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Highlights • Insufficient N accounts for a 40% loss in wheat yields in Australia. • Tillage; time of sowing; summer fallow weeds; and low seedling density also limit yields. • Frost and heat stress account for losses of 16%–26% relative to water-limited yield potential. • Multiple limiting factors interact differently in different seasons and environments. • Emerging management practices can boost the yield frontier by 30%. Abstract Closing the yield gap is essential for global food security and for farmers who face increasing costs of production. Recent work showed that Australia's wheat growers are achieving about half their water-limited yield. While quantifying the yield gap is a necessary first step towards closing them, the next step is to understand which factors constrain rainfed grain growers from achieving their water-limited yields. Here we conducted in silico experiments over 15 years at 50 weather stations to ascertain the impact on grain yield of suboptimal practices against the 'best management practice' rules that were used to calculate the benchmark water-limited yields. Average national losses per suboptimal practice were: the average N fertiliser application rate – 40%; conventional tillage – 33%; suboptimal weed control during the summer fallow – 26%; low seedling density – 12%; and a two week delay in sowing – 7%. Combining two suboptimal practices does not necessarily lead to an additive effect on yield. Other factors that contribute to the yield gap include biotic stresses such as plant diseases, insects and other pests, in-crop weeds and extreme weather events (e.g. floods, strong winds and hail). In addition to calculating the impact of causes of the yield gap we investigated the opportunity to lift the water-limited yield by adopting an emergent new management practice of sowing on an optimised site specific date that is earlier than the traditional sowing window as described for the currently accepted best practice. We found that this emergent practice, matched with slower maturing varieties and additional N inputs as required, has the potential to increase wheat yields nationally by 30%. Frost and heat stress accounted for losses of 16% to 26% depending on the stress function used. Allowing for the impact of frost and heat stress reduced the yield potential of both the current and emergent water-limited yields yet it did not reduce the advantage of the emergent practice. [ABSTRACT FROM AUTHOR]

Global food security requires that grain yields continue to increase to 2050, yet yields have stalled in many developed countries. This disturbing trend has so far been only partially explained. Here, we show that wheat yields in Australia have stalled since 1990 and investigate the extent to which climate trends account for this observation. Based on simulation of 50 sites with quality weather data, that are representative of the agro-ecological zones and of soil types in the grain zone, we show that water-limited yield potential declined by 27% over a 26 year period from 1990 to 2015. We attribute this decline to reduced rainfall and to rising temperatures while the positive effect of elevated atmospheric CO2 concentrations prevented a further 4% loss relative to 1990 yields. Closer investigation of three sites revealed the nature of the simulated response of water-limited yield to water availability, water stress and maximum temperatures. At all three sites, maximum temperature hastened time from sowing to flowering and to maturity and reduced grain number per m2 and average weight per grain. This 27% climate-driven decline in water-limited yield is not fully expressed in actual national yields. This is due to an unprecedented rate of technology-driven gains closing the gap between actual and water-limited potential yields by 25 kg ha−1 yr−1 enabling relative yields to increase from 39% in 1990 to 55% in 2015. It remains to be seen whether technology can continue to maintain current yields, let alone increase them to those required by 2050. [ABSTRACT FROM AUTHOR]

Abstract: To 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. [Copyright &y& Elsevier]

Abstract: To 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. [Copyright &y& Elsevier]

Achieving sustainable global food security for a rapidly growing world population is one of the greatest challenges of our time. Producing more food efficiently by closing the yield gaps is regarded as a promising solution to address this challenge without further expanding farming land. However, there is limited understanding of the causes contributing to yield gaps. The present study aimed to comprehensively examine three dimensions of the causes for the wheat yield gaps in Australia: farm management practices, farm characteristics and grower characteristics. Computer-assisted telephone interviews of 232 wheat producers from 14 contrasting local areas were conducted. The data collected on these three dimensions were used to develop a comprehensive framework to understand causes of yield gaps. Results reveal significant differences between farms with smaller yield gaps and those with greater yield gaps in relation to farming management as well as farm and grower characteristics. Findings further underline that farms with smaller yield gaps are likely to be smaller holdings growing less wheat on more favourable soil types, are more likely to apply more N fertiliser, to have a greater crop diversity, to soil-test a greater proportion of their fields, to have fewer resistant weeds, to adopt new technologies, and are less likely to grow wheat following either cereal crops or a pasture. They are more likely to use and trust a fee-for-service agronomist, and have a university education. The dynamic relationships between grower characteristics and farm management practices in causing yield gaps are further highlighted through a path analysis. This study is the first to demonstrate that yield gaps are the result of the intertwined dynamics between biophysical factors, grower socio-psychological characteristics and farm management practices. Socio-psychological factors not only directly contribute to yield gaps, but they also influence farm management practices that in turn contribute to yield gaps. Our findings suggest that, to close wheat yield gaps, it is important to develop integrated strategies that address both socio-psychological and farm management dimensions. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]