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Yield gap analysis of rainfed wheat demonstrates local to global relevance

  • D. L. GOBBETT (a1), Z. HOCHMAN (a2), H. HORAN (a2), J. NAVARRO GARCIA (a3), P. GRASSINI (a4) and K. G. CASSMAN (a4)...

Australia has a role to play in future global food security as it contributes 0·12 of global wheat exports. How much more can it contribute with current technology and varieties? The present paper seeks to quantify the gap between water-limited yield potential (Yw) and farmer yields (Ya) for wheat in Australia by implementing a new protocol developed by the Global Yield Gap and Water Productivity Atlas (GYGA) project. Results of past Australian yield gap studies are difficult to compare with studies in other countries because they were conducted using a variety of methods and at a range of scales. The GYGA project protocols were designed to facilitate comparisons among countries through the application of a consistent yet flexible methodology. This is the first implementation of GYGA protocols in a country with the high spatial and temporal climatic variability that exists in Australia.

The present paper describes the application of the GYGA protocol to the whole Australian grain zone to derive estimates of rainfed wheat yield gap. The Australian grain zone was partitioned into six key agro-climatic zones (CZs) defined by the GYGA Extrapolation Domain (GYGA-ED) zonation scheme. A total of 22 Reference Weather Stations (RWS) were selected, distributed among the CZs to represent the entire Australian grain zone. The Agricultural Production Systems sIMulator (APSIM) Wheat crop model was used to simulate Yw of wheat crops for major soil types at each RWS from 1996 to 2010. Wheat varieties, agronomy and distribution of wheat cropping were held constant over the 15-year period. Locally representative dominant soils were selected for each RWS and generic sowing rules were specified based on local expertise. Actual yield (Ya) data were sourced from national agricultural data sets. To upscale Ya and Yw values from RWS to CZs and then to national scale, values were weighted according to the area of winter cereal cropping within RWS buffer zones. The national yield gap (Yg = Yw–Ya) and relative yield (Y% = 100 × Ya/Yw) were then calculated from the weighted values.

The present study found that the national Yg was 2·0 tonnes (t)/ha and Y% was 47%. The analysis was extended to consider factors contributing to the yield gap. It was revealed that the RWS 15-year average Ya and Yw were strongly correlated (R 2 = 0·76) and that RWS with higher Yw had higher Yg. Despite variable seasonal conditions, Y% was relatively stable over the 15 years. For the 22 RWS, average Yg correlated positively and strongly with average annual rainfall amount, but surprisingly it correlated poorly with RWS rainfall variability. Similarly, Y% correlated negatively but less strongly (R 2 = 0·33) with RWS average annual rainfall, and correlated poorly with RWS rainfall variability, which raises questions about how Australian farmers manage climate risk. Interestingly a negative relationship was found between Yg and variability of Yw for the 22 RWS (R 2 = 0·66), and a positive relationship between Y% and Yw variability (R 2 = 0·23), which suggests that farmers in lower yielding, more variable sites are achieving yields closer to Yw. The Yg estimates appear to be quite robust in the context of estimates from other Australian studies, adding confidence to the validity of the GYGA protocol. Closing the national yield gap so that Ya is 0·80 of Yw, which is the level of Yg closure achieved consistently by the most progressive Australian farmers, would increase the average annual wheat production (20·9 million t in 1996/07 to 2010/11) by an estimated 15·3 million t, which is a 72% increase. This indicates substantial potential for Australia to increase wheat production on existing farmland areas using currently available crop varieties and farming practices and thus make a substantial contribution to achieving future global food security.

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ABARE-BRS (2010). Land Use of Australia, Version 4, 2005–06. Canberra, Australia: Australian Bureau of Agricultural and Resource Economics - Bureau of Rural Sciences (ABARE-BRS).
ABARES (2012). Agricultural Commodity Statistics 2012. Canberra, Australia: Australian Bureau of Agricultural and Resource Economics and Sciences.
ABARES (2015). Australian Agricultural and Grazing Industries Survey (AAGIS). Canberra, Australia: Australian Bureau of Agricultural and Resource Economics and Sciences.
ABS (2012). Agricultural Census: Value of Agricultural Commodities 2010–11. Canberra, Australia: Australian Bureau of Statistics.
ACLEP (2012). Australian Soil Classification (ESRI Grid). Australian Collaborative Land Evaluation Program (ACLEP) endorsed through the National Committee on Soil and Terrain (NCST). Canberra, Australia: ACLEP. Available from: (verified 8 March 2016).
Anderson W. K. (2010). Closing the gap between actual and potential yield of rainfed wheat. The impacts of environment, management and cultivar. Field Crops Research 116, 1422.
Barlow K. M., Christy B. P., O'Leary G. J., Riffkin P. A. & Nuttall J. G. (2015). Simulating the impact of extreme heat and frost events on wheat crop production: a review. Field Crops Research 171, 109119.
BoM (2009). The Australian Data Archive of Meteorology. Melbourne, Australia: Commonwealth of Australia, Bureau of Meteorology.
Brown H. E., Huth N. I., Holzworth D. P., Teixeira E. I., Zyskowski R. F., Hargreaves J. N. G. & Moot D. J. (2014). Plant modelling framework: software for building and running crop models on the APSIM platform. Environmental Modelling & Software 62, 385398.
Carberry P. S., Liang W. L., Twomlow S., Holzworth D. P., Dimes J. P., McClelland T., Huth N. I., Chen F., Hochman Z. & Keating B. A. (2013). Scope for improved eco-efficiency varies among diverse cropping systems. Proceedings of the National Academy of Sciences of the United States of America 110, 83818386.
Cornish P. S. & Murray G. M. (1989). Low rainfall rarely limits wheat yields in southern New South Wales. Australian Journal of Experimental Agriculture 29, 7783.
CSIRO (2015). Australian National Outlook 2015: Economic Activity, Resource Use, Environmental Performance and Living Standards, 1970–2050. Canberra, Australia: CSIRO.
Dalgliesh N. P., Foale M. A. & McCown R. L. (2009). Re-inventing model-based decision support with Australian dryland farmers. 2. Pragmatic provision of soil information for paddock-specific simulation and farmer decision making. Crop & Pasture Science 60, 10311043.
Edwards J., Umbers A. & Wentworth S. (2012). GRDC Farm Practices Survey 2012. Kingston, ACT: Grains Research & Development Corporation.
ESRI (2010). ArcGIS 10·0. Redlands, CA, USA: Environmental Systems Research Institute.
Feldman D., Thomas Q., Farre Codina I., Plunkett B. & Kingwell R. (2015). Is a low-input strategy a sound business defence in a drying climate? In 59th Australian Agricultural and Resource Economics Society Annual Conference. Rotorua, New Zealand: Copyright by authors. Available from: (verified 8 March 2016).
Fischer R. A., Byerlee D. & Edmeades G. O. (2014). Crop Yields and Global Food Security: Will Yield Increase Continue to Feed the World? ACIAR Monograph No. 158. Canberra, Australia: Australian Centre for International Agricultural Research.
Freebairn D. M., Wockner G. H., Lawrence D., Cawley S. & Hamilton A. N. (1998). A framework for extending principles of conservation cropping. In Proceedings of the 9th Australian Agronomy Conference (Eds Michalk D. L. & Pratley J. E.), pp. 89. Wagga Wagga, NSW, Australia: Australian Society of Agronomy.
Grassini P., Eskridge K. M. & Cassman K. G. (2013). Distinguishing between yield advances and yield plateaus in historical crop production trends. Nature Communications 4, article no. 2918.
Grassini P., van Bussel L. G. J., Van Wart J., Wolf J., Claessens L., Yang H., Boogaard H., de Groot H., van Ittersum M. K. & Cassman K. G. (2015). How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Research 177, 4963.
Hochman Z., Holzworth D. & Hunt J. R. (2009). Potential to improve on-farm wheat yield and WUE in Australia. Crop & Pasture Science 60, 708716.
Hochman Z., Gobbett D., Holzworth D., McClelland T., van Rees H., Marinoni O., Navarro Garcia J. & Horan H. (2012). Quantifying yield gaps in rainfed cropping systems: a case study of wheat in Australia. Field Crops Research 136, 8596.
Hochman Z., Prestwidge D. & Carberry P. S. (2014). Crop sequences in Australia's northern grain zone are less agronomically efficient than implied by the sum of their parts. Agricultural Systems 129, 124132.
Holzworth D. P., Huth N. I., deVoil P. G., Zurcher E. J., Herrmann N. I., McLean G., Chenu K., van Oosterom E. J., Snow V., Murphy C., Moore A. D., Brown H., Whish J. P. M., Verrall S., Fainges J., Bell L. W., Peake A. S., Poulton P. L., Hochman Z., Thorburn P. J., Gaydon D. S., Dalgliesh N. P., Rodriguez D., Cox H., Chapman S., Doherty A., Teixeira E., Sharp J., Cichota R., Vogeler I., Li F. Y., Wang E., Hammer G. L., Robertson M. J., Dimes J. P., Whitbread A. M., Hunt J., van Rees H., McClelland T., Carberry P. S., Hargreaves J. N. G., MacLeod N., McDonald C., Harsdorf J., Wedgwood S. & Keating B. A. (2014). APSIM – evolution towards a new generation of agricultural systems simulation. Environmental Modelling & Software 62, 327350.
Hunt J. R. & Kirkegaard J. A. (2011). Re-evaluating the contribution of summer fallow rain to wheat yield in southern Australia. Crop and Pasture Science 62, 915929.
Jeffrey S. J., Carter J. O., Moodie K. B. & Beswick A. R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environmental Modelling & Software 16, 309330.
Keating B. A., Carberry P. S., Hammer G. L., Probert M. E., Robertson M. J., Holzworth D., Huth N. I., Hargreaves J. N. G., Meinke H., Hochman Z., McLean G., Verburg K., Snow V., Dimes J. P., Silburn M., Wang E., Brown S., Bristow K. L., Asseng S., Chapman S., McCown R. L., Freebairn D. M. & Smith C. J. (2003). An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18, 267288.
Keating B. A., Herrero M., Carberry P. S., Gardner J. & Cole M. B. (2014). Food wedges: framing the global food demand and supply challenge towards 2050. Global Food Security 3, 125132.
Lobell D. B., Cassman K. G. & Field C. B. (2009). Crop yield gaps: their importance, magnitudes, and causes. Annual Review of Environment and Resources 34, 179204.
Monjardino M., McBeath T., Ouzman J., Llewellyn R. & Jones B. (2015). Farmer risk-aversion limits closure of yield and profit gaps: a study of nitrogen management in the southern Australian wheatbelt. Agricultural Systems 137, 108118.
Nidumolu U. B., Hayman P. T., Howden S. M. & Alexander B. M. (2012). Re-evaluating the margin of the South Australian grain belt in a changing climate. Climate Research 51, 249260.
Oliver Y. M. & Robertson M. J. (2013). Quantifying the spatial pattern of the yield gap within a farm in a low rainfall Mediterranean climate. Field Crops Research 150, 2941.
Oliver Y. M., Robertson M. J. & Weeks C. (2010). A new look at an old practice: benefits from soil water accumulation in long fallows under Mediterranean conditions. Agricultural Water Management 98, 291300.
Ray D. K., Ramankutty N., Mueller N. D., West P. C. & Foley J. A. (2012). Recent patterns of crop yield growth and stagnation. Nature Communications 3, article number 1293.
Ray D. K., Mueller N. D., West P. C. & Foley J. A. (2013). Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8, e66428.
Stephens D., Anderson W., Nunweek M., Potgieter A. & Walcott J. (2011). GRDC Strategic Planning for Investment Based on Agro-Ecological Zones - Second Phase. Perth, Australia: Department of Agriculture and Food Western Australia.
Tilman D., Balzer C., Hill J. & Befort B. L. (2011). Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences of the United States of America 108, 2026020264.
van Bussel L. G. J., Grassini P., Van Wart J., Wolf J., Claessens L., Yang H., Boogaard H., de Groot H., Saito K., Cassman K. G. & van Ittersum M. K. (2015). From field to atlas: upscaling of location-specific yield gap estimates. Field Crops Research 177, 98108.
van Herwaarden A. F., Farquhar G. D., Angus J. F., Richards R. A. & Howe G. N. (1998). ‘Haying-off’, the negative grain yield response of dryland wheat to nitrogen fertiliser: I. Biomass, grain yield, and water use. Australian Journal of Agricultural Research 49, 10671081.
van Ittersum M. K., Cassman K. G., Grassini P., Wolf J., Tittonell P. & Hochman Z. (2013). Yield gap analysis with local to global relevance – a review. Field Crops Research 143, 417.
van Rees H., McClelland T., Hochman Z., Carberry P., Hunt J., Huth N. & Holzworth D. (2014). Leading farmers in South East Australia have closed the exploitable wheat yield gap: prospects for further improvement. Field Crops Research 164, 111.
Van Wart J., Kersebaum K. C., Peng S., Milner M. & Cassman K. G. (2013 a). Estimating crop yield potential at regional to national scales. Field Crops Research 143, 3443.
Van Wart J., van Bussel L. G. J., Wolf J., Licker R., Grassini P., Nelson A., Boogaard H., Gerber J., Mueller N. D., Claessens L., van Ittersum M. K. & Cassman K. G. (2013 b). Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research 143, 4455.
Walcott J. J., Zuo H., Loch A. D. & Smart R. V. (2013). Patterns and trends in Australian agriculture: a consistent set of agricultural statistics at small areas for analysing regional changes. Journal of Land Use Science 9, 453473.
Whitbread A. M., Davoren C. W., Gupta V. V. S. R., Llewellyn R. & Roget D. (2015). Long-term cropping system studies support intensive and responsive cropping systems in the low-rainfall Australian Mallee. Crop and Pasture Science 66, 553565.
You L., Crespo S., Guo Z., Koo J., Sebastian K., Tenorio M. T., Wood S. & Wood-Sichra U. (2009). Spatial Production Allocation Model (SPAM) 2000 Version 3 Release 6. Washington, D.C.: MapSPAM. Available from: (verified 8 March 2015).
Zadoks J. C., Chang T. T. & Konzak C. F. (1974). A decimal code for the growth stages of cereals. Weed Research 14, 415421.
Zajaczkowski J., Wong K. & Carter J. (2013). Improved historical solar radiation gridded data for Australia. Environmental Modelling & Software 49, 6477.
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