Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Co-evolution of wild rabbits (Oryctolagus cuniculus) and RHDV: resistance and virulence

Rabbit Haemorrhagic Disease Virus (RHDV) was introduced to Australia in 1995 for the control of wild rabbits. Initial outbreaks greatly reduced rabbit numbers and the virus has continued to control rabbits to varying degrees in different parts of Australia. However, recent field evidence suggests that the virus may be becoming less effective in those areas that have previously experienced repeated epizootics causing high mortality. There are also reports of rabbits returning to pre-1995 density levels, Virus and host can be expected to co-evolve. The host will develop resistance to the virus with the virus subsequently changing to overcome that resistance. It has been 12 years since the release of RHDV and it is an opportune time to examine where the dynamic currently stands between RHDV and rabbits. Laboratory challenge tests have indicated that resistance to RHDV has developed to different degrees in populations throughout Australia. In one population a low dose (1:25 dilution) of Czech strain RHDV failed to infect a single susceptible rabbit, yet infected a low to high (up to 73%) percentage across other populations tested. Different selection pressures are present in these populations and will be driving the level of resistance being seen. The mechanisms and genetics behind the development of resistance are also important as the on-going use of RHDV as a control tool in the management of rabbits relies on our understanding of factors influencing the efficacy of the virus. Understanding how resistance has developed may provide clues on how best to use the virus to circumvent these mechanisms. Similarly, it will help in managing populations that have yet to develop high levels of resistance.

Action learning in partnership with Landcare and catchment management groups to support increased pasture sowings in southern inland Queensland

The incorporation of sown pastures as short-term rotations into the cropping systems of northern Australia has been slow. The inherent chemical fertility and physical stability of the predominant vertisol soils across the region enabled farmers to grow crops for decades without nitrogen fertiliser, and precluded the evolution of a crop–pasture rotation culture. However, as less fertile and less physically stable soils were cropped for extended periods, farmers began to use contemporary farming and sown pasture technologies to rebuild and maintain their soils. This has typically involved sowing long-term grass and grass–legume pastures on the more marginal cropping soils of the region. In partnership with the catchment management authority, the Queensland Murray–Darling Committee (QMDC) and Landcare, a pasture extension process using the LeyGrain™ package was implemented in 2006 within two Grain & Graze projects in the Maranoa-Balonne and Border Rivers catchments in southern inland Queensland. The specific objectives were to increase the area sown to high quality pasture and to gain production and environmental benefits (particularly groundcover) through improving the skills of producers in pasture species selection, their understanding and management of risk during pasture establishment, and in managing pastures and the feed base better. The catalyst for increasing pasture sowings was a QMDC subsidy scheme for increasing groundcover on old cropping land. In recognising a need to enhance pasture knowledge and skills to implement this scheme, the QMDC and Landcare producer groups sought the involvement of, and set specific targets for, the LeyGrain workshop process. This is a highly interactive action learning process that built on the existing knowledge and skills of the producers. Thirty-four workshops were held with more than 200 producers in 26 existing groups and with private agronomists. An evaluation process assessed the impact of the workshops on the learning and skill development by participants, their commitment to practice change, and their future intent to sow pastures. The results across both project catchments were highly correlated. There was strong agreement by producers (>90%) that the workshops had improved knowledge and skills regarding the adaptation of pasture species to soils and climates, enabling a better selection at the paddock level. Additional strong impacts were in changing the attitudes of producers to all aspects of pasture establishment, and the relative species composition of mixtures. Producers made a strong commitment to practice change, particularly in managing pasture as a specialist crop at establishment to minimise risk, and in the better selection and management of improved pasture species (particularly legumes and the use of fertiliser). Producers have made a commitment to increase pasture sowings by 80% in the next 5 years, with fourteen producers in one group alone having committed to sow an additional 4893 ha of pasture in 2007–08 under the QMDC subsidy scheme. The success of the project was attributed to the partnership between QMDC and Landcare groups who set individual workshop targets with LeyGrain presenters, the interactive engagement processes within the workshops themselves, and the follow-up provided by the LeyGrain team for on-farm activities.

Weed management strategies for farming systems with herbicide tolerant cotton.

The introduction of glyphosate tolerant cotton has significantly improved the flexibility and management of a number of problem weeds in cotton systems. However, reliance on glyphosate poses risks to the industry in term of glyphosate resistance and species shift. The aims of this project were to identify these risks, and determine strategies to prevent and mitigate the potential for resistance evolution. Field surveys identified fleabane as the most common weed now in both irrigated and dryland system. Sowthistle has also increased in prevalence, and bladder ketmia and peachvine remained common. The continued reliance on glyphosate has favoured small seeded, and glyphosate tolerant species. Fleabane is both of these, with populations confirmed resistant in grains systems in Queensland and NSW. When species were assessed for their resistance risk, fleabane, liverseed grass, feathertop Rhodes grass, sowthistle and barnyard grass were determined to have high risk ratings. Management practices were also determined to rely heavily on glyphosate and therefore be high risk in summer fallows, and dryland glyphosate tolerant and conventional cotton. Situations were these high risk species are present in high risk cropping phases need particular attention. The confirmation of a glyphosate resistance barnyard grass population in a dryland glyphosate tolerant cotton system means resistance is now a reality for the cotton industry. However, experiments have shown that resistant populations can be managed with other herbicide options currently available. However, the options for fleabane management in cotton are still limited. Although some selective residual herbicides are showing promise, the majority of fleabane control tactics can only be used in other phases of the cotton rotation. An online glyphosate resistance tool has been developed. This tool allows growers to assess their individual glyphosate resistance risks, and how they can adjust their practices to reduce their risks. It also provides researchers with current information on weed species present and practices used across the industry. This tool will be extremely useful in tailoring future research and extension efforts. Simulations from the expanded glyphosate resistance model have shown that glyphosate resistance can be prevented and managed in glyphosate-tolerant cotton farming systems. However, for strategies to be successful, some effort is required. Simulations have shown the importance of controlling survivors of glyphosate applications, using effective glyphosate alternatives in fallows, and combining several effective glyphosate alternatives in crop, and these are the key to the prevention and management of glyphosate resistance.

Dosage consistency is the key factor in avoiding evolution of resistance to phosphine and population increase in stored-grain pests

BACKGROUND Control of pests in stored grain and the evolution of resistance to pesticides are serious problems worldwide. A stochastic individual-based two-locus model was used to investigate the impact of two important issues, the consistency of pesticide dosage through the storage facility and the immigration rate of the adult pest, on overall population control and avoidance of evolution of resistance to the fumigant phosphine in an important pest of stored grain, the lesser grain borer. RESULTS A very consistent dosage maintained good control for all immigration rates, while an inconsistent dosage failed to maintain control in all cases. At intermediate dosage consistency, immigration rate became a critical factor in whether control was maintained or resistance emerged. CONCLUSION Achieving a consistent fumigant dosage is a key factor in avoiding evolution of resistance to phosphine and maintaining control of populations of stored-grain pests; when the dosage achieved is very inconsistent, there is likely to be a problem regardless of immigration rate. © 2012 Society of Chemical Industry

Managing glyphosate resistance in Australian cotton farming: modelling shows how to delay evolution and maintain long-term population control

Glyphosate resistance is a rapidly developing threat to profitability in Australian cotton farming. Resistance causes an immediate reduction in the effectiveness of in-crop weed control in glyphosate-resistant transgenic cotton and summer fallows. Although strategies for delaying glyphosate resistance and those for managing resistant populations are qualitatively similar, the longer resistance can be delayed, the longer cotton growers will have choice over which tactics to apply and when to apply them. Effective strategies to avoid, delay, and manage resistance are thus of substantial value. We used a model of glyphosate resistance dynamics to perform simulations of resistance evolution in Sonchus oleraceus (common sowthistle) and Echinochloa colona (awnless barnyard grass) under a range of resistance prevention, delaying, and management strategies. From these simulations, we identified several elements that could contribute to effective glyphosate resistance prevention and management strategies. (i) Controlling glyphosate survivors is the most robust approach to delaying or preventing resistance. High-efficacy, high-frequency survivor control almost doubled the useful lifespan of glyphosate from 13 to 25 years even with glyphosate alone used in summer fallows. (ii) Two non-glyphosate tactics in-crop plus two in-summer fallows is the minimum intervention required for long-term delays in resistance evolution. (iii) Pre-emergence herbicides are important, but should be backed up with non-glyphosate knockdowns and strategic tillage; replacing a late-season, pre-emergence herbicide with inter-row tillage was predicted to delay glyphosate resistance by 4 years in awnless barnyard grass. (iv) Weed species' ecological characteristics, particularly seed bank dynamics, have an impact on the effectiveness of resistance strategies; S. oleraceus, because of its propensity to emerge year-round, was less exposed to selection with glyphosate than E. colona, resulting in an extra 5 years of glyphosate usefulness (18 v. 13 years) even in the most rapid cases of resistance evolution. Delaying tactics are thus available that can provide some or many years of continued glyphosate efficacy. If glyphosate-resistant cotton cropping is to remain profitable in Australian farming systems in the long-term, however, growers must adapt to the probability that they will have to deal with summer weeds that are no longer susceptible to glyphosate. Robust resistance management systems will need to include a diversity of weed control options, used appropriately.

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

Modelling the manager: Representing rule-based management in farming systems simulation models

We trace the evolution of the representation of management in cropping and grazing systems models, from fixed annual schedules of identical actions in single paddocks toward flexible scripts of rules. Attempts to define higher-level organizing concepts in management policies, and to analyse them to identify optimal plans, have focussed on questions relating to grazing management owing to its inherent complexity. “Rule templates” assist the re-use of complex management scripts by bundling commonly-used collections of rules with an interface through which key parameters can be input by a simulation builder. Standard issues relating to parameter estimation and uncertainty apply to management sub-models and need to be addressed. Techniques for embodying farmers' expectations and plans for the future within modelling analyses need to be further developed, especially better linking planning- and rule-based approaches to farm management and analysing the ways that managers can learn.

BYGUM – a new tool for BarnYard Grass Understanding and Management

Weed management has become increasingly challenging for cotton growers in Australia in the last decade. Glyphosate, the cornerstone of weed management in the industry, is waning in effectiveness as a result of the evolution of resistance in several species. One of these, awnless barnyard grass, is very common in Australian cotton fields, and is a prime example of the new difficulties facing growers in choosing effective and affordable management strategies. RIM (Ryegrass Integrated Management) is a computer-based decision support tool developed for the south-western Australian grains industry. It is commonly used there as a tool for grower engagement in weed management thinking and strategy development. We used RIM as the basis for a new tool that can fulfil the same types of functions for subtropical Australian cotton-grains farming systems. The new tool, BYGUM, provides growers with a robust means to evaluate five-year rotations including testing the economic value of fallows and fallow weed management, winter and summer cropping, cover crops, tillage, different herbicide options, herbicide resistance management, and more. The new model includes several northernregion- specific enhancements: winter and summer fallows, subtropical crop choices, barnyard grass seed bank, competition, and ecology parameters, and more freedom in weed control applications. We anticipate that BYGUM will become a key tool for teaching and driving the changes that will be needed to maintain sound weed management in cotton in the near future.

A review of weed management in wheat using crop competition

Wheat occupies a principal place in the diet of humans globally, contributing more to our daily calorie and protein intake than any other crop. For this reason, preventing weed induced yield losses in wheat has high significance for world food sustainability. Herbicides and tillage play an important role in weed control, but their use has often unacceptable consequences for humans and the wider environment. Additionally, the range of herbicides effective on key weeds is dwindling due to the evolution of herbicide resistance. Elevating crop competitiveness against weeds, through a combination of wheat breeding and innovative planting design (planting density, row spacing and orientation), has strong potential to reduce weed-induced yield losses in wheat. The last decade of research has provided a solid foundation for the breeding of weed suppressive wheat cultivars, and continued research in this area should be a focus for the future. In the interim, there is cause for optimism that weeds can be effectively suppressed using existing wheat varieties, through careful cultivar selection and choice of planting design. Further research is required to define the nature of relationships between cultivar traits and competitive planting strategies, across diverse weed flora in multiple countries, sites and seasons. Investment in such innovation promises to produce benefits, not only in terms of sustained wheat yields, but also in terms of human and ecosystem health, through ameliorating chemical and sediment contamination, soil degradation, and CO2 pollution.