Subsoil constraints to grain production in the cropping soils of the north-eastern region of Australia: an overview

In dryland agricultural systems of the subtropical, semi-arid region of north-eastern Australia, water is the most limiting resource. Crop productivity depends on the efficient use of rainfall and available water stored in the soil during fallow. Agronomic management practices including a period of fallow, stubble retention, and reduced tillage enhance reserves of soil water. However, access to stored water in these soils may be restricted by the presence of growth-limiting conditions in the rooting zone of the crop. These have been termed as subsoil constraints. Subsoil constraints may include compacted or gravel layers (physical), sodicity, salinity, acidity, nutrient deficiencies, presence of toxic elements (chemical) and low microbial activity (biological). Several of these constraints may occur together in some soils. Farmers have often not been able to obtain the potential yield determined by their prevailing climatic conditions in the marginal rainfall areas of the northern grains region. In the past, the adoption of soil management practices had been largely restricted to the top 100 mm soil layer. Exploitation of the subsoil as a source of water and nutrients has largely been overlooked. The key towards realising potential yields would be to gain better understanding of subsoils and their limitations, then develop options to manage them practically and economically. Due to the complex nature of the causal factors of these constraints, efforts are required for a combination of management approaches rather than individual options, with the aim to combat these constraints for sustainable crop production, managing natural resources and avoiding environmental damage.

Crop sequences to manage soil pathogens and increase northern grain production

This is part of a GRDC funded project led by Dr Jeremy Whish of CSIRO Ecosystem Sciences. The project aims to build a root-lesion nematode module into the crop growth simulation program APSIM (Agricultural Production Systems Simulator). This will utilise existing nematode and crop data from field, glasshouse and laboratory research led by Dr John Thompson. New data will be collected to validate and extend the model.

Evaluation for use efficiency of agricultural resources in grain production: A case study of Changshu, Taihe and Ansai in China

National Natural Science Foundation of China [70673097]

Updated empirical model of genetically-modified maize grain production practices to achieve European Union labeling thresholds

An updated empirical approach is proposed for specifying coexistence requirements for genetically modified (GM) maize (Zea mays L.) production to ensure compliance with the 0.9% labeling threshold for food and feed in the European Union. The model improves on a previously published (Gustafson et al., 2006) empirical model by adding recent data sources to supplement the original database and including the following additional cases: (i) more than one GM maize source field adjacent to the conventional or organic field, (ii) the possibility of so-called “stacked” varieties with more than one GM trait, and (iii) lower pollen shed in the non-GM receptor field. These additional factors lead to the possibility for somewhat wider combinations of isolation distance and border rows than required in the original version of the empirical model. For instance, in the very conservative case of a 1-ha square non-GM maize field surrounded on all four sides by homozygous GM maize with 12 m isolation (the effective isolation distance for a single GM field), non-GM border rows of 12 m are required to be 95% confident of gene flow less than 0.9% in the non-GM field (with adventitious presence of 0.3%). Stacked traits of higher GM mass fraction and receptor fields of lower pollen shed would require a greater number of border rows to comply with the 0.9% threshold, and an updated extension to the model is provided to quantify these effects.

Regional adjustments in grain production : a linear programming analysis /

"U.S. Dept. of Agriculture, in cooperation with Iowa Agriculture and Home Economics Experiment Station Center for agricultural and economic adjustment."

Regional adjustments in grain production : a linear programming analysis : mathematical models, proofs, methods of data collection and estimation, and supplementary tables /

Cover title.

Grain production and marketing /

"Issued October 1949."

The socioeconomics of food crop production and climate change vulnerability: a global scale quantitative analysis of how grain crops are sensitive to drought

Many studies warn that climate change may undermine global food security. Much work on this topic focuses on modelling crop-weather interactions but these models do not generally account for the ways in which socio-economic factors influence how harvests are affected by weather. To address this gap, this paper uses a quantitative harvest vulnerability index based on annual soil moisture and grain production data as the dependent variables in a Linear Mixed Effects model with national scale socio-economic data as independent variables for the period 1990-2005. Results show that rice, wheat and maize production in middle income countries were especially vulnerable to droughts. By contrast, harvests in countries with higher investments in agriculture (e.g higher amounts of fertilizer use) were less vulnerable to drought. In terms of differences between the world's major grain crops, factors that made rice and wheat crops vulnerable to drought were quite consistent, whilst those of maize crops varied considerably depending on the type of region. This is likely due to the fact that maize is produced under very different conditions worldwide. One recommendation for reducing drought vulnerability risks is coordinated development and adaptation policies, including institutional support that enables farmers to take proactive action.

Livestock production in a changing climate : adaptation and mitigation research in Australia

Climate change presents a range of challenges for animal agriculture in Australia. Livestock production will be affected by changes in temperature and water availability through impacts on pasture and forage crop quantity and quality, feed-grain production and price, and disease and pest distributions. This paper provides an overview of these impacts and the broader effects on landscape functionality, with a focus on recent research on effects of increasing temperature, changing rainfall patterns, and increased climate variability on animal health, growth, and reproduction, including through heat stress, and potential adaptation strategies. The rate of adoption of adaptation strategies by livestock producers will depend on perceptions of the uncertainty in projected climate and regional-scale impacts and associated risk. However, management changes adopted by farmers in parts of Australia during recent extended drought and associated heatwaves, trends consistent with long-term predicted climate patterns, provide some insights into the capacity for practical adaptation strategies. Animal production systems will also be significantly affected by climate change policy and national targets to address greenhouse gas emissions, since livestock are estimated to contribute ~10% of Australia’s total emissions and 8–11% of global emissions, with additional farm emissions associated with activities such as feed production. More than two-thirds of emissions are attributed to ruminant animals. This paper discusses the challenges and opportunities facing livestock industries in Australia in adapting to and mitigating climate change. It examines the research needed to better define practical options to reduce the emissions intensity of livestock products, enhance adaptation opportunities, and support the continued contribution of animal agriculture to Australia’s economy, environment, and regional communities.

Landscape ecology of the lesser grain borer, Rhyzopertha dominica

The Lesser Grain Borer is a major pest of stored grain with a global distribution. This project has, for the first time recorded this pest throughout broad spatial areas, tens of kilometres from grain production or storage. Statistical analysis revealed that different factors such as ambient temperature and the availability of food resources affect R. dominica differently between different habitats. This suggests that, contrary to the prevailing view, this pest is not solely dependent on stored wheat and can continue to persist throughout a range of habitats. These findings have important management implications for Australia's wheat industry.

Strong resistance to phosphine in the rusty grain beetle, Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae): its characterisation, a rapid assay for diagnosis and its distribution in Australia

BACKGROUND: The recent development of very high resistance to phosphine in rusty grain beetle, Cryptolestes ferrugineus (Stephens), seriously threatens stored-grain biosecurity. The aim was to characterise this resistance, to develop a rapid bioassay for its diagnosis to support pest management and to document the distribution of resistance in Australia in 20072011. RESULTS: Bioassays of purified laboratory reference strains and field-collected samples revealed three phenotypes: susceptible, weakly resistant and strongly resistant. With resistance factors of > 1000 x , resistance to phosphine expressed by the strong resistance phenotype was higher than reported for any stored-product insect species. The new time-to-knockdown assay rapidly and accurately diagnosed each resistance phenotype within 6 h. Although less frequent in western Australia, weak resistance was detected throughout all grain production regions. Strong resistance occurred predominantly in central storages in eastern Australia. CONCLUSION: Resistance to phosphine in the rusty grain beetle is expressed through two identifiable phenotypes: weak and strong. Strong resistance requires urgent changes to current fumigation dosages. The development of a rapid assay for diagnosis of resistance enables the provision of same-day advice to expedite resistance management decisions. (c) 2012 Commonwealth of Australia. Published by John Wiley & Sons, Ltd.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Predicting the response of wheat (Triticum aestivum L.) to liquid and granular phosphorus fertilisers in Australian soils

Liquid forms of phosphorus (P) have been shown to be more effective than granular P for promoting cereal growth in alkaline soils with high levels of free calcium carbonate on Eyre Peninsula, South Australia. However, the advantage of liquid over granular P forms of fertiliser has not been fully investigated across the wide range of soils used for grain production in Australia. A glasshouse pot experiment tested if liquid P fertilisers were more effective for growing spring wheat (Triticum aestivum L.) than granular P (monoammonium phosphate) in 28 soils from all over Australia with soil pH (H2O) ranging from 5.2 to 8.9. Application of liquid P resulted in greater shoot biomass, as measured after 4 weeks' growth (mid to late tillering, Feeks growth stage 2-3), than granular P in 3 of the acidic to neutral soils and in 3 alkaline soils. Shoot dry matter responses of spring wheat to applied liquid or granular P were related to soil properties to determine if any of the properties predicted superior yield responses to liquid P. The calcium carbonate content of soil was the only soil property that significantly contributed to predicting when liquid P was more effective than granular P. Five soil P test procedures (Bray, Colwell, resin, isotopically exchangeable P, and diffusive gradients in thin films (DGT)) were assessed to determine their ability to measure soil test P on subsamples of soil collected before the experiment started. These soil test values were then related to the dry matter shoot yields to assess their ability to predict wheat yield responses to P applied as liquid or granular P. All 5 soil test procedures provided a reasonable prediction of dry matter responses to applied P as either liquid or granular P, with the resin P test having a slightly greater predictive capacity on the range of soils tested. The findings of this investigation suggest that liquid P fertilisers do have some potential applications in non-calcareous soils and confirm current recommendations for use of liquid P fertiliser to grow cereal crops in highly calcareous soils. Soil P testing procedures require local calibration for response to the P source that is going to be used to amend P deficiency.

CRC40142 Defining the plant pathogen risk posed by international travellers

This project will define the plant pathogen incursion risk posed by people returning from overseas and interstate travel. This will be achieved through the development of technically sound sample/survey methodologies. The project will initially focus on cereal rusts. An assessment of the current level of human mediated rust entries into Australia will be determined through the sampling of travellers who have been known to have visited grain production regions overseas.