Net radiation dynamics: performance of 20 daily net radiation models as related to model structure and intricacy in two climates.

We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

Near infrared spectroscopy as a rapid non-invasive tool for agricultural and industrial process management with special reference to avocado and sandalwood industries

Near infrared spectroscopy (NIRS) can play a vital role as a cost effective, rapid, non-invasive, reproducible diagnostic tool for many environmental management, agricultural and industrial waste water monitoring applications. In this paper we highlight the ability of NIRS technology to be used as a diagnostic tool in agricultural and environmental applications through the successful assessment of Fourier Transform NIRS to predict α santalol in sandalwood chip samples, and maturity of ‘Hass’ avocado fruit based on dry matter content. Presented at the Third International Conference on Challenges in Environmental Science & Engineering, CESE-2010. 26 September – 1 October 2010, The Sebel, Cairns, Queensland, Australia.

Declining soil phosphorus reserves on sustainable agricultural production systems

PhD scholarship investigating the relative sensitivity of nitrogen fixation in adapted grain and ley legume species to low soil phosphorus.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

AG15 (Sustainable Agricultural State-level Investment Program) natural resource management extension in irrigated cotton and grain

Natural Resource Management project developing reources and supporting best practice management for irrigated cotton and grain growers in Queensland.

Implementation costs of Agricultural Management Practices for Water Quality Improvement in the Great Barrier Reef Catchments. CSIRO: Water for Healthy Country National Research Flagship

Executive summary. In this report we analyse implementation costs and benefits for agricultural management practices, grouped into farming systems. In order to do so, we compare plot scale gross margins for the dominant agricultural production systems (sugarcane, grazing and banana cultivation) in the NRM regions Wet Tropics, Burdekin Dry Tropics and Mackay Whitsundays. Furthermore, where available, we present investment requirements for changing to improved farming systems. It must be noted that transaction costs are not captured within this project. For sugarcane, this economic analysis shows that there are expected benefits to sugarcane growers in the different regions through transitions to C and B class farming systems. Further transition to A-class farming systems can come at a cost, depending on the capital investment required and the length of the investment period. Obviously, the costs and benefits will vary for each individual grower and will depend on their starting point and individual property scenario therefore each circumstance needs to be carefully considered before making a change in management practice. In grazing, overall, reducing stocking rates comes at a cost (reduced benefits). However, when operating at low utilisation rates in wetter country, lowering stocking rates can potentially come at a benefit. With win-win potential, extension is preferred to assist farmer in changing management practices to improve their land condition. When reducing stocking rates comes at a cost, incentives may be applicable to support change among farmers. For banana cultivation, the results indicate that the transition to C and B class management practices is a worthwhile proposition from an economic perspective. For a change from B to A class farming systems however, it is not worthwhile from a financial perspective. This is largely due to the large capital investment associated with the change in irrigation system and negative impact in whole of farm gross margin. Overall, benefits will vary for each individual grower depending on their starting point and their individual property scenario. The results presented in this report are one possible set of figures to show the changes in profitability of a grower operating in different management classes. The results in this report are not prescriptive of every landholder. Landholders will have different costs and benefits from transitioning to improved practices, even if similar operations are practiced, hence it is recommended that landholders that are willing to change management undertake their own research and analysis into the expected costs and benefits for their own soil types and property circumstances.

Predicting Additive and Non-additive Genetic Effects from Trials Where Traits Are Affected by Interplot Competition

There are two key types of selection in a plant breeding program, namely selection of hybrids for potential commercial use and the selection of parents for use in future breeding. Oakey et al. (in Theoretical and Applied Genetics 113, 809-819, 2006) showed how both of these aims could be achieved using pedigree information in a mixed model analysis in order to partition genetic effects into additive and non-additive effects. Their approach was developed for field trial data subject to spatial variation. In this paper we extend the approach for data from trials subject to interplot competition. We show how the approach may be used to obtain predictions of pure stand additive and non-additive effects. We develop the methodology in the context of a single field trial using an example from an Australian sorghum breeding program.

Agricultural intensification, priming for persistence and the emergence of Nipah virus: a lethal bat-borne zoonosis

Emerging zoonoses threaten global health, yet the processes by which they emerge are complex and poorly understood. Nipah virus (NiV) is an important threat owing to its broad host and geographical range, high case fatality, potential for human-to-human transmission and lack of effective prevention or therapies. Here, we investigate the origin of the first identified outbreak of NiV encephalitis in Malaysia and Singapore. We analyse data on livestock production from the index site (a commercial pig farm in Malaysia) prior to and during the outbreak, on Malaysian agricultural production, and from surveys of NiV's wildlife reservoir (flying foxes). Our analyses suggest that repeated introduction of NiV from wildlife changed infection dynamics in pigs. Initial viral introduction produced an explosive epizootic that drove itself to extinction but primed the population for enzootic persistence upon reintroduction of the virus. The resultant within-farm persistence permitted regional spread and increased the number of human infections. This study refutes an earlier hypothesis that anomalous El Nino Southern Oscillation-related climatic conditions drove emergence and suggests that priming for persistence drove the emergence of a novel zoonotic pathogen. Thus, we provide empirical evidence for a causative mechanism previously proposed as a precursor to widespread infection with H5N1 avian influenza and other emerging pathogens.

Modelling interactions between farm-level structural adjustment and a regional economy: A case of the Australian rice industry

Climate change and on-going water policy reforms will likely contribute to on-farm and regional structural adjustment in Australia. This paper gathers empirical evidence of farm-level structural adjustments and integrates these with a regional equilibrium model to investigate sectoral and regional impacts of climate change and recent water use policy on rice industry. We find strong evidence of adjustments to the farming system, enabled by existing diversity in on-farm production. A further loss of water with additional pressures to adopt less intensive and larger-scale farming, will however reduce the net number of farm businesses, which may affect regional rice production. The results from a regional CGE model show impacts on the regional economy over and above the direct cost of the environmental water, although a net reduction in real economic output and real income is partially offset by gains in rest of the Australia through the reallocation or resources. There is some interest within the industry and from potential new corporate entrants in the relocation of some rice production to the north. However, strong government support would be crucial to implement such relocation.

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.

Good science for improving policy: greenhouse gas emissions from agricultural manures

Australia’s and New Zealand’s major agricultural manure management emission sources are reported to be, in descending order of magnitude: (1) methane (CH4) from dairy farms in both countries; (2) CH4 from pig farms in Australia; and nitrous oxide (N2O) from (3) beef feedlots and (4) poultry sheds in Australia. We used literature to critically review these inventory estimates. Alarmingly for dairy farm CH4 (1), our review revealed assumptions and omissions that when addressed could dramatically increase this emission estimate. The estimate of CH4 from Australian pig farms (2) appears to be accurate, according to industry data and field measurements. The N2O emission estimates for beef feedlots (3) and poultry sheds (4) are based on northern hemisphere default factors whose appropriateness for Australia is questionable and unverified. Therefore, most of Australasia’s key livestock manure management greenhouse gas (GHG) emission profiles are either questionable or are unsubstantiated by region-specific research. Encouragingly, GHG from dairy shed manure are relatively easy to mitigate because they are a point source which can be managed by several ‘close-to-market’ abatement solutions. Reducing these manure emissions therefore constitutes an opportunity for meaningful action sooner compared with the more difficult-to-implement and long-term strategies that currently dominate agricultural GHG mitigation research. At an international level, our review highlights the critical need to carefully reassess GHG emission profiles, particularly if such assessments have not been made since the compilation of original inventories. Failure to act in this regard presents the very real risk of missing the ‘low hanging fruit’ in the rush towards a meaningful response to climate change

Allelopathy for weed control in agricultural systems

Weeds are a hidden foe for crop plants, interfering with their functions and suppressing their growth and development. Yield losses of ∼34 are caused by weeds among the major crops, which are grown worldwide. These yield losses are higher than the losses caused by other pests in the crops. Sustainable weed management is needed in the wake of a huge decline in crop outputs due to weed pressure. A diversity in weed management tools ensures sustainable weed control and reduces chances of herbicide resistance development in weeds. Allelopathy as a tool, can be importantly used to combat the challenges of environmental pollution and herbicide resistance development. This review article provides a recent update regarding the practical application of allelopathy for weed control in agricultural systems. Several studies elaborate on the significance of allelopathy for weed management. Rye, sorghum, rice, sunflower, rape seed, and wheat have been documented as important allelopathic crops. These crops express their allelopathic potential by releasing allelochemicals which not only suppress weeds, but also promote underground microbial activities. Crop cultivars with allelopathic potentials can be grown to suppress weeds under field conditions. Further, several types of allelopathic plants can be intercropped with other crops to smother weeds. The use of allelopathic cover crops and mulches can reduce weed pressure in field crops. Rotating a routine crop with an allelopathic crop for one season is another method of allelopathic weed control. Importantly, plant breeding can be explored to improve the allelopathic potential of crop cultivars. In conclusion, allelopathy can be utilized for suppressing weeds in field crops. Allelopathy has a pertinent significance for ecological, sustainable, and integrated weed management systems.

Queensland Agricultural Journal Volume 13 Parts 1-6 July to December 1903

General Index Vol 13 Parts 1-6, pages 1-81

Consumption of crops by feral pigs (Sus scrofa) in a fragmented agricultural landscape

Feral pigs (Sus scrofa) consume and damage crops and impact the environment through predation, competition and habitat disturbance, although supporting dietary data are lacking in agricultural landscapes. This study was undertaken to determine the relative importance of food items in the diet of feral pigs in a fragmented agricultural landscape, particularly to assist in predicting the breadth of likely impacts. Diet composition was assessed from the stomach contents of 196 feral pigs from agricultural properties in southern Queensland. Feral pigs were herbivorous, with plant matter comprising >99% of biomass consumed. Crops were consumed more frequently than non-crop species, and comprised >60% of dietary biomass, indicating a clear potential for direct economic losses. Consumption of pasture and forage species also suggests potential competition for pasture with domestic stock. There is little evidence of direct predation on native fauna, but feral pig feeding activities may impact environmental values. Seasonal differences in consumption of crop, pasture or animal food groups probably reflect the changing availability of food items. We recommend that future dietary studies examine food availability to determine any dietary preferences to assist in determining the foods most susceptible to damage. The outcomes of this study are important for developing techniques for monitoring the impacts of feral pigs, essential for developing management options to reduce feral pig damage on agricultural lands.