Seasonal climate forecasts for more effective raingrown grain-cotton production systems

Cropping is a risky business. Our highly variable climate makes it difficult to decide how best to manage crops and cropping systems. What works well one year might not work well the next. To develop better risk management practices, this project uses the APSIM cropping systems model to examine the profitability and sustainability of a range of alternative dryland cotton/grain cropping systems throughout the northern grain region of eastern Australia. It involves working closely with farmer collaborators in Central Queensland, the Darling Downs, the northwest slopes of NSW and the Liverpool Plains

Sowing summer grain crops early in late winter or spring: Effects on root growth, water use, and yield

CONTEXT. Drought and extreme heat at flowering are common stresses limiting the yield of summer crops. Adaptation to these stresses could be increased by sowing summer crops early in late winter or spring, to avoid the overlap with critical crop stages around flowering. Though little is known about the effects of cold weather on root growth, water use and final grain yield in sorghum. OBJECTIVE. To research the effects of cold conditions in early sowing sorghum on crop and root growth and function (i.e., water use), and final grain yield. METHODS. Two years of field experiments were conducted in the Darling and Eastern Downs region of Qld, Australia. Each trial consisted of three times of sowing (late winter, spring, and summer), two levels of irrigation (i.e., rainfed and supplementary irrigated), four plant population densities (3, 6, 9 and 12 pl m⁻²), and six commercial sorghum hybrids. Roots and shoots were sampled at the flag leaf stage on three times of sowing, two levels of irrigation, and three replications, for a single hybrid and a single plant population density (9pl m⁻²). Crop water use and functional root traits were derived from consecutive electromagnetic induction (EMI) surveys around flowering. At maturity crop biomass, yield and yield components were determined across all treatments. RESULTS. The combinations of seasons, times of sowing and levels of irrigation created large variations in growth conditions that affected the growth and production of the crops. Early sowing increased yield by transferring water use from vegetative to reproductive stages increasing water use efficiency (kg mm⁻¹ available water). The larger yields in the early and spring sown crops were associated to larger grain numbers, particularly in tillers. Cold temperatures in the early sowing times tended to produce smaller crops with smaller rooting systems, smaller root-to-shoot ratios, and larger average root diameters. Total root length and root length density increased with increasing pre-flowering mean air temperatures up to 20°C. Linear relationships were observed between an EMI derived index of root activity and the empirically determined values of root length density (cm cm⁻³) at flowering. CONCLUSIONS. Sowing sorghum, a summer crop, early in late winter or spring transferred water use from vegetative stages to flowering and post-flowering stages increasing crop water use efficiency. The higher grain numbers in early sown crops were related to higher grain numbers in tillers. Root length and root length density were reduced by pre-flowering mean temperatures lower than 20°C, indicating a need to increase cold tolerance for early sowing. The EMI derived index of root activity has potential in the development of high throughput root phenotyping applications

Transformational agronomy by growing summer crops in winter: The cropping system and farm profits

The idea that “Yield is King” fails to acknowledge that what matters most to farmers is farm profits and risk, rather than yield. This is because decisions made in one season will affect options and crop performance over the next few years. Therefore, quantifying the longer-term impacts of innovation adoption is important. We used the Agricultural Production Simulation model (APSIM) to simulate and investigate the implications of adopting rain-fed winter sown sorghum in the Australian northern grains region. Results indicate that within a crop rotation early-planted sorghum will tend to decrease median sorghum crop yields but increase the following winter crop yields. This appears to have a marginal economic effect in Breeza and Dalby but encouraging results in Emerald. The inclusion of chickpea within the rotation increased returns in the best seasons with little change to downside risks in poor seasons

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

Rainfall variability at decadal and longer time scales: signal or noise?

Rainfall variability occurs over a wide range of temporal scales. Knowledge and understanding of such variability can lead to improved risk management practices in agricultural and other industries. Analyses of temporal patterns in 100 yr of observed monthly global sea surface temperature and sea level pressure data show that the single most important cause of explainable, terrestrial rainfall variability resides within the El Nino-Southern Oscillation (ENSO) frequency domain (2.5-8.0 yr), followed by a slightly weaker but highly significant decadal signal (9-13 yr), with some evidence of lesser but significant rainfall variability at interclecadal time scales (15-18 yr). Most of the rainfall variability significantly linked to frequencies tower than ENSO occurs in the Australasian region, with smaller effects in North and South America, central and southern Africa, and western Europe. While low-frequency (LF) signals at a decadal frequency are dominant, the variability evident was ENSO-like in all the frequency domains considered. The extent to which such LF variability is (i) predictable and (ii) either part of the overall ENSO variability or caused by independent processes remains an as yet unanswered question. Further progress can only be made through mechanistic studies using a variety of models

Effects of a wheat rotation on cotton production in a changing climate: a simulation study

There is mounting evidence that climate change could be threatening the viability of cotton production in regions of Australia. This study aims to evaluate the effectiveness of a cotton-wheat rotation system in dealing with climate change for the period centred on 2030 by linking the outputs of the CSIRO Conformal Cubic Atmospheric Model with the Agricultural Production System sIMulator (APSIM) through a stochastic weather generator, LARS-WG. For irrigated cotton, we considered 3 crop sequences and 9 production areas spanning the current industry. For rain-fed cotton, we considered 2 crop sequences with 3 cotton row configurations and 4 production areas. Simulation results show that (1) for irrigated cotton, cotton 3 yr in and 1 yr out would perform the best in terms of cotton lint yield; (2) crop yields would decrease in a changing climate across crop sequences at most of the locations with wheat yield decreasing more than cotton; (3) for rain-fed cotton, continuous cotton would perform better at Emerald, Dalby and/or Narrabri under solid and single skip row configurations, while a cotton-wheat sequence would out-perform continuous cotton in terms of cotton lint yields under double skip at Emerald, Moree and Narrabri; and (4) wheat yield would decrease across locations. To maintain current production levels, better performing crop sequence needs to be combined with other adaptation options

A participatory whole farm modelling approach to understand impacts and increase preparedness to climate change in Australia

This study presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario. The newly generated information was used to support discussions with the participating farmers in the search for options to design more profitable and sustainable farming systems in Queensland Australia. The four case studies contrasted in key systems characteristics: opportunism in decision making, i.e. flexible versus rigid crop rotations; function, i.e. production of livestock or crops; and level of intensification, i.e. dryland versus irrigated agriculture. Tested tactical and strategic changes under a baseline and climate change scenario (CCS) involved changes in the allocation of land between cropping and grazing enterprises, alternative allocations of limited irrigation water across cropping enterprises, and different management rules for planting wheat and sorghum in rainfed cropping. The results show that expected impacts from a likely climate change scenario were evident in the following increasing order: the irrigated cropping farm case study, the cropping and grazing farm, the more opportunistic rainfed cropping farm and the least opportunistic rainfed cropping farm. We concluded that in most cases the participating farmers were operating close to the efficiency frontier (i.e. in the relationship between profits and risks). This indicated that options to adapt to climate change might need to evolve from investments in the development of more innovative cropping and grazing systems and/or transformational changes on existing farming systems. We expect that even though assimilating expected changes in climate seems to be rather intangible and premature for these farmers, as innovations are developed, adaptation is likely to follow quickly. The multiple interactions among farm management components in complex and dynamic farm businesses operating in a variable and changing climate, make the use of whole farm participatory modelling approaches valuable tools to quantify benefits and trade-offs from alternative farming systems designs in the search for improved profitability and resilience

Simulating the efficiency and resilience of diverse crop sequences in Australia’s subtropical cropping zone

Farming systems in Australia’s subtropics have been under-performing. This study used simulation modelling to evaluate common crop sequences used in subtropical Australia in terms of their system water-use-efficiency (WUE) and resilience to climate variability. The analysis here examines this for 4 locations spanning the subtropical farming systems of eastern Australia. We found significant variation in the system WUE ($/ha/mm) amongst crop sequences, with common crop sequences in each location found to be 12-40% less WUE than the best crop sequence. Cropping intensity is a key driver of system profitability and risk, more so than a mix of crops used. Crop systems with higher intensities (i.e. less time in fallow) have higher average profitability but also higher risk; conversely, crop systems with longer fallows have a lower risk but there are trade-offs of lower long-term gross margins. It is critical to match cropping intensity to the environment to optimise the risk-return trade-offs. Lower crop intensities (0.5-0.75 crops/yr) are optimal in harsher environments (e.g. western districts), moderate crop intensities (0.75-1.0 crops/yr) in the moderate environments, but crop systems with higher crop intensities (1.0-1.3 crops/yr) are optimal in higher rainfall environments