Root-lesion nematodes (Pratylenchus thornei and P. neglectus): A review of recent progress in managing a significant pest of grain crops in northern Australia

Two species of root-lesion nematode (predominantly Pratylenchus thornei but also P. neglectus) are widespread pathogens of wheat and other crops in Australia's northern grain belt, a subtropical region with deep, fertile clay soils and a summer-dominant rainfall pattern. Losses in grain yield from P. thornei can be as high as 70% for intolerant wheat cultivars. This review focuses on research which has led to the development of effective integrated management programs for these nematodes. It highlights the importance of correct identification in managing Pratylenchus species, reviews the plant breeding work done in developing tolerant and resistant cultivars, outlines the methods used to screen for tolerance and resistance, and discusses how planned crop sequencing with tolerant and partially resistant wheat cultivars, together with crops such as sorghum, sunflower, millets and canaryseed, can be used to reduce nematode populations and limit crop damage. The declining levels of soil organic matter in cropped soils are also discussed with reference to their effect on soil health and biological suppression of root-lesion nematodes.

A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets

Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Modelling climatic risks of aflatoxin contamination in maize

Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

Risk management for mycotoxin contamination of Australian maize

Recent incidents of mycotoxin contamination (particularly aflatoxins and fumonisins) have demonstrated a need for an industry-wide management system to ensure Australian maize meets the requirements of all domestic users and export markets. Results of recent surveys are presented, demonstrating overall good conformity with nationally accepted industry marketing standards but with occasional samples exceeding these levels. This paper describes mycotoxin-related hazards inherent in the Australian maize production system and a methodology combining good agricultural practices and the hazard analysis critical control point framework to manage risk.

Managing mycotoxins in maize: Case studies

Mycotoxin contamination of Australian maize is neither common nor extensive, but has the capacity to seriously disrupt marketing. Low to moderate levels of aflatoxins and fumonisins can be widespread in some seasons, but zearalenone, nivalenol and deoxynivalenol are usually confined to small growing localities. Possible approaches to such situations were tested by an analysis of several case studies. It is concluded that communication and coordination across the industry, prediction and prevention of contamination, rapid detection and assessment of contamination, effective use of contaminated maize and breeding for resistance comprise a useful set of strategies for managing mycotoxins in maize.

Architectural modelling of maize under water stress

Two field experiments using maize (Pioneer 31H50) and three watering regimes [(i) irrigated for the whole crop cycle, until anthesis, (ii) not at all (experiment 1) and (iii) fully irrigated and rain grown for the whole crop cycle (experiment 2)] were conducted at Gatton, Australia, during the 2003-04 season. Data on crop ontogeny, leaf, sheath and internode lengths and leaf width, and senescence were collected at 1- to 3-day intervals. A glasshouse experiment during 2003 quantified the responses of leaf shape and leaf presentation to various levels of water stress. Data from experiment 1 were used to modify and parameterise an architectural model of maize (ADEL-Maize) to incorporate the impact of water stress on maize canopy characteristics. The modified model produced accurate fitted values for experiment 1 for final leaf area and plant height, but values during development for leaf area were lower than observed data. Crop duration was reasonably well fitted and differences between the fully irrigated and rain-grown crops were accurately predicted. Final representations of maize crop canopies were realistic. Possible explanations for low values of leaf area are provided. The model requires further development using data from the glasshouse study and before being validated using data from experiment 2 and other independent data. It will then be used to extend functionality in architectural models of maize. With further research and development, the model should be particularly useful in examining the response of maize production to water stress including improved prediction of total biomass and grain yield. This will facilitate improved simulation of plant growth and development processes allowing investigation of genotype by environment interactions under conditions of suboptimal water supply.

Analysis of high yielding maize production - A study based on a commercial crop

This paper reports on the use of APSIM - Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004-05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004-05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004-05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

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.

Insecticide resistance and implications for future aphid management in Australian grains and pastures: A review

Aphids can cause substantial damage to cereals, oilseeds and legumes through direct feeding and through the transmission of plant pathogenic viruses. Aphid-resistant varieties are only available for a limited number of crops. In Australia, growers often use prophylactic sprays to control aphids, but this strategy can lead to non-target effects and the development of insecticide resistance. Insecticide resistance is a problem in one aphid pest of Australian grains in Australia, the green peach aphid (Myzus persicae). Molecular analyses of field-collected samples demonstrate that amplified E4 esterase resistance to organophosphate insecticides is widespread in Australian grains across Australia. Knockdown resistance to pyrethroids is less abundant, but has an increased frequency in areas with known frequent use of these insecticides. Modified acetylcholinesterase resistance to dimethyl carbamates, such as pirimicarb, has not been found in Australia, nor has resistance to imidacloprid. Australian grain growers should consider control options that are less likely to promote insecticide resistance, and have reduced impacts on natural enemies. Research is ongoing in Australia and overseas to provide new strategies for aphid management in the future.

Host-plant resistance and biopesticides: Ingredients for successful integrated pest management (IPM) in Australian sorghum production

There are two major pests of sorghum in Australia, the sorghum midge, Stenodiplosis sorghicola (Coquillett), and the corn earworm, Helicoverpa armigera (Hübner). During the past 10 years the management of these pests has undergone a revolution, due principally to the development of sorghum hybrids with resistance to sorghum midge. Also contributing has been the adoption of a nucleopolyhedrovirus for the management of corn earworm. The practical application of these developments has led to a massive reduction in the use of synthetic insecticides for the management of major pests of sorghum in Australia. These changes have produced immediate economic, environmental and social benefits. Other flow-on benefits include providing flexibility in planting times, the maintenance of beneficial arthropods and utilisation of sorghum as a beneficial arthropod nursery, a reduction in midge populations and a reduction in insecticide resistance development in corn earworm. Future developments in sorghum pest management are discussed.

Impacts of feeding system and season on milk composition and Cheddar cheese yield in a subtropical environment

Milk obtained from cows on 2 subtropical dairy feeding systems were compared for their suitability for Cheddar cheese manufacture. Cheeses were made in a small-scale cheesemaking plant capable of making 2 blocks ( about 2 kg each) of Cheddar cheese concurrently. Its repeatability was tested over 10 separate cheesemaking days with no significant differences being found between the 2 vats in cheesemaking parameters or cheese characteristics. In the feeding trial, 16 pairs of Holstein - Friesian cows were used in 2 feeding systems (M1, rain-grown tropical grass pastures and oats; and M5, a feedlot, based on maize/barley silage and lucerne hay) over 2 seasons ( spring and autumn corresponding to early and late lactation, respectively). Total dry matter, crude protein (kg/cow. day) and metabolisable energy (MJ/cow.day) intakes were 17, 2.7, and 187 for M1 and 24, 4, 260 for M5, respectively. M5 cows produced higher milk yields and milk with higher protein and casein levels than the M1 cows, but the total solids and fat levels were similar (P > 0.05) for both M1 and M5 cows. The yield and yield efficiency of cheese produced from the 2 feeding systems were also not significantly different. The results suggest that intensive tropical pasture systems can produce milk suitable for Cheddar cheese manufacture when cows are supplemented with a high energy concentrate. Season and stage of lactation had a much greater effect than feeding system on milk and cheesemaking characteristics with autumn ( late lactation) milk having higher protein and fat contents and producing higher cheese yields.

Relative contributions of light interception and radiation use efficiency to the reduction of maize productivity under cold temperatures

Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

The use of high resolution melting (HRM) to map single nucleotide polymorphism markers linked to a covered smut resistance gene in barley

Using an established genetic map, a single gene conditioning covered smut resistance, Ruh.7H, was mapped to the telomere region of chromosome 7HS in an Alexis/Sloop doubled haploid barley population. The closest marker to Ruh.7H, abg704 was 7.5 cM away. Thirteen loci on the distal end of 7HS with potential to contain single nucleotide polymorphisms (SNPs) were identified by applying a comparative genomics approach using rice sequence data. Of these, one locus produced polymorphic co-dominant bands of different size while two further loci contained SNPs that were identified using the recently developed high resolution melting (HRM) technique. Two of these markers flanked Ruh.7H with the proximal marker located 3.8 cM and the distal marker 2.7 cM away. This is the first report on the application of the HRM technique to SNP detection and to rapid scoring of known cleaved amplified polymorphic sequence (CAPS) markers in plants. This simple, precise post-PCR technique should find widespread use in the fine-mapping of genetic regions of interest in complex cereal and other plant genomes.

Graze to grain - measuring and modelling the effects of grazed pasture leys on soil nitrogen and sorghum yield on a Vertosol soil in the Australian subtropics

Highly productive sown pasture systems can result in high growth rates of beef cattle and lead to increases in soil nitrogen and the production of subsequent crops. The nitrogen dynamics and growth of grain sorghum following grazed annual legume leys or a grass pasture were investigated in a no-till system in the South Burnett district of Queensland. Two years of the tropical legumes Macrotyloma daltonii and Vigna trilobata (both self regenerating annual legumes) and Lablab purpureus (a resown annual legume) resulted in soil nitrate N (0-0.9 m depth), at sorghum sowing, ranging from 35 to 86 kg/ha compared with 4 kg/ha after pure grass pastures. Average grain sorghum production in the 4 cropping seasons following the grazed legume leys ranged from 2651 to 4012 kg/ha. Following the grass pasture, grain sorghum production in the first and second year was < 1900 kg/ha and by the third year grain yield was comparable to the legume systems. Simulation studies utilising the farming systems model APSIM indicated that the soil N and water dynamics following 2-year ley phases could be closely represented over 4 years and the prediction of sorghum growth during this time was reasonable. In simulated unfertilised sorghum crops grown from 1954 to 2004, grain yield did not exceed 1500 kg/ha in 50% of seasons following a grass pasture, while following 2-year legume leys, grain exceeded 3000 kg/ha in 80% of seasons. It was concluded that mixed farming systems that utilise short term legume-based pastures for beef production in rotation with crop production enterprises can be highly productive.

Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform

A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.