Archive for the category: New methods of measuring reactive nitrogen in the environment

Richard Brackin¹, Torgny Näsholm^2,3, Nicole Robinson¹, Stéphane Guillou¹, Kerry Vinall¹, Scott Buckley¹, Prakash Lakshmanan⁴, Susanne Schmidt¹, Erich Inselsbacher^5
1 School of Agriculture and Food Sciences, The University of Queensland, QLD, 4072 Brisbane, Australia; email: richard.brackin@uqconnect.edu.au

² Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, SE-90183 Umeå.

³ Department of Forest Genetics and Plant Physiology, Umeå Plant Science Center, Swedish University of Agricultural Sciences, SE-90183 Umeå.

⁴ Sugar Research Australia, 50 Meiers Road, Indooroopilly, QLD 4068 Brisbane, Australia.

⁵ Department of Geography and Regional Research, University of Vienna, AT-1090 Vienna, Austria.

Abstract

Extracts of soil are used to provide estimates of plant-available nitrogen sources such as nitrate, ammonium and amino acids (low molecular weight nitrogen, LMW-N). Soil extracts are a blunt tool; they introduce a number of inaccuracies through soil disturbance, and do not indicate the rapidity of N pool turnover. Microdialysis is used predominantly in neuroscience but was recently introduced in soil research. Small in situ probes cause minimal disturbance, and passive diffusion of solutes across a semi-permeable membrane allows dialysate to be collected over time allowing study of nutrient flux dynamics. This sampling mode is functionally similar to plant roots, and may provide a good estimate of the N forms available to roots. We used microdialysis to quantify induced diffusive fluxes of LMW-N in a subtropical agricultural soil under three fertiliser regimes. Shifts in LMW-N fluxes were detected over time, suggesting the formation of depletion zones around the probe surface similar to those associated with roots. A pronounced difference was observed between results from microdialysis and soil extracts. In dialysate, amino acids contributed up to 70% of LMW-N in unfertilised soil and 5-20% in fertilised soils. In contrast, amino acids were a minor constituent in soil extracts, highlighting that soil extracts underestimate amino acid availability in soils. Modelling plant N uptake based on soil N fluxes and root uptake kinetics, we show that use of inorganic N in fertilised soil was constrained by the root’s uptake. In contrast, fluxes of amino acids and the root’s uptake capacity were closely matched.

Friederike Gnädinger and Urs Schmidhalter 

Chair of Plant Nutrition, Technical University of Munich (TUM), Emil-Raman-Str.2, 85354 Freising

Abstract

Yields are primarily dependent on the input of nitrogen. Since fertilization poses serious environmental concerns, better performing maize cultivars with reduced nitrogen inputs are required. The aim of this work is to develop efficient phenotyping procedures to assess differences in nitrogen uptake and nitrogen use efficiency at the reproductive stage of maize cultivars supplied with different nitrogen doses. Both, active and passive sensor systems were tested to assess such traits and the spectral information was related to destructively assessed parameters of the aboveground biomass and nitrogen uptake at flowering, kernel dough stage and at grain harvest. In general, spectral indices obtained from the hyperspectral sensor were better related to the biomass or the nitrogen uptake of maize cultivars than those obtained from active sensors. Optimized hyperspectral indices were closest related to the leaf dry biomass with R²-values of 0.55 and to the Nitrogen Nutrition Index with R² = 0.77 at the kernel dough stage. PLSR models were calculated for two experimental years, using data from 2015 as calibration data set and from 2014 as validation data set and allowed to predict leaf nitrogen uptake with R² = 0.70 and RMSE of 10.8 kg N ha^-1. The phenotyping platform PhenoTrac 4 developed by TUM allowed to obtain enhanced information of the complex traits nitrogen uptake and nitrogen use efficiency. In combination with improved algorithms using both optimized indices as well as PLSR models promising results were obtained to further narrow the gap existing between genomics and phenomics.

Caio T. Inácio¹, Segundo Urquiaga², Phillip M. Chalk³

¹ Embrapa Solos, Rua Jardim Botânico 1024, Rio de Janeiro, RJ, 22460-000, www.embrapa.br/solos, caio.teves@embrapa.br

² Embrapa Agrobiologia, Rodovia BR-465 KM 7, Seropédica, RJ, 23891-000

³ University of Melbourne, Parkville 3010, Melbourne, Victoria

Abstract

The remarkable influence of organic inputs, such as manure and compost, on d¹⁵N values of growing plants suggests the possible use of ¹⁵N natural abundance as a tracer of N. Thus, using ¹⁵N natural abundance might be possible to estimate compost-N recovery as an alternative method to the use of ¹⁵N-enriched materials. The objective of this study was to verify the feasibility of using d¹⁵N value to estimate compost-N recovery by plants. Head lettuce, carrots and broccoli were cultivated (randomized blocks) in sequence under increasing levels (0 to 2.5 kg/m², dry matter) of compost application. Pearson correlations were significant and positive between plants d¹⁵N and yield (except lettuce, no yield response). A new equation for estimating compost-N recovery by plants was proposed using differences in d¹⁵N-plant with and without compost application. The compost-N recoveries were 2-8 % for lettuce, 4-9 % for carrots, and 9-18 % for broccoli. Unrealistic estimates were disregarded and assigned primarily to non-representative sampling because of intra-plant d¹⁵N variations. This study showed the theoretical and experimental basis of using d¹⁵N values to estimate compost-N recovery by test plants.