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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]

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]

Studies evaluating the complexity of models, which are suitable to simulate grass growth at regional scales in intensive grassland production systems are scarce. Therefore, two different grass growth models (GrasProg1.0 and APSIM) with different complexity and input requirements were compared against long-term observations from variety trials with perennial ryegrass (Lolium perenne) in Germany and Denmark. The trial sites covered a large range of environmental conditions, with annual average temperatures ranging from 5.9 to 10.3 °C, and annual rainfall from 536 to 1154 mm. The sites also varied regarding soil type, which were for modelling categorised into three different groups according to their plant available water (PAW) content: light soils with a PAW of 60 mm, medium soils with a PAW of 80 mm, and heavy soils with a PAW of 100 mm. The objective was to investigate whether the simple model performed equally well with the given low number of inputs, namely climate and PAW group. Evaluation statistics showed that both models provided satisfactory results, with root mean square errors for individual cuts ranging from 0.59 to 1.28 t dry matter ha−1. The model efficiency (Nash–Sutcliffe efficiency) for the separate cuts were also good for both models, with 81% of the sites having a positive Nash–Sutcliffe efficiency value with GrasProg1.0, and 72% with APSIM. These results reveal that without detailed site-specific descriptions, the less complex GrasProg1.0 model can be incorporated into a simple decision support tool for optimising grassland management in intensive livestock production systems. [ABSTRACT FROM AUTHOR]

Knowledge about pasture growth rates is crucial for optimizing forage use efficiencies in intensively managed pasture and silage-based dairy systems, enabling optimized cutting/grazing times for high yields with high forage quality. The aim of this study was to parameterise a simple model, GrasProg, for predicting pasture growth in an intensively managed dairy production system under a cut-and-carry management. For this, pasture crop-growth rates were measured over a period of two years (2016 and 2017) at five contrasting sites in Schleswig-Holstein, Northern Germany. The pastures received nitrogen (N) fertilizer at a rate of 280 kg N ha−1 and were cut on a four-week interval. Average annual dry matter (DM) yields ranged from 10.9 to 11.6 t/ha for the three different locations. The DM accumulation simulated by GrasProg matched actual measurements over the varying intervals well (R2 = 0.65; RMSE = 49.5 g DM m−2; and NSE = 0.44). Two model parameters were adjusted within the vegetation period, namely, the relative growth rate, a proxy of the number of generative tillers, and the initial biomass at the start of each growth period, a proxy for the tillering density. Both predicted and measured pasture growth rates showed the same typical seasonal pattern, with high growth rates in spring, followed by decreasing growth rates to the end of the vegetation period. These good calibration statistics, with adjusting of only two model parameters, for the different sites and different climatic conditions mean that GrasProg can be used to identify optimum grazing or cutting strategies, with optimal yield and forage quality. [ABSTRACT FROM AUTHOR]

Keeping cover crops to reduce nitrogen leaching often conflicts with timing tillage operations before the soil becomes un-trafficable during winter, while leaving cover crops in the field until spring raises concerns over pre-emptive competition with the following crop. Therefore, farmers may resort to tilling their fields in autumn after letting cover crops remain in the fields for only a short period of time. We explore the effects of this practice in a laboratory lysimeter setting by analyzing the leaching of nitrate from intact topsoil cores. Cores were extracted from no-till (NT) plots and plots tilled in autumn (AuT), in areas kept bare (B) and with volunteer winter rye plant cover (V) after harvest. Nitrate breakthrough curves show that V significantly reduced N leaching by 61% relative to B in NT, but did not have a significant effect in AuT. Dissection of leached cores and undisturbed reference cores indicated a significant removal of mineral N from the soil during the lysimeter experiment for all treatments except V in NT. This indicates that volunteer cover removed a crucial amount of leachable N and suggests that tillage counteracted the effect of V in AuT, likely due to a combination of reduced uptake and re-mineralization of N in cover crop residue. [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]

Nitrous oxide (N2O) emissions from pastures can vary significantly depending on soil and environmental conditions, nitrogen (N) input, as well as the plant's ability to take up the N. We tested the hypothesis that legume-based N sources are characterized by significantly lower emission factors than mineral N based dairy systems. Therefore, this study monitored N2O emissions for a minimum of 100 days and up to two growing seasons across a gradient of plant species diversity. Emissions were measured from both grazed pastures and a controlled application of urine and dung using the static chamber method. About 90% of the simulated experiments' accumulated N2O emissions occurred during the first 60–75 days. The average accumulated N2O emissions were 0.11, 0.87, 0.99, and 0.21 kg ha−1 for control, dung, urine patches, and grazed pastures, respectively. The N uptake efficiency at the excreta patch scale was about 70% for both dung and urine. The highest N2O-N emission factor was less than half compared with the IPCC default (0.3 vs. 0.77), suggesting an overestimation of N2O-N emissions from organically managed pastures in temperate climates. Plant diversity showed no significant effect on N2O emission. However, functional groups were significant (p < 0.05). We concluded that legume-containing pasture systems without a fertilizer addition generally appear capable of utilizing nitrogen inputs from excreta patches efficiently, resulting in low N2O emissions. [ABSTRACT FROM AUTHOR]

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]