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Irrigated cotton in Australia is mainly grown on heavy textured soils which are prone to waterlogging, resulting in significant losses of nitrogen (N) via denitrification and surface run-off. This study investigated fertiliser nitrogen use efficiency (fNUE) over three seasons on five commercial cotton farms using the 15N tracer technique. Fertiliser NUE was consistently low across all fertilised treatments, with on average 47% of the applied fertiliser lost and only 17% of the N taken up by the crop derived from fertiliser. There was no significant effect of different N fertiliser products and rates on cotton lint yield. High lint yields (0.9–3.6 Mg ha−1) could be achieved even without the application of N fertiliser, demonstrating mineralisation of soil organic N, residual fertiliser, or N returned with crop residues, as key source of N in these cropping systems. Using the nitrification inhibitor DMPP and overhead instead of furrow irrigation showed potential to reduce N fertiliser losses. The results demonstrate that under current on-farm management fNUE is low on irrigated cotton farms in Australia and highlight the need to account for soil N stocks and mineralisation rates when assessing optimized fertiliser rates. There is substantial scope to improve fNUE and reduce N losses without any impact on lint yield, by adjusting N fertiliser application rates, in particular in combination with the use of the nitrification inhibitor DMPP. Using overhead instead of furrow irrigation is a promising approach to improve not only water use efficiency, but also fNUE in irrigated cotton systems.

Nitrogen (N) fertiliser inputs represent one of the largest variable costs in dryland cropping systems, and a key determinant of water-limited yield. Despite extensive research into microbial N losses via intermediate denitrification products such as N2O, limited research exists on total N losses, and the effect of increasing soil N surplus has on fertiliser use-efficiency is not clear. In this study, the fate of banded urea fertiliser N across crop uptake, soil residual N and N losses was determined using the 15N recovery technique over nine trials with four N rates (0, plus low, medium and high industry rates) across N responsive and non-N responsive sites over 3 years in dryland sorghum (Sorghum bicolor). On average, crop uptake efficiency ranged from 50% at the low and medium N rate (80 kg N ha−1) to < 38% at the highest N rate, and was as low as 5%. Nitrogen losses averaged 26.5% across all rates and trials. At the medium N rate, losses exceeded 18% in all trials, despite relatively dry seasons, and in some trials exceeded 34%. Losses of N were driven by large cumulative rain events and high early-season rainfall. In dryland systems, the inability of crops to acquire banded N fertiliser can potentially leave fertiliser stranded in the topsoil, leaving it vulnerable to losses.

Intensive vegetable production is characterised by high nitrogen (N) application rates and frequent irrigations, promoting elevated nitrous oxide (N2O) emissions, a powerful greenhouse gas indicative for the low N use efficiency (NUE) in these systems. The use of nitrification inhibitors (NI) has been promoted as an effective strategy to increase NUE and decrease N2O emissions in N-intensive agricultural systems. This study investigated the effect of two NIs, 3,4-dimethylpyrazole phosphate (DMPP) and 3-methylpyrazole 1,2,4-triazole (Piadin), on N2O emissions and 15N fertiliser recovery in a field experiment in sweet corn. The trial compared the conventional fertiliser N rate to a 20% reduced rate combined with either DMPP or Piadin. The use of NI-coated urea at a 20% reduced application rate decreased cumulative N2O emissions by 51% without yield penalty. More than 25% of applied N was lost from the conventional treatment, while a reduced N rate in combination with the use of a NI significantly decreased N fertiliser losses (by up to 98%). Across treatments, between 30 and 50% of applied N fertiliser remained in the soil, highlighting the need to account for residual N to optimise fertilisation in the following crop. The reduction of overall N losses without yield penalties suggests that the extra cost of using NIs can be compensated by reduced fertiliser application rates, making the use of NIs an economically viable management strategy for growers while minimising environmentally harmful N losses from vegetable growing systems.

Early detection of within-field yield variability for high-value commodity crops, such as cotton (Gossypium spp.), offers growers potential to improve decision-making, optimize yields, and increase profits. Over recent years, publicly available datasets have become increasingly available and at a resolution where within-field yield prediction is possible. However, the viability of using these datasets with machine learning to predict within-field cotton lint yield at key growth stages are largely unknown. This study was conducted on two cotton fields, located near Mungindi, New South Wales, Australia. Three years of yield data, soil, elevation, rainfall, and Landsat imagery were collected from each field. A total of 12 models were created using: (a) two machine learning algorithms: random forest (RF) and gradient boosting machines (GBM); (b) three growth stages: squaring, flowering, and boll-fill; and (c) two different amounts of variables: all variables and the optimal variables determined by a recursive feature elimination (RFE). Results showed a strong agreement between predicted and observed yields at flowering and boll-fill when more information was available. At flowering and boll-fill, root mean square error (RMSE) ranged between 0.15 and 0.20 t ha−1 and Lin's concordance correlation coefficient (LCCC) ranged between 0.50 and 0.66, with RF providing superior results in most cases. Models created using the optimal variables determined by the RFE provided similar results compared to using all variables, allowing greater model accuracy and resolution with targeted sampling. Overall, these findings indicate significant potential of publicly available datasets to predict within-field cotton yield and guide decision-making in-season.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield-scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The pote

Grain sorghum grown in north-eastern Australia’s cropping region increasingly requires nitrogen (N) fertiliser to supplement the soil available N supply. The rates of N required can be high when fallows between crop seasons are short (higher cropping intensities) and when yield potentials are high. Fertiliser N is typically applied before or at crop sowing and is vulnerable to environmental loss in the period between application and significant crop N demand due to potentially intense rainfall events in the summer-dominant rainfall environment. Nitrification inhibitors added to urea can reduce certain gaseous loss pathways but the agronomic efficacy of these products has not been explored. Urea and urea coated with the nitrification inhibitor DMPP (3,4-dimethylpyrazole phosphate) were compared in sorghum crops grown at five research sites over consecutive summer sorghum growing seasons in south-east Queensland. Products were compared in terms of crop responses in dry matter, N uptake and grain yield, with DMPP found to produce only subtle increases on grain yield. There was no effect on dry matter or N uptake. Outcomes suggest any advantages from use of DMPP in this region are most significant in situations where higher fertiliser application rates (>80 kg N/ha) are required.

The potential for elevated nitrous oxide (N2O) losses is high in subtropical cereal cropping systems in north-east Australia, where the fertiliser nitrogen (N) input is one single application at or before planting. The use of urea coated with the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) has been reported to substantially decrease N2O emissions and increase crop yields in humid, high-intensity rainfall environments. However, it is still uncertain whether this product is similarly effective in contrasting soil types in the cropping region of north-east Australia. In this study the grain yield response of sorghum (Sorghum bicolor L. Moench) to rates of fertiliser N applied as urea or urea coated with DMPP were compared in crops grown on a Vertisol and an Oxisol in southern Queensland. Seasonal N2O emissions were monitored on selected treatments for the duration of the cropping season and the early stages of a subsequent fallow period using a fully automated high-frequency greenhouse gas measuring system. On each soil the tested treatments included an unfertilised control (0 kg N ha–1) and two fertilised treatments chosen on the basis of delivering at least 90% of seasonal potential grain yield (160 and 120 kg N ha–1 on the Vertisol and Oxisol respectively) or at a common (suboptimal) rate at each site (80 kg N ha–1). During this study DMPP had a similar impact at both sites, clearly inhibiting nitrification for up to 8 weeks after fertiliser application. Despite the relatively dry seasonal conditions during most of the monitoring period, DMPP was effective in abating N2O emissions on both soils and on average reduced seasonal N2O emissions by 60% compared with conventional urea at fertiliser N rates equivalent to those producing 90% of site maximum grain yield. The significant abatement of N2O emissions observed with DMPP, however, did not translate into significant yield gains or improvements in agronomic efficiencies of fertiliser N use. These re

To meet the global food demand in the coming decades, crop yields per unit area must increase. This can only be achieved by a further intensification of existing cropping systems and will require even higher inputs of N fertilisers, which may result in increased losses of nitrous oxide (N2O) from cropped soils. Enhanced efficiency fertilisers (EEFs) have been promoted as a potential strategy to mitigate N2O emissions and improve nitrogen use efficiency (NUE) in cereal cropping systems. However, only limited data are currently available on the use of different EEF products in sub-tropical cereal systems. A field experiment was conducted to investigate the effect of three different EEFs on N2O emissions, NUE and yield in a sub-tropical summer cereal cropping system in Australia. Over an entire year soil N2O fluxes were monitored continuously (3 h sampling frequency) with a fully-automated measuring system. The experimental site was fertilised with different nitrogen (N) fertilisers applied at 170 kg N ha–1, namely conventional urea (Urea), urea with the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP), polymer-coated urea (PCU), and urea with the nitrification inhibitor nitrapyrin (Nitrapyrin). Nitrous oxide emissions were highly episodic and mainly controlled by heavy rainfall events within two months of planting and fertiliser N application. Annual N2O emissions in the four treatments amounted to 2.31, 0.40, 0.69 and 1.58 kg N2O-N ha–1 year–1 for Urea, DMPP, PCU and Nitrapyrin treatments, respectively, while unfertilised plots produced an average of 0.16 kg N2O-N ha–1 year–1. Two of the tested products (DMPP and PCU) were found to be highly effective, decreasing annual N2O losses by 83% and 70%, respectively, but did not affect yield or NUE. This study shows that EEFs have a high potential to decrease N2O emissions from sub-tropical cereal cropping systems. More research is needed to assess if the increased costs of EEFs can be compensated by lower fert

This is the first study to investigate alternative fertilisation strategies to increase cereal production while reducing greenhouse gas emissions from the most common soil type in subtropical regions. The results of this research will contribute to define future farming practices to achieve global food security and mitigate climate change. The study established that introducing legumes in cropping systems is the most agronomically viable and environmentally sustainable fertilisation strategy. Importantly, this strategy can be widely adopted in subtropical regions since it is economically accessible, requires little know-how transfer and technology investment, and can be profitable in both low- and high-input cropping systems.