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Agricultural Production Systems Simulator (APSIM)

Agricultural Production Systems Simulator (APSIM). Simulates: yield of crops, pastures, trees, weeds ... key soil processes (water, N, P, carbon, pH) surface residue dynamics & erosion range of management options crop rotations + fallowing + mixtures short or long term effects

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Agricultural Production Systems Simulator (APSIM)

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  1. Agricultural Production Systems Simulator (APSIM) Simulates: • yield of crops, pastures, trees, weeds ... • key soil processes (water, N, P, carbon, pH) • surface residue dynamics & erosion • range of management options • crop rotations + fallowing + mixtures • short or long term effects • one or two dimensions • high software engineering standards • BUT, not yet pests nor diseases

  2. APSIM - developmental goals • Production and profit • sought to retain yield prediction in relation to management options and environment (c/f - CERES, CROPGRO models) • Fate of the soil resource • sought valid long-term simulation of key soil processes (c/f - CENTURY, EPIC) • Impacts off-farm • predict loss of soil, water, nutrients off-site (c/f - EPIC)

  3. APSIM - some statistics • Development team • 7 programmers / model support staff • 12 scientist / modellers • User base • 180 licensed users • 9 countries, 4 continents • Product Suite • ca. 450,000 lines of code • 4 languages • 38 modules • 12 interfaces or major tools

  4. Crop/pasture/tree wheat sorghum sugarcane chickpea mungbean soybean barley groundnut maize sunflower hemp lucerne fababean canola lupin mucuna cowpea Pinus radiata Eucalyptus sp. cotton - CSIRO PI pearl millet - ICRISAT pigeonpea - ICRISAT Soil SoilWat SWIM SoilN SoilP SoilpH Solute Residue Manure - ICRISAT Developing our knowledge & capability - APSIM modules Management Sowing Tillage Irrigate Fertilize Intercrop/mixture competition

  5. Multiple user interfaces –e.g. APSFront interface

  6. APSIM has been used to simulate … Some examples

  7. …physiological processes Pigeonpea qualitative photoperiod response

  8. …plant organs Tiller leaf area in millet

  9. …crop growth & development Growth & development of pigeonpea

  10. …yield of experimental crops Mungbean Chickpea Cowpea 3000 5000 yields 1200 4500 1:1 line 2500 regression 4000 y = 1.0631x - 70.964 900 3500 2000 2 R = 0.7924 3000 Predicted Predicted 1500 600 2500 Predicted 2000 1000 1:1 line 1500 300 Grain (g/m2) y = 0.87x + 221.44 1000 500 Biomass (g/m2) 2 R = 0.77 500 0 0 0 0 300 600 900 1200 0.0 500.0 1000.0 1500.0 2000.0 2500.0 3000.0 0 1000 2000 3000 4000 5000 Observed Observed Observed Prediction n regression line R2 slope intercept wheat grain 43 1.07 -13.0 0.79 maize grain 111 0.98 ( 0.04) -5.5 ( 240) 0.85 chickpea grain 60 0.90 ( 0.07) 163 ( 172) 0.76 mungbean grain 47 1.07 ( 0.10) -27.2 ( 128) 0.72 cowpea grain 15 0.93 ( 0.08) -31.6 ( 34.6) 0.91 stylo biomass 63 0.84 ( 0.06) -131.7 ( 171) 0.78

  11. …yield of commercial crops • APSIM tested against data from commercial farms • Crops include cotton, sorghum, mungbean, wheat, chickpea

  12. … yield of smallholder crops Maize response to N in Malawi Maize response to N & manure in Kenya Maize response to N at Makoholi

  13. … N response in smallholder crops Testing simulation of maize response to N at Makoholi over 7 seasons 1991-1997

  14. … seasonal perspectives How representative were the seasons 91-98 at Makoholi?

  15. … yield of crops in rotation Lines = predicted Symbols = observed Wheat-Sorghum Long Fallow rotation

  16. … soil water of crops in rotation Wheat Sorgham Wheat-Sorghum Long Fallow rotation

  17. … ET of crops in rotation 93 Wheat, 94-97 Lucerne measured in lysimeter

  18. … legume rotation effects Maize response (TBM) to fertiliser N following pigeonpea, India

  19. … consequence of crop rotations $GM drainage wheat-wheat-mungbean-sorghum-chickpea rotation

  20. … soil organic matter changes Farming systems on a vertisol at Dalby, Qld.

  21. …crop-weed competition Maize – volunteer stylo

  22. …response to manure application High & low quality manure applied to maize

  23. … response to N, P fertilizer & manure Maize response to P rates in Kenya Response to N, P and manure, India

  24. … “on-farm” constraints Response to 36 kg N/ha

  25. … agroforestry systems Enabling landholder assessment of the productivity and risk of commercial agroforestry investment on grain farms in Australia’s medium to low rainfall regions

  26. … change in wheat production under climate change

  27. … but can you use such technical information with farmers?

  28. YES…but the information needs to be made relevant to farmers’ realities

  29. Source: Peter Carberry CSIRO, Australia Click the back button on your browser to return to the main menu

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