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The determination of optimum nitrogen (N) fertilisation rates, which maximise yields and minimise N losses, remains problematic due to unknown upcoming crop requirements and near-future supply by the soil. Remote sensing can be used for determining the crop N status and to assess the spatial variability within a field or between fields. This can be used to improve N fertilisation, provided that the optimal fertilisation rate at the time of fertiliser application for an expected yield is known. Using the APSIM-wheat model, we developed an algorithm that relates the N status of the plants at early development stages to the yield response to N. Simulations were performed for winter wheat under growth conditions in Denmark. To obtain a range of different N status in the biomass at early growth stages, the soil N in autumn was varied from 20 to 180 kg N ha−1, and at BBCH23, fertiliser was applied at a rate of 50 kg N ha−1. In a full factorial setup, additional N fertiliser was applied ranging from 0 to 150 kg N ha−1 during three different development stages (BBCH30, 32, and 37). The algorithm was evaluated by comparing model outputs with a standard N application of 50 kg N ha−1 at BBCH23 and 150 kg N ha−1 at BBCH30. The evaluation showed that, depending on the N status of the soil, the algorithm either provided higher or lower optimal N fertilisation rates when targeting 95% of the maximum yield, and these affected the grain yield and the grain N, as well as the amount of N leaching. Split application of fertiliser into three applications was generally beneficial, with decreased product-related N leaching of up to nearly 30%. Further testing of the model under different environmental conditions is needed before such an algorithm can be used to guide N fertilisation. [ABSTRACT FROM AUTHOR]

Abstract Catch crop (CC) mixtures of non-legumes (nL) and legumes (L) have been promoted as a strategy to achieve two different goals: to decrease the risk of nitrate leaching and to enhance the nitrogen supply to the subsequent crop. To investigate if two-component mixtures of nL + L have advantages over pure nL stands experiments were carried out over a two year period (2013–2015) at two contrasting field sites in Denmark. Nitrogen (N) uptake by the CCs was measured by aboveground biomass sampling, and N leaching by ceramic suction cups. When grown in pure stands, white clover (Trifolium repens) on coarse sand and common vetch (Vicia sativa) on sandy loam were less effective at reducing N leaching than perennial ryegrass (Lolium perenne) and fodder radish (Raphanus sativus). When the proportion of the nL + L in mixtures was similar or favored the nL, leaching was not significantly different from the nL in the pure stand. However, during one of the years on the sandy loam L (vetch) almost outperformed nL (fodder radish), resulting in N leaching from nL + L similar to L. The yield of the following spring barley was only significantly different from the yield in the plots with previously bare soil in one of the years on the coarse sandy soil. It is concluded that in nL + L mixtures L can take over and thereby lower the effect of the CCs on N leaching while not necessarily enhancing the N supply for the subsequent crop. Highlights • In monocultures legumes were less effective at reducing N leaching than non-legumes. • Non-legume/legume mixtures were as effective as non-legume catch crops in reducing N leaching. • When non-legume/legume mixtures are not balanced N leaching was similar to that from legumes. • Use a catch crop only increased the subsequent spring yield on the sandy loam in one of the years. • The catch crop had no effect on the yield of the subsequent crop on the clay soil. [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]

To determine the impact of potential reductions of terrain-targeted nitrogen (N) fertilisation rates on N losses a simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). To simulate N runoff a simple approach was used, in which runoff is based on the N concentration in the soil solution and an extraction coefficient. Firstly, APSIM parameters that have the largest effect on runoff of water and N were determined for terrains with different slopes for a poorly drained silt loam. A sensitivity analysis was then conducted to assess the effect of soil hydraulic properties and soil organic carbon content on runoff losses. Finally, APSIM was set up to simulate pasture production and water and N dynamics (including pasture N uptake, leaching and N runoff) for a farm on rolling hills in South Canterbury, New Zealand. Two different fertilisation approaches were used, either scheduled or based on the aboveground N concentration of the pasture. For the poorly drained silt loam, the rainfall intensity and the surface conductance had the highest effect on the amount of water lost by runoff. Soil hydraulic conductivity at saturation and field capacity, as well as plant available water content also controlled runoff of water and N, while the organic carbon content of the topsoil had less effect on N runoff. Both the extraction coefficient and the depth considered to exchange N with the runoff water affected the amount of N lost via runoff. Using the aboveground pasture N concentration prior to fertilisation had positive effects on pasture yield and reduced N runoff losses. • a simple approach was developed to include N runoff in APSIM. • the approach is based on the soil solution's N content and an extraction coefficient. • both the extraction coefficient and the depth considered influenced N runoff. • hydraulic conductivity and surface conductance highly affected water runoff. • Rainfall intensity should be considered sub-daily for simulating water runoff. [ABSTRACT FROM AUTHOR]

To investigate the potential use of diverse pasture swards to reduce nitrate leaching from intensive sheep and beef farms while maintaining economic viability, an integrated modelling assessment was conducted for the Canterbury region, New Zealand. The biophysical Agriculture Production Systems Simulator (APSIM) was used to obtain pasture growth curves for simple and diverse pastures over 10 different years, and the whole-farm system models FARMAX® and OVERSEER® were used to examine feed flow, nutrient balance, profitability, and nitrate leaching. The N leaching estimates obtained from OVERSEER® nutrient budget model ( Overseer ) were compared to estimates from APSIM. Five farm scenarios were explored, including three different proportions of the flat farm area under simple and diverse pastures (100% simple, 100% diverse, 50/50), two different stocking policies (without and with adjustment of livestock numbers), and three different years (an average, a best and a worst year, based on annual pasture yields). In the average year pasture growth was similar for the simple and diverse pasture swards, with annual pasture yields of 8.98 and 9.23 t DM/ha. The simple pasture had slightly higher growth in winter due to lower sensitivity to cold temperatures, whereas the diverse pasture showed higher growth during summer, which is frequently prone to water limitations. However, in the best year modelled pasture growth as well as profit were higher for the simple compared with the diverse pasture sward. Pasture N concentrations ranged from 2.5 to 3.5% of dry matter (DM) in the simple pasture, and from 2.2 to 3.1% in the diverse pasture sward, mainly due to a lower proportion of legumes. For the average year, having a diverse pasture on 50% of the farm area without changing the stocking policy of the farm, increased farm profit by 16%, due to the sale of surplus pasture. The total farm N leaching values predicted by APSIM, based on excretal N amounts obtained from Overseer , showed that the use of diverse pastures on 100% of the flat area decreased N leaching in an average year by 35%. In the worst year however, N leaching under the diverse pasture was slightly higher, and in the best year it decreased by 14% compared with the simple pasture. Corresponding reductions in N leaching estimated from Overseer were 6, 5 and 13% for the diverse pasture, primarily due to the lower N concentration of the diverse pasture. In contrast to APSIM, Overseer does not take into account the higher uptake of N of diverse pastures from the urine patches compared to simple pastures, which is mainly due to increased pasture growth in summer of the species included in the diverse pasture. This potential of diverse pastures to decrease N leaching needs to be evaluated via experimental studies, which should also include other aspects such as pasture persistence, and address the need for accurate model parameterisation. The modelling work also provided guidance for model refinement. [ABSTRACT FROM AUTHOR]

Abstract: Nitrogen leaching from urine patches has been identified as a major source of nitrogen loss under intensive grazing dairy farming. Leaching is notoriously variable, influenced by management, soil type, year-to-year variation in climate and timing and rate of urine depositions. To identify early indicators for the risk of N leaching from urine patches for potential usage in a precision management system, we used the simulation model APSIM (Agricultural Production Systems SIMulator) to produce an extensive N leaching dataset for the Waikato region of New Zealand. In total, nearly forty thousand simulation runs with different combinations of soil type and urine deposition times, in 33 different years, were done. The risk forecasting indicators were chosen based on their practicality: being readily measured on farm (soil water content, temperature and pasture growth) or that could be centrally supplied to farms (such as actual and forecast weather data). The thresholds of the early indicators that are used to forecast a period for high risk of N leaching were determined via classification and regression tree analysis. The most informative factors were soil temperature, pasture dry matter production, and average soil water content in the top soil over the two weeks prior to the urine N application event. Rainfall and air temperature for the two weeks following urine deposition were also important to fine-tune the predictions. The identified early indicators were then tested for their potential to predict the risk of N leaching in two typical soils from the Waikato region in New Zealand. The accuracy of the predictions varied with the number of indicators, the soil type and the risk level, and the number of correct predictions ranged from about 45 to over 90%. Further expansion and fine-tuning of the indicators and the development of a practical N risk tool based on these indicators is needed. [Copyright &y& Elsevier]

For arable stockless farming systems, the integration of catch crops (CC) during the fallow period might be a key for closing the nitrogen (N) cycle, reducing N leaching and increasing the transfer of N to the subsequent crop. However, despite considerable research efforts, the fate of N in such integrated systems remains unclear. To address this, a two-year field experiment was carried out in northern Germany with different CC, including frost-tolerant and frost-killed CC. The experiment started following a two-year ryegrass/red clover ley, which was subsequently sown with a cereal (CE) or a grain legume (field pea, PE). This provided two contrasting systems with high residual N in autumn. The results showed high N uptake of the CC, ranging from 84 to 136 kg N ha−1 with PE as the pre-crop, and from 33 to 110 kg N ha−1 with CE. All CC reduced N leaching compared with the control, a bare fallow over autumn/winter. Of the various CC, the frost-killed CC showed higher leaching compared with the other CCs, indicating mineralisation of the CC residue in the later autumn/winter period. The process based APSIM (Agricultural Production SIMulator) model was used to simulate N cycling for a cereal grain legume rotation, including a frost-killed and a frost resistant CC. While the model simulated the biomass and the N uptake by the crops, as well as the reduction of N leaching with the use of CC well, it under-estimated N leaching from the frost-killed CC. The study showed that all CC were affective at reducing N leaching, but winter hard catch crops should be preferred, as there is a risk of increased leaching following the mineralisation of residues from frost-killed CC. [ABSTRACT FROM AUTHOR]