Crop Updates 2009 - Farming Systems

This session covers nineteen papers from different authors: Decision support technology 1. The use of high resolution imagery in broad acre cropping, Derk Bakker and Grey Poulish, Department of Agriculture and Food 2. Spraywise decisions – online spray applicatiors planning tool, Steve Lacy, Nufarm Australia Ltd 3. Testing for redlegged earthmite resistance in Western Australia, Svetlana Micic, Peter Mangano, Tony Dore and Alan Lord, Department of Agriculture and Food 4. Screening cereal, canola and pasture cultivars for Root Lesion Nematode (Pratylenchus neglectus), Vivien Vanstone, Helen Hunter and Sean Kelly,Department of Agriculture and Food Farming Systems Research 5. Lessons from five years of cropping systems research, WK Anderson, Department of Agriculture and Food 6. Facey Group rotations for profit: Five years on and where to next? Gary Lang and David McCarthy, Facey Group, Wickepin, WA Mixed Farming 7. Saline groundwater use by Lucerne and its biomass production in relation to groundwater salinity, Ruhi Ferdowsian, Ian Roseand Andrew Van Burgel, Department of Agriculture and Food 8. Autumn cleaning yellow serradella pastures with broad spectrum herbicides – a novel weed control strategy that exploits delayed germination, Dr David Ferris, Department of Agriculture and Food 9. Decimating weed seed banks within non-crop phases for the benefit of subsequent crops, Dr David Ferris, Department of Agriculture and Food 10. Making seasonal variability easier to deal with in a mixed farming enterprise! Rob Grima,Department of Agriculture and Food 11. How widely have new annual legume pastures been adopted in the low to medium rainfall zones of Western Australia? Natalie Hogg, Department of Agriculture and Food, John Davis, Institute for Sustainability and Technology Policy, Murdoch University 12. Economic evaluation of dual purpose cereal in the Central wheatbelt of Western Australia, Jarrad Martin, Pippa Michael and Robert Belford, School of Agriculture and Environment, CurtinUniversity of Technology, Muresk Campus 13. A system for improving the fit of annual pasture legumes under Western Australian farming systems, Kawsar P Salam1,2, Roy Murray-Prior1, David Bowran2and Moin U. Salam2, 1Curtin University of Technology; 2Department of Agriculture and Food 14. Perception versus reality: why we should measure our pasture, Tim Scanlon, Department of Agriculture and Food, Len Wade, Charles Sturt University, Megan Ryan, University of Western Australia Modelling 15. Potential impact of climate changes on the profitability of cropping systems in the medium and high rainfall areas of the northern wheatbelt, Megan Abrahams, Chad Reynolds, Caroline Peek, Dennis van Gool, Kari-Lee Falconer and Daniel Gardiner, Department of Agriculture and Food 16. Prediction of wheat grain yield using Yield Prophet®, Geoff Anderson and Siva Sivapalan, Department of Agriculture and Food 17. Using Yield Prophet® to determine the likely impacts of climate change on wheat production, Tim McClelland1, James Hunt1, Zvi Hochman2, Bill Long3, Dean Holzworth4, Anthony Whitbread5, Stephen van Rees1and Peter DeVoil6 1 Birchip Cropping Group, Birchip, Vic, 2Agricultural Production Systems Research Unit (APSRU), CSIRO Sustainable Ecosystems, Climate Adaptation Flagship, Qld, 3 AgConsulting, SA 4 Agricultural Production Systems Research Unit (APSRU), CSIRO Sustainable Ecosystems, Toowoomba Qld, 5 CSIRO Sustainable Ecosystems, SA, 6 Agricultural Production Systems Research Unit (APSRU), Department of Agriculture and Fisheries, Queensland 18. Simple methods to predict yield potential: Improvements to the French and Schultz formula to account for soil type and within-season rainfall, Yvette Oliver, Michael Robertson and Peter Stone, CSIRO Sustainable Ecosystems 19. Ability of various yield forecasting models to estimate soil water at the start of the growing season, Siva Sivapalan, Kari-Lee Falconer and Geoff Anderson, Department of Agriculture and Foo

Crop Updates 2006 - Cereals

This session covers twenty nine papers from different authors: PLENARY 1. The 2005 wheat streak mosaic virus epidemic in New South Wales and the threat posed to the Western Australian wheat industry, Roger Jones and Nichole Burges, Department of Agriculture SOUTH COAST AGRONOMY 2. South coast wheat variety trial results and best options for 2006, Mohammad Amjad, Ben Curtis and Wal Anderson, Department of Agriculture 3. Dual purpose winter wheats to improve productivity, Mohammad Amjad and Ben Curtis, Department of Agriculture 4. South coast large-scale premium wheat variety trials, Mohammad Amjad and Ben Curtis, Department of Agriculture 5. Optimal input packages for noodle wheat in Dalwallinu – Liebe practice for profit trial, Darren Chitty, Agritech Crop Research and Brianna Peake, Liebe Group 6. In-crop risk management using yield prophet®, Harm van Rees1, Cherie Reilly1, James Hunt1, Dean Holzworth2, Zvi Hochman2; 1Birchip Cropping Group, Victoria; 2CSIRO, Toowoomba, Qld 7. Yield Prophet® 2005 – On-line yield forecasting, James Hunt1, Harm van Rees1, Zvi Hochman2,Allan Peake2, Neal Dalgliesh2, Dean Holzworth2, Stephen van Rees1, Trudy McCann1 and Peter Carberry2; 1Birchip Cropping Group, Victoria; 2CSIRO, Toowoomba, Qld 8. Performance of oaten hay varieties in Western Australian environments, Raj Malik and Kellie Winfield, Department of Agriculture 9. Performance of dwarf potential milling varieties in Western Australian environments, Kellie Winfield and Raj Malik, Department of Agriculture 10. Agronomic responses of new wheat varieties in the Southern agricultural region of WA, Brenda Shackley and Judith Devenish, Department of Agriculture 11. Responses of new wheat varieties to management factors in the central agricultural region of Western Australia, Darshan Sharma, Steve Penny and Wal Anderson,Department of Agriculture 12. Sowing time on wheat yield, quality and $ - Northern agricultural region, Christine Zaicou-Kunesch, Department of Agriculture NUTRITION 13.The most effective method of applying phosphorus, copper and zinc to no-till crops, Mike Bolland and Ross Brennan, Department of Agriculture 14. Uptake of K from the soil profile by wheat, Paul Damon and Zed Rengel, Faculty of Natural and Agricultural Sciences, University of Western Australia 15. Reducing nitrogen fertiliser risks, Jeremy Lemon, Department of Agriculture 16. Yield Prophet® and canopy management, Harm van Rees1, Zvi Hochman2, Perry Poulton2, Nick Poole3, Brooke Thompson4, James Hunt1; 1Birchip Cropping Group, Victoria; 2CSIRO, Toowoomba, Qld; 3Foundation for Arable Research, New Zealand; 4Cropfacts, Victoria 17. Producing profits with phosphorus, Stephen Loss, CSBP Ltd, WA 18. Potassium response in cereal cropping within the medium rainfall central wheatbelt, Jeff Russell1, Angie Roe2 and James Eyres2, Department of Agriculture1, Farm Focus Consultants, Northam2 19. Matching nitrogen supply to wheat demand in the high rainfall cropping zone, Narelle Simpson, Ron McTaggart, Wal Anderson, Lionel Martin and Dave Allen, Department of Agriculture DISEASES 20. Comparative study of commercial wheat cultivars and differential lines (with known Pm resistance genes) to powdery mildew response, Hossein Golzar, Manisha Shankar and Robert Loughman, Department of Agriculture 21. On farm research to investigate fungicide applications to minimise leaf disease impacts in wheat – part II, Jeff Russell1, Angie Roe2and James Eyres2, Department of Agriculture1, and Farm Focus Consultants, Northam2 22. Disease resistance update for wheat varieties in WA, Manisha Shankar, John Majewski, Donna Foster, Hossein Golzar, Jamie Piotrowski, Nicole Harry and Rob Loughman, Department of Agriculture 23. Effect of time of stripe rust inoculum arrival on variety response in wheat, Manisha Shankar, John Majewski and Rob Loughman, Department of Agriculture 24. Fungicide seed dressing management of loose smut in Baudin barley, Geoff Thomas and Kith Jayasena, Department of Agriculture PESTS 25. How to avoid insect contamination in cereal grain at harvest, Svetlana Micic, Paul Matson and Tony Dore, Department of Agriculture ABIOTIC 26. Environment – is it as important as variety in sprouting tolerance? Thomas (Ben) Biddulph1, Dr Daryl Mares1, Dr Julie Plummer1 and Dr Tim Setter2, School of Plant Biology, University of Western Australia1 and Department of Agriculture2 27. Frost or fiction, Garren Knell, Steve Curtin and Wade Longmuir, ConsultAg Pty Ltd, WA 28. High moisture wheat harvesting in Esperance 2005, Nigel Metz, South East Premium Wheat Growers Association (SEPWA) Projects Coordinator, Esperance, WA SOILS 28. Hardpan penetration ability of wheat roots, Tina Botwright Acuña and Len Wade, School of Plant Biology, University of Western Australia MARKETS 29. Crop shaping to meet predicted market demands for wheat in the 21st Century, Cindy Mills and Peter Stone,Australian Wheat Board, Melbourn

Location-specific vs location-agnostic machine learning metamodels for predicting pasture nitrogen response rate

In this work we compare the performance of a location-specific and a location-agnostic machine learning metamodel for crop nitrogen response rate prediction. We conduct a case study for grass-only pasture in several locations in New Zealand. We generate a large dataset of APSIM simulation outputs and train machine learning models based on that data. Initially, we examine how the models perform at the location where the location-specific model was trained. We then perform the Mann–Whitney U test to see if the difference in the predictions of the two models (i.e. location-specific and location-agnostic) is significant. We expand this procedure to other locations to investigate the generalization capability of the models. We find that there is no statistically significant difference in the predictions of the two models. This is both interesting and useful because the location-agnostic model generalizes better than the location-specific model which means that it can be applied to virgin sites with similar confidence to experienced sites

Agricultural Model Exchange Initiative (AMEI)

International audienc

Reprint of “Quantifying yield gaps in rainfed cropping systems: A case study of wheat in Australia”

AbstractTo feed a growing world population in the coming decades, agriculture must strive to reduce the gap between the yields that are currently achieved by farmers (Ya) and those potentially attainable in rainfed farming systems (Yw). The first step towards reducing yield gaps (Yg) is to obtain realistic estimates of their magnitude and their spatial and temporal variability. In this paper we describe a new yield gap assessment framework. The framework uses statistical yield and cropping area data, remotely sensed data, cropping system simulation and GIS mapping to calculate wheat yield gaps at scales from 1.1km cells to regional. The framework includes ad hoc on-ground testing of the calculated yield gaps. This framework was applied to wheat in the Wimmera region of Victoria, Australia. Estimated Yg over the whole Wimmera region varied annually from 0.63 to 4.12Mgha−1with an average of 2.00Mgha−1. Expressed as a relative yield (Y%) the range was 26.3–77.9% with an average of 52.7%. Similarly large spatial variability was described in a Wimmera yield gap map. Such maps can be used to show where efforts to bridge the yield gap are likely to have the biggest impacts. Bridging the exploitable yield gap in the Wimmera region by increasing average Y% to 80% would increase average annual wheat production from 1.09Mtonnes to 1.65Mtonnes. Model estimates of Yw and Yg were compared with data from crop yield contests, experimental variety trials, and on-farm water use and yields. These alternative approaches agreed well with the modelling results, indicating that the proposed framework provided a robust and widely applicable method of determining yield gaps. Its successful implementation requires that: (1) Ya as well as the area and geospatial distribution of wheat cropping are well defined; (2) there is a crop model with proven performance in the local agro-ecological zone; (3) daily weather and soil data (such as PAWC) required by crop models are available throughout the area; and (4) local agronomic best practice is well defined

The development of a farming systems model (APSIM) - A disciplined approach

The Agricultural Production Systems Simulator (APSIM) is a mature and stable modelling framework used widely in Australia and elsewhere in the domain of farming systems research and extension. It is capable of simulating a diverse range of farming systems including broadacre dryland and irrigated cropping, small holder farming and on-farm agroforestry systems. This includes the interaction of trees and crops and, through collaboration with other groups, integrated stock and cropping enterprises. APSIM was developed primarily as a research tool to investigate on-farm management practices especially where outcomes are affected by variable climatic conditions. Its use has been extended to looking at modifying farm practices and to include analysis of natural resource management issues including salinity and solute movement, climate risk studies, and climate change scenarios to name but a few. In recent times commercialisation activities have increased to broaden the user base by taking the utility of APSIM directly to consultants and farmers and tailoring it to their needs. This paper details APSIM's evolution over the past 15 years including its conception, specification, construction, performance and use. APSIM's development was very much a collaborative effort between multiple organisations and it has been driven by both user needs and scientific advances in crop and soil science, while the implementation of these advances in modelling was carried out by professional programmers and software engineers to assure best practice and quality control. APSIM's development is on-going. Here, we chronicle the development effort to date and detail some of the lessons learnt along the way