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Performance of the APSIM (Agricultural Production Systems sIMulator) wheat model was assessed to simulate winter wheat phenology, biomass, grain yield, and nitrogen (N) uptake for its potential to optimize fertilizer applications for optimal crop growth and minimal environmental degradation. The calibration and evaluation dataset had 144 and 72 different field growing conditions (location (~7) × year (~5) × sowing date (2) × N treatment (7–13)), respectively, and included seven cultivars. APSIM simulated phenological stages satisfactorily with both model calibration and evaluation data sets with r2 of 0.97 and RMSE of 3.98–4.15 BBCH (BASF, Bayer, Ciba-Geigy, and Hoechst) scale. Simulations for biomass accumulation and N uptake during early growth stages (BBCH 28–49) were also reasonable with r2 of 0.65 and RMSE of 1510 kg ha−1, and r2 of 0.64–0.66 and RMSE of 28–39 kg N ha−1, respectively, with a higher accuracy during booting (BBCH 45–47). Overestimation of N uptake during stem elongation (BBCH 32–39) was attributed to (1) high inter-annual variability in simulations, and (2) high sensitivity of parameters regulating N uptake from soil. Calibration accuracy of grain yield and grain N was higher than that of biomass and N uptake at the early growth stages. APSIM wheat model showed high potential for optimizing fertilizer management in winter wheat cultivation in Northern Europe. [ABSTRACT FROM AUTHOR]

BACKGROUND: Nitrogen (N) fertiliser used on crops is among the main sources of water pollution. Reliable measurement of N losses from land uses in catchments is key to designing effective management strategies that minimise those losses at the same time as keeping farms profitable. In the present study, we used a management simulation tool within the Agricultural Production Systems sIMulator (APSIM) to assess the effect of fertiliser management on N leaching from croplands in the Aparima catchment in Southland, New Zealand. The assessment was based on two N‐fertiliser regimes: (i) Scheduled (conventional) where, N‐fertiliser rates and timing of application followed a prescribed programme, and (ii) Soil‐test where, N‐fertiliser rates and timing depended on daily analysis of simulated soil N levels. Four rotations (continuous wheat, pasture‐wheat‐grain oats, wheat‐fodder beet‐peas and wheat‐green oats‐fodder beet‐peas) were used in the evaluation. RESULTS: APSIM simulated crop productivity with reasonable accuracy. Yields were 2% greater, fertiliser N input was 11% lower and leaching was 20% lower under the Soil‐test compared to the Scheduled fertiliser management. These results show the potential of a Soil‐test based fertiliser application to increase fertiliser‐N use efficiency and reduce the risk of N loss to the Southland catchment water systems. CONCLUSION: The present study demonstrates a dynamic farm systems model can be a viable tool to generate valuable data for assessing the productivity and environmental effects of cropping systems at a catchment scale. © 2021 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Highlights • A modelling approach was used to test different irrigation managements. • In a shallow soil more frequent irrigation resulted in a higher pasture production. • In deep soils pasture production was not affected by irrigation frequency. • Building up of soil water deficits in less frequent irrigation reduced N losses. Abstract While the benefits of irrigation for agricultural production are well established, the effects of irrigation management on production and environmental consequences are not well quantified. We used the APSIM (Agricultural Production Systems sIMulator) model to simulate the effect of six different irrigation management scenarios on pasture production and nitrogen (N) losses from both urine patches and non-urine affected areas using New Zealand farming systems as a test case. Nitrogen losses included nitrate (NO 3) leaching, and gaseous emissions via ammonia (NH 3) volatilisation and denitrification (nitrous oxide (N 2 O) and dinitrogen (N 2) emissions). The effects of different climate and rainfall regimes were simulated for three different soil types – deep, poorly drained (Otokia), deep, well drained (Templeton) and shallow, well drained (Eyre) soils, using 20 years of data from two climate stations with mean annual rainfall amounts of 600 and 800 mm. In the shallow soil with the least plant available water, more frequent irrigation with higher total annual amounts resulted in a significant increase in predicted pasture production compared with less frequent irrigation due to less plant water stress. However, predicted N losses through leaching, denitrification and N 2 O emissions also increased. In the deep soils pasture growth was not affected by the frequency of irrigation, whereas denitrification increased with higher frequency irrigation, especially in the poorly drained soil, leading to increased N 2 O emissions. Based on these modelling results, N losses can be reduced with little effect on production by irrigating less frequently and maintaining soil water deficits. [ABSTRACT FROM AUTHOR]

To demonstrate the use of a previously developed fertilisation algorithm and to determine its potential effects on nitrogen (N) losses from grazed pastoral systems, a simulation study was performed using the Agricultural Production Systems Simulator (APSIM). The study considered a dairy system with irrigated ryegrass pasture on a silt loam soil in the Canterbury region of New Zealand. Firstly, the algorithm was parameterised for each month based on pasture yield and N contents from simulation run over 20 years using a wide range of N fertilisation rates. The algorithm was then used in the simulation of fertilisation management of a hypothetical dairy farm under different scenarios where its performance for increasing pasture yield with more efficient N use was tested. The scenarios were based on different yield targets for the proposed algorithm (50, 75, 90 or 100% of the average maximum yield) and included scheduled fertilisation to mimic more typical management. For more realistic evaluation, the simulations took into account changes in stocking rates and N flows in the farm resulting from the different fertiliser management. The simulations also considered the uneven return of urinary N by grazing animals, which are crucial to determine N losses in these systems. Both pasture yield and N losses were in general agreement with available measured data from similar systems and with comparable N inputs. Thus providing support for the simulation study as a valid way to demonstrate the potential effects of changing fertiliser management. The average of simulations run over 10 years showed that direct losses from the fertiliser were lower when the fertilisation was controlled by the proposed algorithm compared with scheduled fertilisation at similar N rates. However, with animals in the paddock and thus including the effects of urine patches, N losses were not significantly different. As there was an increase in pasture yield and consequent stocking numbers, the area receiving urinary N increased, counter balancing the increased N use efficiency when using the algorithm. Nonetheless, the larger yield lead to greater farm productivity, and this resulted in about 13% reduction in N losses per unit of milk production. [ABSTRACT FROM AUTHOR]

Decoupling productivity and environmental pollution growth is a key objective of modern agricultural systems. The use of diverse (multispecies) pastures may contribute to this objective. Increasing the species diversity of intensively managed pastures can potentially increase annual herbage growth and N use efficiency. Here, we review the literature on simple (predominantly perennial ryegrass and white clover mixes) and diverse temperate pastures (those with three or more sown species) that address the soil-plant-animal interrelationships relevant to N leaching losses from intensive grazing systems. An analysis of trial results suggests that annual herbage yields from diverse mixtures are greater than those from simple mixtures. The review also suggests that greater species diversity in pastures can increase sward N uptake, attributable to complementarity of species through differentiation in rooting depths and seasonal plant growth activity. The presence of specific species in the sward was more relevant to herbage production and N dynamics than the number of species present in the sward, emphasizing the role of well-adapted plant functional types. The inclusion of forbs (e.g., chicory and plantain) in pastures is also shown to aid in reducing the N load of urine patches, thereby reducing the risk of N leaching from grazed pastures. To achieve the objective of increasing productivity and reducing N leaching, research questions remain around the role of species diversity on other aspects of the production system and N cycle, such as soil type and species adaptation, plant N uptake, and management of diverse pastures for successful on-farm implementation. [ABSTRACT FROM AUTHOR]

Nitrogen (N) dynamics in ley-arable cropping systems require better understanding in order to assess the potential of such systems to contribute to improved productivity and reduced nutrient losses in crop production. Large inputs of organic matter after termination of the ley phase result in increased mineralization and N availability to subsequent crops. The description and quantification of this residual N effect in ley-arable systems remains a major scientific challenge due to its variability and many influencing factors. Simulation modeling could contribute to improved understanding of N dynamics in ley-arable systems. The aim of this study was to evaluate the robustness of the Agricultural Production Systems Simulator (APSIM) to predict biomass yield, N yield, and N leaching of different forage maize systems in northwest Europe, while using two different approaches to predict the residual N effect. The evaluation was based on three field experiments covering plant phenology, biomass, N yield, and N leaching over several years. Model adjustments were necessary to describe mineralization of organic matter and release of N after ploughing of the grass leys. For this purpose, three scenarios were investigated by accounting for either (1) aboveground grass residues; (2) above- and belowground grass residues, both with the generic turnover approach in the model; or (3) N release depending on the carbon-to-N ratio of the residue compiled in a simple mineralization model (SMM). The results showed that APSIM-simulated biomass and N yield of maize were reasonable to poor across the different systems and sites, regardless of using the residue-related approach. The SMM performed more accurately compared to the generic turnover approach in predicting N leaching in a maize following a grass-clover ley. However, for all scenarios, APSIM had difficulties to predict a delay of N leaching observed in the experimental data after a pure ryegrass ley. In conclusion, the process description in APSIM related to organic matter mineralization in ley-arable systems under northwest European pedo-climatic conditions needs improved accounting of belowground grass residues, while the SMM is of added value to improve N mineralization patterns and leaching after a ley phase. [ABSTRACT FROM AUTHOR]

• A simple mineralisation model (SMM) based on first order decay and the C:N was tested. • SMM, linked with APSIM could predict N release from catch crop residues well. • The default approach in APSIM underpredicted N mineralisation from catch crops (CC). • APSIM with SMM potential tool for predicting effect of CC on N leaching and N supply. Determining the nitrogen (N) release from catch crop residues is important for N management in arable farming systems. The use of catch crops and subsequent incorporation of its residues represents a nutrient provision for the following crop and has the potential of reducing N leaching. To investigate whether the Agricultural Production Simulator (APSIM) can be used to predict the N release from Brassica catch crop residues with different carbon to nitrogen ratios (C:N) under different temperatures the model was set-up using three different approaches: (i) the generic approach, in which the residue is distributed to the various carbon pools with default APSIM parameters (Gen), (ii) the generic approach but with partitioning of the various pools based on the biochemical composition (Gen-BC), and (iii) the inclusion of an additional carbon pool in which mineralisation is based on first order decay and the C:N of the crop residue, termed simple mineralisation model (SMM). The SMM was parameterized based on results from various previous incubation studies. APSIM was then used to predict N release through mineralisation from these experiments. The simulations indicate that the generic approach in APSIM greatly underestimates the amount of N released from the cover crop residues, especially at low temperatures; the model efficiency (based on the Nash Sutcliffe efficiency score) was negative for the incubation study done at 2 °C. APSIM linked with the SMM shows a substantially higher prediction accuracy. The Gen-BC, which could only be done for one of the incubation experiments, had a higher prediction accuracy than the generic approach, but was not as good as the SMM. This indicates that, for accurate predictions of N mineralisation from Brassica catch crop residues, the generic approach with default partitioning needs to be modified, either by assigning various carbon pools based on the biochemical composition or by including an additional carbon pool. [ABSTRACT FROM AUTHOR]