (7 days) performed the best when considering all soil types; in a cross-validation test, this model gave an external R2 of 0.77 for prediction of the 301-day mineralised N. Since the mixed-effects model accounts for the various sources of uncertainty, we suggest this approach as a framework for prediction of in-field available N, with further measurement of long-term mineralised N in other soils to strengthen predictive certainty of these soil indices.
Additional keywords: exponential model, kinetics, N0, soil N supply.
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