An overview of integrated pest management (IPM) in north-eastern Australian grain farming systems: Past, present and future prospects

The authors overview integrated pest management (IPM) in grain crops in north-eastern Australia, which is defined as the area north of latitude 32°S. Major grain crops in this region include the coarse grains (winter and summer cereals), oilseeds and pulses. IPM in these systems is complicated by the diversity of crops, pests, market requirements and cropping environments. In general, the pulse crops are at greatest risk, followed by oilseeds and then by cereal grains. Insecticides remain a key grain pest management tool in north-eastern Australia. IPM in grain crops has benefited considerably through the increased adoption of new, more selective insecticides and biopesticides for many caterpillar pests, in particular Helicoverpa spp. and loopers, and the identification of pest-crop scenarios where spraying is unnecessary (e.g. for most Creontiades spp. populations in soybeans). This has favoured the conservation of natural enemies in north-eastern Australia grain crops, and has arguably assisted in the management of silverleaf whitefly in soybeans in coastal Queensland. However, control of sucking pests and podborers such as Maruca vitrata remains a major challenge for IPM in summer pulses. Because these crops have very low pest-damage tolerances and thresholds, intervention with disruptive insecticides is frequently required, particularly during podfill. The threat posed by silverleaf whitefly demands ongoing multi-pest IPM research, development and extension as this pest can flare under favourable seasonal conditions, especially where disruptive insecticides are used injudiciously. The strong links between researchers and industry have facilitated the adoption of IPM practices in north-eastern Australia and augers well for future pest challenges and for the development and promotion of new and improved IPM tactics.

Assessing the sustainability of wheat-based cropping systems using APSIM: Model parameterisation and evaluation

Assessing the sustainability of crop and soil management practices in wheat-based rotations requires a well-tested model with the demonstrated ability to sensibly predict crop productivity and changes in the soil resource. The Agricultural Production Systems Simulator (APSIM) suite of models was parameterised and subsequently used to predict biomass production, yield, crop water and nitrogen (N) use, as well as long-term soil water and organic matter dynamics in wheat/chickpea systems at Tel Hadya, north-western Syria. The model satisfactorily simulated the productivity and water and N use of wheat and chickpea crops grown under different N and/or water supply levels in the 1998-99 and 1999-2000 experimental seasons. Analysis of soil-water dynamics showed that the 2-stage soil evaporation model in APSIM's cascading water-balance module did not sufficiently explain the actual soil drying following crop harvest under conditions where unused water remained in the soil profile. This might have been related to evaporation from soil cracks in the montmorillonitic clay soil, a process not explicitly simulated by APSIM. Soil-water dynamics in wheat-fallow and wheat-chickpea rotations (1987-98) were nevertheless well simulated when the soil water content in 0-0.45 m soil depth was set to 'air dry' at the end of the growing season each year. The model satisfactorily simulated the amounts of NO3-N in the soil, whereas it underestimated the amounts of NH 4-N. Ammonium fixation might be part of the soil mineral-N dynamics at the study site because montmorillonite is the major clay mineral. This process is not simulated by APSIM's nitrogen module. APSIM was capable of predicting long-term trends (1985-98) in soil organic matter in wheat-fallow and wheat-chickpea rotations at Tel Hadya as reported in literature. Overall, results showed that the model is generic and mature enough to be extended to this set of environmental conditions and can therefore be applied to assess the sustainability of wheat-chickpea rotations at Tel Hadya.

A systems evaluation of high-input management using fortified molasses for beef production in Australia's dry tropics

The potential of beef producers to profitably produce 500-kg steers at 2.5 years of age in northern Australia's dry tropics to meet specifications of high-value markets, using a high-input management (HIM) system was examined. HIM included targeted high levels of fortified molasses supplementation, short seasonal mating and the use of growth promotants. Using herds of 300-400 females plus steer progeny at three sites, HIM was compared at a business level to prevailing best-practice, strategic low-input management (SLIM) in which there is a relatively low usage of energy concentrates to supplement pasture intake. The data presented for each breeding-age cohort within management system at each site includes: annual pregnancy rates (range: 14-99%), time of conception, mortalities (range: 0-10%), progeny losses between confirmed pregnancy and weaning (range: 0-29%), and weaning rates (range: 14-92%) over the 2-year observation. Annual changes in weight and relative net worth were calculated for all breeding and non-breeding cohorts. Reasons for outcomes are discussed. Compared with SLIM herds, both weaning weights and annual growth were >= 30 kg higher, enabling 86-100% of HIM steers to exceed 500 kg at 2.5 years of age. Very few contemporary SLIM steers reached this target. HIM was most profitably applied to steers. Where HIM was able to achieve high pregnancy rates in yearlings, its application was recommended in females. Well managed, appropriate HIM systems increased profits by around $15/adult equivalent at prevailing beef and supplement prices. However, a 20% supplement price rise without a commensurate increase in values for young slaughter steers would generally eliminate this advantage. This study demonstrated the complexity of pro. table application of research outcomes to commercial business, even when component research suggests that specific strategies may increase growth and reproductive efficiency and/or be more pro. table. Because of the higher level of management required, higher costs and returns, and higher susceptibility to market changes and disease, HIM systems should only be applied after SLIM systems are well developed. To increase profitability, any strategy must ultimately either increase steer growth and sale values and/or enable a shift to high pregnancy rates in yearling heifers.

Runoff, soil loss, and nutrient transport from cropping systems on Red Ferrosols in tropical northern Australia.

Runoff, soil loss, and nutrient loss were assessed on a Red Ferrosol in tropical Australia over 3 years. The experiment was conducted using bounded, 100-m(2) field plots cropped to peanuts, maize, or grass. A bare plot, without cover or crop, was also instigated as an extreme treatment. Results showed the importance of cover in reducing runoff, soil loss, and nutrient loss from these soils. Runoff ranged from 13% of incident rainfall for the conventional cultivation to 29% under bare conditions during the highest rainfall year, and was well correlated with event rainfall and rainfall energy. Soil loss ranged from 30 t/ha. year under bare conditions to <6 t/ha. year under cropping. Nutrient losses of 35 kg N and 35 kg P/ha. year under bare conditions and 17 kg N and 11 kg P/ha. year under cropping were measured. Soil carbon analyses showed a relationship with treatment runoff, suggesting that soil properties influenced the rainfall runoff response. The cropping systems model PERFECT was calibrated using runoff, soil loss, and soil water data. Runoff and soil loss showed good agreement with observed data in the calibration, and soil water and yield had reasonable agreement. Longterm runs using historical weather data showed the episodic nature of runoff and soil loss events in this region and emphasise the need to manage land using protective measures such as conservation cropping practices. Farmers involved in related, action-learning activities wished to incorporate conservation cropping findings into their systems but also needed clear production benefits to hasten practice change.

Sensory Systems in Sawfishes. 2. The Lateral Line.

The lateral line system allows elasmobranchs to detect hydrodynamic movements in their close surroundings. We examined the distribution of pit organs and lateral line canals in 4 species of sawfish (Anoxypristis cuspidata, Pristis microdon, P. clavata and P. zijsron). Pit organs could only be located in A. cuspidata, which possesses elongated pits that are lined by dermal denticles. In all 4 pristid species, the lateral line canals are well developed and were separated into regions of pored and non-pored canals. In all species the tubules that extend from pored canals form extensive networks. In A. cuspidata, P. microdon and P. clavata, the lateral line canals on both the dorsal and ventral surfaces of the rostrum possess extensively branched and pored tubules. Based on this morphological observation, we hypothesized that these 3 species do not use their rostrum to search in the substrate for prey as previously assumed. Other batoids that possess lateral line canals adapted to perceive stimuli produced by infaunal prey possess non-pored lateral line canals, which also prevent the intrusion of substrate particles. However, this hypothesis remains to be tested behaviourally in pristids. Lateral line canals located between the mouth and the nostrils are non-pored in all 4 species of sawfish. Thus this region is hypothesized to perceive stimuli caused by direct contact with prey before ingestion. Lateral line canals that contain neuromasts are longest in P. microdon, but canals containing neuromasts along the rostrum are longest in A. cuspidata.

Economic modelling of grazing systems in the Fitzroy and Burdekin catchments

The Great Barrier Reef (GBR) is the largest reef system in the world; it covers an area of approximately 2,225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland coast. Recent research has identified that poor water quality is having negative impacts on the GBR (Haynes et al. 2007). The Fitzroy Basin covers 143,000 km² and is the largest catchment draining into the GBR as well as being one of the largest catchments in Australia (Karfs et al. 2009). The Burdekin Catchment is the second largest catchment entering into the GBR and covers 133,432 km².The prime determinant for the changes in water quality entering into the GBR have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al. 2009). Extensive beef production contributes over $1 billion dollars to the national economy annually and employs over 9000 people, many in rural communities (Gordon 2007). ‘Economic modelling of grazing systems in the Fitzroy and Burdekin catchments’ was a joint project with the Fitzroy Basin Association and the Queensland Department of Employment Economic Development and Innovation. The project was formed under the federally funded Caring For Our Country and the Reef Rescue programs. The project objectives were as follows; * Quantifying the costs of over-utilising available pasture and the resulting sediment leaving a representative farm for four of the major land systems in the Burdekin or Fitzroy catchments and identifying economically optimal pasture utilisation rates * Estimating the cost of reducing pasture utilisation rates below the determined optimal * Using this information, guide the selection of appropriate tools to achieve reduced utilisation rates e.g. extension process versus incentive payments or a combination of both * Model the biophysical and economic impacts of altering grazing systems to restore land condition e.g. from C condition to B condition for four land systems in the Burdekin or Fitzroy catchments.

The role of tillage, fertiliser and forage species in sustaining dairying based on crops in southern Queensland 2. Double-crop and summer sole-crop systems.

Dairy farms located in the subtropical cereal belt of Australia rely on winter and summer cereal crops, rather than pastures, for their forage base. Crops are mostly established in tilled seedbeds and the system is vulnerable to fertility decline and water erosion, particularly over summer fallows. Field studies were conducted over 5 years on contrasting soil types, a Vertosol and Sodosol, in the 650-mm annual-rainfall zone to evaluate the benefits of a modified cropping program on forage productivity and the soil-resource base. Growing forage sorghum as a double-crop with oats increased total mean annual production over that of winter sole-crop systems by 40% and 100% on the Vertosol and Sodosol sites respectively. However, mean annual winter crop yield was halved and overall forage quality was lower. Ninety per cent of the variation in winter crop yield was attributable to fallow and in-crop rainfall. Replacing forage sorghum with the annual legume lablab reduced fertiliser nitrogen (N) requirements and increased forage N concentration, but reduced overall annual yield. Compared with sole-cropped oats, double-cropping reduced the risk of erosion by extending the duration of soil water deficits and increasing the time ground was under plant cover. When grown as a sole-crop, well fertilised forage sorghum achieved a mean annual cumulative yield of 9.64 and 6.05 t DM/ha on the Vertosol and Sodosol, respectively, being about twice that of sole-cropped oats. Forage sorghum established using zero-tillage practices and fertilised at 175 kg N/ha. crop achieved a significantly higher yield and forage N concentration than did the industry-standard forage sorghum (conventional tillage and 55 kg N/ha. crop) on the Vertosol but not on the Sodosol. On the Vertosol, mean annual yield increased from 5.65 to 9.64 t DM/ha (33 kg DM/kg N fertiliser applied above the base rate); the difference in the response between the two sites was attributed to soil type and fertiliser history. Changing both tillage practices and N-fertiliser rate had no affect on fallow water-storage efficiency but did improve fallow ground cover. When forage sorghum, grown as a sole crop, was replaced with lablab in 3 of the 5 years, overall forage N concentration increased significantly, and on the Vertosol, yield and soil nitrate-N reserves also increased significantly relative to industry-standard sorghum. All forage systems maintained or increased the concentration of soil nitrate-N (0-1.2-m soil layer) over the course of the study. Relative to sole-crop oats, alternative forage systems were generally beneficial to the concentration of surface-soil (0-0.1 m) organic carbon and systems that included sorghum showed most promise for increasing soil organic carbon concentration. We conclude that an emphasis on double-or summer sole-cropping rather than winter sole-cropping will advantage both farm productivity and the soil-resource base.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.