Jeremy Whish

Re-inventing model-based decision support with Australian dryland farmers. 3. Relevance of APSIM to commercial crops

Crop simulation models relevant to real-world agriculture have been a rationale for model development over many years. However, as crop models are generally developed and tested against experimental data and with large systematic gaps often reported between experimental and farmer yields, the relevance of simulated yields to the commercial yields of field crops may be questioned. This is the third paper in a series which describes a substantial effort to deliver model-based decision support to Australian farmers. First, the performance of the cropping systems simulator, APSIM, in simulating commercial crop yields is reported across a range of field crops and agricultural regions. Second, how APSIM is used in gaining farmer credibility for their planning and decision making is described using actual case studies. Information was collated on APSIM performance in simulating the yields of over 700 commercial crops of barley, canola, chickpea, cotton, maize, mungbean, sorghum, sugarcane, and wheat monitored over the period 1992 to 2007 in all cropping regions of Australia. This evidence indicated that APSIM can predict the performance of commercial crops at a level close to that reported for its performance against experimental yields. Importantly, an essential requirement for simulating commercial yields across the Australian dryland cropping regions is to accurately describe the resources available to the crop being simulated, particularly soil water and nitrogen. Five case studies of using APSIM with farmers are described in order to demonstrate how model credibility was gained in the context of each circumstance. The proposed process for creating mutual understanding and credibility involved dealing with immediate questions of the involved farmers, contextualising the simulations to the specific situation in question, providing simulation outputs in an iterative process, and together reviewing the ensuing seasonal results against provided simulations. This paper is distinct from many other reports testing the performance and utility of cropping systems models. Here, the measured yields are from commercial crops not experimental plots and the described applications were from real-life situations identified by farmers. A key conclusion, from 17 years of effort, is the proven ability of APSIM to simulate yields from commercial crops provided soil properties are well characterised. Thus, the ambition of models being relevant to real-world agriculture is indeed attainable, at least in situations where biotic stresses are manageable.

Modelling the effects of row configuration on sorghum yield reliability in north-eastern Australia

In recent years, many sorghum producers in the more marginal (<600mm annual rainfall) cropping areas of Queensland and northern New South Wales have used skip row configurations in an attempt to improve yield reliability and reduce sorghum production risk. This paper describes modi. cations made to the APSIM sorghum module to account for the difference in water usage and light interception between alternative crop planting configurations, and then demonstrates how this new model can be used to quantify the long-term benefits of skip sorghum production. Detailed measurements of light interception and water extraction from sorghum crops grown in solid, single and double skip row configurations were collected from on-farm experiments in southern Qld and northern NSW. These measurements underpinned changes to the APSIM-Sorghum model so that it accounted for the elliptical water uptake pattern below the crop row and the reduced total light interception associated with skip row configurations. Long-term simulation runs using long-term weather files for locations near the experimental sites were used to determine the value of skip row sorghum production as a means of maintaining yield reliability. These simulations showed a trade-off between long-term average production (profitability) and annual yield reliability ( risk of failure this year). Over the long term, the production of sorghum in a solid configuration produced a higher average yield compared with sorghum produced in a skip configuration. This difference in average yield is a result of the solid configuration having a higher yield potential compared with the skip configurations. Skip configurations limit the yield potential as a safeguard against crop failure. To achieve the higher average yield in the solid configuration the producer suffers some total failures. Skip configurations reduce the chance of total failure by capping the yield potential, which in turn reduces the long-term average yield. The decision on what row configuration to use should be made tactically and requires consideration of the starting soil water, the soils plant-available water capacity (PAWC), and the farm familys current attitude to risk.

The effect of row spacing and weed density on yield loss of chickpea

The adoption of no-till farming and the desire to maintain stubble cover when sowing legumes in northern New South Wales and southern Queensland have resulted in an increase in commercial row spacing for chickpea (Cicer arietinum L.). This paper examines the effects of increasing crop row widths on weed competition in chickpea crops. Weed densities of 0, 2, 4, 8, 16, and 32 plants/m 2 of wild oats (Avena sterilis ssp. ludoviciana) and turnip weed (Rapistrum rugosum) were established with chickpea crops planted with either 32 or 64 cm row configurations in northern New South Wales during 1996 and 1997. A rectangular hyperbolic model adequately represented the loss in chickpea yield with increasing density of either weed. Even low densities of <10 plants/m 2 caused large (approx. 50%) reductions in yield, particularly with turnip weed. In these experiments, weed-free yields were higher when chickpea was sown in 32 cm rows compared with 64 cm rows, but weeds caused no greater loss in crop yield with the wider row spacing. The results of this work show that the use of wide rows has minimal impact on weed competion in northern chickpea crops. Aowwns d c J

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crops green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crops leaves feedback to the APSIM crop modifying the growth and development of the crops leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework. Modelling biotic constraints within farming system models.The linking of multi-cohort population models and farming systems crop models.Managing the complexity of combining population models and agro-ecological models.

Dual-purpose use of winter wheat in western China: cutting time and nitrogen application effects on phenology, forage production, and grain yield

Abstract. Conventional rainfed mixed crop–livestock systems of western China lack high-quality forage and restrict livestock production. This study explored the forage potential from wheat and its effects on subsequent grain yield. Different cutting times were imposed on winter wheat (Triticum aestivum) at Qingyang, Gansu Province, in two growing seasons, and the effect of nitrogen (N) topdressing rates (0, 60, and 120 kg N/ha) on grain yield recovery was explored. Results showed the potential to produce 0.8–1.6 t DM/ha of wheat forage with high nutritive value when cut before stem elongation (GS 30). In the wetter year, cutting before stem elongation did not delay crop development significantly (<3 days at anthesis and 5 days at maturity), but grain yields were reduced by 17–28% compared with the uncut crop (5.8 t DM/ha), mainly due to reductions in number of spikes per m2 and, consequently, number of grains per m2. In both seasons, more forage biomass was available if crops were cut later than GS 32, but this came with large reductions (>62%) in grain yield and delays in crop development (>9 days or 131 degree-days). Crops cut later than GS 30 had greatly reduced harvest index, tillers per m2, and total N uptake but higher grain protein content. There was no significant effect of N topdressing rate on grain yield, although provided the crop was cut before GS 30, higher rates of N increased maturity biomass and crop N uptake by replacing N removed in cut biomass. This study showed that physiological delay of wheat due to cutting was not significant. The forage harvested from winter wheat before stem elongation could be a valuable feed resource to fill the feed gap in western China.

Do spring cover crops rob water and so reduce wheat yields in the northern grain zone of eastern Australia

During the 14-month-long fallow that arises when moving from summer to winter crops, stubble breakdown can denude the soil surface and leave it vulnerable to erosion. Cover crops of millet have been proposed as a solution, but this then raises the question, how often is there sufficient water in the system to grow a cover crop without reducing the soil water reserves to the point of prejudicing the following wheat crop? An on-farm research approach was used to compare the traditional long fallow (TF) with a millet fallow (MF) in a total of 31 commercial paddocks over 3 years. Each treatment was simulated using the simulation-modelling framework (APSIM) to investigate the outcomes over a longer timeframe and to determine how often a millet fallow could be successfully included within the farming system. The on-farm trials showed that early-sown millet cover crops removed before December had no effect on wheat yield, but this was not true of millet cover crops that were allowed to grow through to maturity. Long-term simulations estimated that a spring cover crop of millet would adversely affect wheat yields in only 2% of years if planted early and removed after 50% cover had been achieved.

Prospects to utilise intercrops and crop variety mixtures in mechanised, rain-fed, temperate cropping systems

Abstract. Despite the potential productivity benefits, intercrops are not widely used in modern, mechanised grain cropping systems such as those practised in Australia, due to the additional labour required and the added complexity of management (e.g. harvesting and handling of mixed grain). In this review we investigate this dilemma using a two-dimensional matrix to categorise and evaluate intercropping systems. The first dimension describes the acquisition and use of resources in complementary or facilitative interactions that can improve resource use efficiency. The outcome of this resource use is often quantified using the land equivalent ratio (LER). This is a measure of the relative land area required as monocultures to produce the same yields as achieved by an intercrop. Thus, an LER greater than 1 indicates a benefit of the intercrop mixture. The second dimension describes the benefits to a farming system arising not only from the productivity benefits relating to increased LER, but from other often unaccounted benefits related to improved product quality, rotational benefits within the cropping system, or to reduced business risks. We contend that a successful intercrop must have elements in both dimensions. To date most intercropping research has considered only one of these two possible dimensions. Intercrops in large, mechanised, rain-fed farming systems can comprise those of annual legumes with non-legume crops to improve N nutrition, or other species combinations that improve water use through hydraulic redistribution (the process whereby a deep-rooted plant extracts water from deep in the soil profile and releases a small proportion of this into the upper layers of the soil at night), or alter disease, pest or weed interactions. Combinations of varieties within cereal varieties were also considered. For our focus region in the southern Australian wheatbelt, we found few investigations that adequately dealt with the systems implications of intercrops on weeds, diseases and risk mitigation. The three main intercrop groups to date were (1) ‘peaola’ (canola-field pea intercrops) where 70% of intercrops (n = 34) had a 50% productivity increase over the monocultures, (2) cereal-grain legume intercrops (n = 22) where 64% showed increases in crop productivity compared with monocultures and (3) mixtures of cereal varieties (n = 113) where there was no evidence of a productivity increase compared with the single varieties. Our review suggests that intercropping may have a role in large rain-fed grain cropping systems, based on the biophysical benefits revealed in the studies to date. However, future research to develop viable intercrop options should identify and quantify the genotypic differences within crop species for adaptation to intercropping, the long-term rotational benefits associated with intercrops, and the yield variability and complexity-productivity trade-offs in order to provide more confidence for grower adoption. Farming systems models will be central to many of these investigations but are likely to require significant improvement to capture important processes in intercrops (e.g. competition for water, nutrients and light).