Performance of a fertiliser management algorithm to balance yield and nitrogen losses in dairy systems

Cichota, Rogerio; Vogeler, Iris; Werner, A.; Wigley, Kathryn; Paton, B. A.

doi:10.1016/j.agsy.2018.01.017

Cited by 15 publications

(9 citation statements)

References 47 publications

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“…There is scope, however, to reduce costs by applying simulation modelling with precision technology (e.g. remote sensing to help map variable rate fertiliser‐N applications) 12,48–50 …”

Section: Discussionmentioning

confidence: 99%

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Simulation of management strategies to mitigate nitrogen losses from crop rotations in Southland, New Zealand

2021

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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

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“…There is scope, however, to reduce costs by applying simulation modelling with precision technology (e.g. remote sensing to help map variable rate fertiliser‐N applications) 12,48–50 …”

Section: Discussionmentioning

confidence: 99%

“…The model allows continuous simulation of changes in soil N and water status in response to weather, management and crop uptake 9 . APSIM has successfully been applied in the assessment of environmental impacts of agricultural activities, as well as to guide N‐fertiliser application based on plant N status and remote sensing 10–12 …”

Section: Introductionmentioning

confidence: 99%

Simulation of management strategies to mitigate nitrogen losses from crop rotations in Southland, New Zealand

2021

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“…This also implies that it can be used everywhere in the world, including in small-scale farming systems of Africa, as long as it is validated for local conditions and crops. The development of the APSIM model was firstly focused on the estimation of crop yield as influenced by the availability of water and nitrogen 53 , but it expanded to include other agricultural systems and environmental processes 54 – 56 . The suite of modules that contains the APSIM software framework enable the simulation of farming systems for a diverse range of plant 57 , crop types 58 , cropping systems rotations 59 , management 60 , soil water 61 , soil organic carbon 62 , soil nutrients 63 , animals 64 , trees 65 , climate 42 , 66 and Genotype * Environment * Management interactions 67 .…”

Section: Methodsmentioning

confidence: 99%

Wheat (Triticum aestivum) adaptability evaluation in a semi-arid region of Central Morocco using APSIM model

Briak

Kebede

2021

Sci Rep

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In this study, we evaluated the suitability of semi-arid region of Central Morocco for wheat production using Agricultural Production Systems sIMulator (APSIM) considering weather, soil properties and crop management production factors. Model calibration was carried out using data collected from field trials. A quantitative statistics, i.e., root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and index of agreement (d) were used in model performance evaluation. Furthermore, series of simulations were performed to simulate the future scenarios of wheat productivity based on climate projection; the optimum sowing date under water deficit condition and selection of appropriate wheat varieties. The study showed that the performance of the model was fairly accurate as judged by having RMSE = 0.13, NSE = 0.95, and d = 0.98. The realization of future climate data projection and their integration into the APSIM model allowed us to obtain future scenarios of wheat yield that vary between 0 and 2.33 t/ha throughout the study period. The simulated result confirmed that the yield obtained from plots seeded between 25 October and 25 November was higher than that of sown until 05 January. From the several varieties tested, Hartog, Sunstate, Wollaroi, Batten and Sapphire were yielded comparatively higher than the locale variety Marzak. In conclusion, APSIM-Wheat model could be used as a promising tool to identify the best management practices such as determining the sowing date and selection of crop variety based on the length of the crop cycle for adapting and mitigating climate change.

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“…However, to understand the results obtained with the pastures, it is necessary to understand the effect of meteorological conditions and soil fertility on the development of the plants (CICHOTA et al, 2018;PEDREIRA et al, 2011;XU et al, 2012). It is necessary to know the basal growth temperature Production of annual ryegrass with different doses of nitrogen fertilization in topdressing of the species in order to manage it physiologically and according to the environmental conditions (MORENO et al, 2014;MÜLLER et al, 2009;ZAKA et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Production of annual ryegrass with different doses of nitrogen fertilization in topdressing

Bolke

Haygert-Velho

Timm

et al. 2019

SCA

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The objective of this study was to assess the growth of annual ryegrass (Lolium multiflorum) cv. BRS Ponteio with different doses of nitrogen applied in the pasture, thereby adjusting their growth to the exponential growth model. A randomized block design was used with five nitrogen application rates (0, 150, 250, 350, and 450 kg N ha-1) and four replicates, applied in installments. Each plot measured 9 m2. On April 15, 2014, 25 kg ha-1 of viable pure seeds of annual ryegrass were sown at a depth of 0.02 m, in 18 rows spaced at 0.17 m in each plot. Growth in the control treatment (zero nitrogen) pasture lasted 167 days with only three cuts, whereas in pastures treated with 350 and 450 kg N ha-1, growth was extended for an additional 45 days with a 333% increase in the number of cuts. The pastures were used for the same duration (188 days) in the treatments with 150 and 250 kg N ha-1, however, increased nitrogen resulted in two additional cuts and a shorter time interval between cuts. The time interval between each cut and the degree-days interacted dynamically causing distinct growth. Growth of the annual ryegrass BRS Ponteio without nitrogen application is poor and cannot be represented even by a first order linear model. The application of nitrogen topdressing, in the form of urea, decreases the time interval between cuts, increases the dry matter production per hectare, stimulates this production, and follows the exponential growth model.

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Performance of a fertiliser management algorithm to balance yield and nitrogen losses in dairy systems

Cited by 15 publications

References 47 publications

Simulation of management strategies to mitigate nitrogen losses from crop rotations in Southland, New Zealand

Simulation of management strategies to mitigate nitrogen losses from crop rotations in Southland, New Zealand

Wheat (Triticum aestivum) adaptability evaluation in a semi-arid region of Central Morocco using APSIM model

Production of annual ryegrass with different doses of nitrogen fertilization in topdressing

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