Beyond the plot: technology extrapolation domains for scaling out agronomic science

Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland.Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate ‘technology extrapolation domains’ based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment

Quantifying the economic impact of soil constraints on Australian agriculture: a case study of wheat

Soil sodicity, acidity, and salinity are important soil constraints to wheat production in many cropping regions across Australia, and the Australian agricultural industry needs accurate information on their economic impacts to guide investment decisions on remediation and minimize productivity losses. We present a modelling framework that maps the effects of soil constraints on wheat yield, quantifying forfeited wheat yields due to specific soil constraints at a broad spatial scale and assessing the economic benefit of managing these constraints. Of the three soil constraints considered (sodicity, acidity, and salinity), sodicity caused the largest magnitude of yield gaps across most of the wheat-cropping areas of Australia, with an average yield gap of 0.13\ua0t hayr. Yield gaps due to acidity were more concentrated spatially in the high-rainfall regions of Western Australia, Victoria, and New South Wales, and averaged 0.04\ua0t hayr across the wheat-cropping areas of Australia, whereas the yield gap due to salinity was estimated to be 0.02\ua0t hayr. The lost opportunity associated with soil sodicity for wheat production was estimated to be worth A$1,300 million per annum, for soil acidity, A$400 million per annum, and for salinity, A$200 million per annum. The results of this work should prove useful to guide national investment decisions on the allocation of resources and to target areas where more detailed information would be required in order to reduce the yield gap associated with soil constraints on wheat yields in Australia

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

Evidence for increasing global wheat yield potential

Wheat is the most widely grown food crop, with 761 Mt produced globally in 2020. To meet the expected grain demand by mid-century, wheat breeding strategies must continue to improve upon yield-advancing physiological traits, regardless of climate change impacts. Here, the best performing doubled haploid (DH) crosses with an increased canopy photosynthesis from wheat field experiments in the literature were extrapolated to the global scale with a multi-model ensemble of process-based wheat crop models to estimate global wheat production. The DH field experiments were also used to determine a quantitative relationship between wheat production and solar radiation to estimate genetic yield potential. The multi-model ensemble projected a global annual wheat production of 1050 +/- 145 Mt due to the improved canopy photosynthesis, a 37% increase, without expanding cropping area. Achieving this genetic yield potential would meet the lower estimate of the projected grain demand in 2050, albeit with considerable challenges

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

The chaos in calibrating crop models

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of system models and has an important impact on simulated values. Here we propose and illustrate a novel method of developing guidelines for calibration of system models. Our example is calibration of the phenology component of crop models. The approach is based on a multi-model study, where all teams are provided with the same data and asked to return simulations for the same conditions. All teams are asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.HighlightsWe propose a new approach to deriving calibration recommendations for system modelsApproach is based on analyzing calibration in multi-model simulation exercisesResulting recommendations are holistic and anchored in actual practiceWe apply the approach to calibration of crop models used to simulate phenologyRecommendations concern: objective function, parameters to estimate, software usedCompeting Interest StatementThe authors have declared no competing interest

Participative research on use of enhanced climate variability information within agribusiness

Climate variability impacts significantly on the agricultural service sector, affecting the operations and policies of agribusiness suppliers, banking and insurance companies. For example, bank lending policy and agribusiness advice was likely affected by recent El Niño drought events. Through consultation with agribusiness suppliers, banks and insurance companies, it is clear that their business operations and policies could benefit substantially from access to enhanced processes for dealing with climate variability. The Agricultural Production Systems Research Unit (APSRU) has demonstrated that farmers can utilise information derived from climate forecasts and simulation models in interpreting past experience, planning and decision making. Variability in production also poses challenges for both input suppliers and firms involved in the value chain from farm to consumer. Bank lending policies, crop insurance policies, product inventories and marketing advice may all be positively influenced through better dealing with climate variability. For example, insurance policies based on the Agricultural Production Systems Simulator (APSIM) model’s objective prediction of yields may potentially reduce claimant disputes and cut legal costs, representing significant savings to industry. Likewise, better prediction of seasonal outlooks using the APSIM model, climate forecasts and fallow water reserves would allow farmers and lenders, such as produce suppliers and banks, to negotiate individually-tailored financial packages. APSRU has recently extended risk management tools developed primarily for farmers to agribusiness to determine whether better targeted and costeffective agribusiness services can be provided for the benefit of agribusiness organisations and Australian farmers. In this paper we report on our experiences and learnings from our action research approach, where APSRU researchers are working alongside agribusiness staff on relevant case studies to identify the opportunities for and to resolve constraints against implementation of improved agribusiness operations based on climate forecasts and use of the APSIM model. Our collaborators represent a mix of agribusiness organisations, including input suppliers, marketers, banks and insurance companies. The case studies involving our collaborators are described and discussed in the paper, along with results of our initial evaluation. The use of climate forecasts and APSIM has generated interest amongst the agribusiness sector. While the costs of conducting this research are high, we conclude that there are good opportunities for these tools to assist agribusiness operations in providing better services to Australian farmers

Yield gap analysis with local to global relevance—A review

Yields of crops must increase substantially over the coming decades to keep pace with global food demand driven by population and income growth. Ultimately global food production capacity will be limited by the amount of land and water resources available and suitable for crop production, and by biophysical limits on crop growth. Quantifying food production capacity on every hectare of current farmland in a consistent and transparent manner is needed to inform decisions on policy, research, development and investment that aim to affect future crop yield and land use, and to inform on-ground action by local farmers through their knowledge networks. Crop production capacity can be evaluated by estimating potential yield and water-limited yield levels as benchmarks for crop production under, respectively, irrigated and rainfed conditions. The differences between these theoretical yield levels and actual farmers’ yields define the yield gaps, and precise spatially explicit knowledge about these yield gaps is essential to guide sustainable intensification of agriculture. This paper reviews methods to estimate yield gaps, with a focus on the local-to-global relevance of outcomes. Empirical methods estimate yield potential from 90 to 95th percentiles of farmers’ yields, maximum yields from experiment stations, growers’ yield contests or boundary functions; these are compared with crop simulation of potential or water-limited yields. Comparisons utilize detailed data sets from western Kenya, Nebraska (USA) and Victoria (Australia). We then review global studies, often performed by non-agricultural scientists, aimed at yield and sometimes yield gap assessment and compare several studies in terms of outcomes for regions in Nebraska, Kenya and The Netherlands. Based on our review we recommend key components for a yield gap assessment that can be applied at local to global scales. Given lack of data for some regions, the protocol recommends use of a tiered approach with preferred use of crop growth simulation models applied to relatively homogenous climate zones for which measured weather data are available. Within such zones simulations are performed for the dominant soils and cropping systems considering current spatial distribution of crops. Need for accurate agronomic and current yield data together with calibrated and validated crop models and upscaling methods is emphasized. The bottom-up application of this global protocol allows verification of estimated yield gaps with on-farm data and experiments