Influence of different nitrogen rates and DMPP nitrification inhibitor on annual N2/O emissions from a subtropical wheat–maize cropping system

Global cereal production will need to increase by 50% to 70% to feed a world population of about 9 billion by 2050. This intensification is forecast to occur mostly in subtropical regions, where warm and humid conditions can promote high N2O losses from cropped soils. To secure high crop production without exacerbating N2O emissions, new nitrogen (N) fertiliser management strategies are necessary. This one-year study evaluated the efficacy of a nitrification inhibitor (3,4-dimethylpyrazole phosphate—DMPP) and different N fertiliser rates to reduce N2O emissions in a wheat–maize rotation in subtropical Australia. Annual N2O emissions were monitored using a fully automated greenhouse gas measuring system. Four treatments were fertilized with different rates of urea, including a control (40 kg-N ha−1 year−1), a conventional N fertiliser rate adjusted on estimated residual soil N (120 kg-N ha−1 year−1), a conventional N fertiliser rate (240 kg-N ha−1 year−1) and a conventional N fertiliser rate (240 kg-N ha−1 year−1) with nitrification inhibitor (DMPP) applied at top dressing. The maize season was by far the main contributor to annual N2O emissions due to the high soil moisture and temperature conditions, as well as the elevated N rates applied. Annual N2O emissions in the four treatments amounted to 0.49, 0.84, 2.02 and 0.74 kg N2O–N ha−1 year−1, respectively, and corresponded to emission factors of 0.29%, 0.39%, 0.69% and 0.16% of total N applied. Halving the annual conventional N fertiliser rate in the adjusted N treatment led to N2O emissions comparable to the DMPP treatment but extensively penalised maize yield. The application of DMPP produced a significant reduction in N2O emissions only in the maize season. The use of DMPP with urea at the conventional N rate reduced annual N2O emissions by more than 60% but did not affect crop yields. The results of this study indicate that: (i) future strategies aimed at securing subtropical cereal production without increasing N2O emissions should focus on the fertilisation of the summer crop; (ii) adjusting conventional N fertiliser rates on estimated residual soil N is an effective practice to reduce N2O emissions but can lead to substantial yield losses if the residual soil N is not assessed correctly; (iii) the application of DMPP is a feasible strategy to reduce annual N2O emissions from sub-tropical wheat–maize rotations. However, at the N rates tested in this study DMPP urea did not increase crop yields, making it impossible to recoup extra costs associated with this fertiliser. The findings of this study will support farmers and policy makers to define effective fertilisation strategies to reduce N2O emissions from subtropical cereal cropping systems while maintaining high crop productivity. More research is needed to assess the use of DMPP urea in terms of reducing conventional N fertiliser rates and subsequently enable a decrease of fertilisation costs and a further abatement of fertiliser-induced N2O emissions.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Increase in β-Ionone, a Carotenoid-Derived Volatile in Zeaxanthin-Biofortified Sweet Corn

Carotenoids are responsible for the yellow color of sweet corn (Zea mays var. saccharata), but are also potentially the source of flavor compounds from the cleavage of carotenoid molecules. The carotenoid-derived volatile, -ionone, was identified in both standard yellow sweet corn (Hybrix5) and a zeaxanthin-enhanced experimental variety (HZ) designed for sufferers of macular degeneration. As -ionone is highly perceivable at extremely low concentration by humans, it was important to confirm if alterations in carotenoid profile may also affect flavor volatiles. The concentration of -ionone was most strongly correlated (R2 > 0.94) with the -arm carotenoids, -carotene, -cryptoxanthin, and zeaxanthin, and to a lesser degree (R2 = 0.90) with the α-arm carotenoid, zeinoxanthin. No correlation existed with either lutein (R2 = 0.06) or antheraxanthin (R2 = 0.10). Delaying harvest of cobs resulted in a significant increase of both carotenoid and -ionone concentrations, producing a 6-fold increase of ?-ionone in HZ and a 2-fold increase in Hybrix5, reaching a maximum of 62g/kg FW and 24g/kg FW, respectively.

Investigation of the microbial metabolism of carbon dioxide and hydrogen in the kangaroo foregut by stable isotope probing

Kangaroos ferment forage material in an enlarged forestomach analogous to the rumen, but in contrast to ruminants, they produce little or no methane. The objective of this study was to identify the dominant organisms and pathways involved in hydrogenotrophy in the kangaroo forestomach, with the broader aim of understanding how these processes are able to predominate over methanogenesis. Stable isotope analysis of fermentation end products and RNA stable isotope probing (RNA-SIP) were used to investigate the organisms and biochemical pathways involved in the metabolism of hydrogen and carbon dioxide in the kangaroo forestomach. Our results clearly demonstrate that the activity of bacterial reductive acetogens is a key factor in the reduced methane output of kangaroos. In in vitro fermentations, the microbial community of the kangaroo foregut produced very little methane, but produced a significantly greater proportion of acetate derived from carbon dioxide than the microbial community of the bovine rumen. A bacterial operational taxonomic unit closely related to the known reductive acetogen Blautia coccoides was found to be associated with carbon dioxide and hydrogen metabolism in the kangaroo foregut. Other bacterial taxa including members of the genera Prevotella, Oscillibacter and Streptococcus that have not previously been reported as containing hydrogenotrophic organisms were also significantly associated with metabolism of hydrogen and carbon dioxide in the kangaroo forestomach.The ISME Journal advance online publication, 13 March 2014; doi:10.1038/ismej.2014.25.

Drought adaptation of stay-green sorghum is associated with canopy development, leaf anatomy, root growth, and water uptake

Stay-green sorghum plants exhibit greener leaves and stems during the grain-filling period under water-limited conditions compared with their senescent counterparts, resulting in increased grain yield, grain mass, and lodging resistance. Stay-green has been mapped to a number of key chromosomal regions, including Stg1, Stg2, Stg3, and Stg4, but the functions of these individual quantitative trait loci (QTLs) remain unclear. The objective of this study was to show how positive effects of Stg QTLs on grain yield under drought can be explained as emergent consequences of their effects on temporal and spatial water-use patterns that result from changes in leaf-area dynamics. A set of four Stg near-isogenic lines (NILs) and their recurrent parent were grown in a range of field and semicontrolled experiments in southeast Queensland, Australia. These studies showed that the four Stg QTLs regulate canopy size by: (1) reducing tillering via increased size of lower leaves, (2) constraining the size of the upper leaves; and (3) in some cases, decreasing the number of leaves per culm. In addition, they variously affect leaf anatomy and root growth. The multiple pathways by which Stg QTLs modulate canopy development can result in considerable developmental plasticity. The reduction in canopy size associated with Stg QTLs reduced pre-flowering water demand, thereby increasing water availability during grain filling and, ultimately, grain yield. The generic physiological mechanisms underlying the stay-green trait suggest that similar Stg QTLs could enhance post-anthesis drought adaptation in other major cereals such as maize, wheat, and rice.

Identifying risk-efficient strategies using stochastic frontier analysis and simulation: An application to irrigated cropping in Australia

In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

Dietary media for mass rearing of rusty grain beetle, Cryptolestes ferrugineus (Stephens) and flat grain beetle, Cryptolestes pusillus (Schonherr) (Coleoptera: Cucujidae)

We developed a suitable diet for mass rearing of Cryptolestes ferrugineus (Stephens) populations under laboratory conditions. Recently, this pest has developed strong level of resistance to phosphine in Australia, and therefore, a significant amount of research has been directed towards its management. In total, nineteen grain-based diets, containing rolled oats, various combinations of cracked grains and flours of wheat, sorghum, maize and barley were tested. Each diet contained a small proportion of wheat germ (4.5% w/w) and torula yeast (0.5% w/w). Experiments were conducted at fixed temperature and relative humidity regimes of 30 ± 2 °C and 70 ± 2%, respectively, and replicated three times. Adults (n = 40) of a laboratory strain of C. ferrugineus were introduced into each diet, removed after 14 days and total numbers of live adult progeny were recorded. The following diets resulted in highest live progeny production: barley flour (95%) (607.67 ± 11.21) = rolled oats (75%) + cracked sorghum (20%) (597.33 ± 33.79) ≥ wheat flour (47.5%) + barley flour (47.5%) (496.67 ± 52.93) > cracked sorghum (95%) (384.00 ± 60.66). The performance of these four diets was then tested with field-collected populations of C. ferrugineus and Cryptolestes pusillus (Schonherr). The diets based on rolled oats + cracked sorghum, wheat flour + barley flour, and barley flour alone consistently produced highest progeny numbers in field-collected populations of both species, with mean progeny numbers ranging from 359.9 to 478.5. The multiplication of C. pusillus was significantly higher than C. ferrugineus on all four diets. Our findings will help in mass rearing of healthy cultures of C. ferrugineus and C. pusillus that will greatly facilitate laboratory and field research and in particular, in developing management tactics for these species.

Networks of stored grain diseases and pests: Strategies for sampling and mitigation

Pathogens and pests of stored grains move through complex dynamic networks linking fields, farms, and bulk storage facilities. Human transport and other forms of dispersal link the components of this network. A network model for pathogen and pest movement through stored grain systems is a first step toward new sampling and mitigation strategies that utilize information about the network structure. An understanding of network structure can be applied to identifying the key network components for pathogen or pest movement through the system. For example, it may be useful to identify a network node, such as a local grain storage facility, through which grain from a large number of fields will be accumulated and move through the network. This node may be particularly important for sampling and mitigation. In some cases more detailed information about network structure can identify key nodes that link two large sections of the network, such that management at the key nodes will greatly reduce the risk of spread between the two sections. In addition to the spread of particular species of pathogens and pests, we also evaluate the spread of problematic subpopulations, such as subpopulations with pesticide resistance. We present an analysis of stored grain pathogen and pest networks for Australia and the United States.

Complementary forages – integration at a whole-farm level

A high proportion of the Australian and New Zealand dairy industry is based on a relatively simple, low input and low cost pasture feedbase. These factors enable this type of production system to remain internationally competitive. However, a key limitation of pasture-based dairy systems is periodic imbalances between herd intake requirements and pasture DM production, caused by strong seasonality and high inter-annual variation in feed supply. This disparity can be moderated to a certain degree through the strategic management of the herd through altering calving dates and stocking rates, and the feedbase by conserving excess forage and irrigating to flatten seasonal forage availability. Australasian dairy systems are experiencing emerging market and environmental challenges, which includes increased competition for land and water resources, decreasing terms of trade, a changing and variable climate, an increasing environmental focus that requires improved nutrient and water-use efficiency and lower greenhouse gas emissions. The integration of complementary forages has long been viewed as a means to manipulate the home-grown feed supply, to improve the nutritive value and DM intake of the diet, and to increase the efficiency of inputs utilised. Only recently has integrating complementary forages at the whole-farm system level received the significant attention and investment required to examine their potential benefit. Recent whole-of-farm research undertaken in both Australia and New Zealand has highlighted the importance of understanding the challenges of the current feedbase and the level of complementarity between forage types required to improve profit, manage risk and/or alleviate/mitigate against adverse outcomes. This paper reviews the most recent systems-level research into complementary forages, discusses approaches to modelling their integration at the whole-farm level and highlights the potential of complementary forages to address the major challenges currently facing pasture-based dairy systems.

Evaluating pasture species for less fertile soils in a subtropical aseasonal low rainfall zone

Grasses, legumes, saltbushes and herbs were evaluated at 6 sites in southern inland Queensland to identify potential pasture and forage plants for use on marginal cropping soils. The region experiences summer heat waves and severe winter frosts. Emphasis was on perennial plants, and native species were included. Seedlings were transplanted into the unfertilized fields in either summer or autumn to suit the growing season of plants, and watered to ensure estab-lishment. Summer-growing grasses were the most successful group, while cool season-growing perennials mostly failed. Summer legumes were disappointing, with Stylosanthes scabra and Indigofera schimperi performing best. Some lines such as I. schimperi and the Eragrostis hybrid cv. Cochise were assessed as potential weeds owing to low animal acceptance. Native Rhynchosia minima grew well at some sites and deserves more study. Cenchrus ciliaris was always easy to establish and produced the highest yields. Persistence of some Digitaria and Bothriochloa species, Eragrostis curvula and Fingerhuthia africana at specific sites was encouraging, but potential weediness needs careful assessment. Standard species were identified to represent the main forage types, such as Austrostipa scabra for cool season-growing grasses, for incorporation into future trials with new genetic materials. The early field testing protocol used should be considered for use elsewhere, if unreliable rainfall poses a high risk of establishment failure from scarce seed.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.