Carbon Capture and Productivity of Plantation Forests in North-eastern Australia

Approximately 130,000 ha of hardwood plantations have been established in north-eastern Australia in the last 15 years. As a result of poor taxa selection approximately 25,000 ha have failed due to drought, pest and disease or extreme weather events (drought and cyclones). Given the predicted impacts of climate change in north-eastern Australia (reduced rainfall, increased temperatures and an increase in extreme weather conditions, particularly drought, storms and cyclones), selection of the right taxa for plantation development is even more critical as the taxon planted needs to be able to perform well under the environments experienced at planting as well as those that may develop over in 30 years time as a result of changing climate.

Intensity, productivity and efficiency in agriculture in Finland and implications for N and P fertiliser management

The purpose of this study was to evaluate intensity, productivity and efficiency in agriculture in Finland and show implications for N and P fertiliser management. Environmental concerns relating to agricultural production have been and still are focused on arguments about policies that affect agriculture. These policies constrain production while demand for agricultural products such as food, fibre and energy continuously increase. Therefore the importance of increasing productivity is a great challenge to agriculture. Over the last decades producers have experienced several large changes in the production environment such as the policy reform when Finland joined the EU 1995. Other and market changes occurred with the further EU enlargement with neighbouring countries in 2005 and with the decoupling of supports over the 2006-2007 period. Decreasing prices a decreased number of farmers and decreased profitability in agricultural production have resulted from these changes and constraints and of technological development. It is known that the accession to the EU 1995 would herald changes in agriculture. Especially of interest was how the sudden changes in prices of commodities on especially those of cereals, decreased by 60%, would influence agricultural production. The knowledge of properties of the production function increased in importance as a consequence of price changes. A research on the economic instruments to regulate productions was carried out and combined with earlier studies in paper V. In paper I the objective was to compare two different technologies, the conventional farming and the organic farming, determine differences in productivity and technical efficiency. In addition input specific or environmental efficiencies were analysed. The heterogeneity of agricultural soils and its implications were analysed in article II. In study III the determinants of technical inefficiency were analysed. The aspects and possible effects of the instability in policies due to a partial decoupling of production factors and products were studied in paper IV. Consequently connection between technical efficiency based on the turnover and the sales return was analysed in this study. Simple economic instruments such as fertiliser taxes have a direct effect on fertiliser consumption and indirectly increase the value of organic fertilisers. However, fertiliser taxes, do not fully address the N and P management problems adequately and are therefore not suitable for nutrient management improvements in general. Productivity of organic farms is lower on average than conventional farms and the difference increases when looking at selling returns only. The organic sector needs more research and development on productivity. Livestock density in organic farming increases productivity, however, there is an upper limit to livestock densities on organic farms and therefore nutrient on organic farms are also limited. Soil factors affects phosphorous and nitrogen efficiency. Soils like sand and silt have lower input specific overall efficiency for nutrients N and P. Special attention is needed for the management on these soils. Clay soils and soils with moderate clay content have higher efficiency. Soil heterogeneity is cause for an unavoidable inefficiency in agriculture.

Informational efficiency of the European Union emission allowance market

This thesis studies the informational efficiency of the European Union emission allowance (EUA) market. In an efficient market, the market price is unpredictable and profits above average are impossible in the long run. The main research problem is does the EUA price follow a random walk. The method is an econometric analysis of the price series, which includes an autocorrelation coefficient test and a variance ratio test. The results reveal that the price series is autocorrelated and therefore a nonrandom walk. In order to find out the extent of predictability, the price series is modelled with an autoregressive model. The conclusion is that the EUA price is autocorrelated only to a small degree and that the predictability cannot be used to make extra profits. The EUA market is therefore considered informationally efficient, although the price series does not fulfill the requirements of a random walk. A market review supports the conclusion, but it is clear that the maturing of the market is still in process.

Water-use efficiency and productivity trends in Australian irrigated cotton: a review

The aim of this review is to report changes in irrigated cotton water use from research projects and on-farm practice-change programs in Australia, in relation to both plant-based and irrigation engineering disciplines. At least 80% of the Australian cotton-growing area is irrigated using gravity surface-irrigation systems. This review found that, over 23 years, cotton crops utilise 6-7ML/ha of irrigation water, depending on the amount of seasonal rain received. The seasonal evapotranspiration of surface-irrigated crops averaged 729mm over this period. Over the past decade, water-use productivity by Australian cotton growers has improved by 40%. This has been achieved by both yield increases and more efficient water-management systems. The whole-farm irrigation efficiency index improved from 57% to 70%, and the crop water use index is >3kg/mm.ha, high by international standards. Yield increases over the last decade can be attributed to plant-breeding advances, the adoption of genetically modified varieties, and improved crop management. Also, there has been increased use of irrigation scheduling tools and furrow-irrigation system optimisation evaluations. This has reduced in-field deep-drainage losses. The largest loss component of the farm water balance on cotton farms is evaporation from on-farm water storages. Some farmers are changing to alternative systems such as centre pivots and lateral-move machines, and increasing numbers of these alternatives are expected. These systems can achieve considerable labour and water savings, but have significantly higher energy costs associated with water pumping and machine operation. The optimisation of interactions between water, soils, labour, carbon emissions and energy efficiency requires more research and on-farm evaluations. Standardisation of water-use efficiency measures and improved water measurement techniques for surface irrigation are important research outcomes to enable valid irrigation benchmarks to be established and compared. Water-use performance is highly variable between cotton farmers and farming fields and across regions. Therefore, site-specific measurement is important. The range in the presented datasets indicates potential for further improvement in water-use efficiency and productivity on Australian cotton farms.

Responses of Super Rice (Oryza sativa L.) to Different Planting Methods for Grain Yield and Nitrogen-Use Efficiency in the Single Cropping Season

To break the yield ceiling of rice production, a super rice project was developed in 1996 to breed rice varieties with super high yield. A two-year experiment was conducted to evaluate yield and nitrogen (N)-use response of super rice to different planting methods in the single cropping season. A total of 17 rice varieties, including 13 super rice and four non-super checks (CK), were grown under three N levels [0 (N0), 150 (N150), and 225 (N225) kg ha−1] and two planting methods [transplanting (TP) and direct-seeding in wet conditions (WDS)]. Grain yield under WDS (7.69 t ha−1) was generally lower than TP (8.58 t ha−1). However, grain yield under different planting methods was affected by N rates as well as variety groups. In both years, there was no difference in grain yield between super and CK varieties at N150, irrespective of planting methods. However, grain yield difference was dramatic in japonica groups at N225, that is, there was an 11.3% and 14.1% average increase in super rice than in CK varieties in WDS and TP, respectively. This suggests that high N input contributes to narrowing the yield gap in super rice varieties, which also indicates that super rice was bred for high fertility conditions. In the japonica group, more N was accumulated in super rice than in CK at N225, but no difference was found between super and CK varieties at N0 and N150. Similar results were also found for N agronomic efficiency. The results suggest that super rice varieties have an advantage for N-use efficiency when high N is applied. The response of super rice was greater under TP than under WDS. The results suggest that the need to further improve agronomic and other management practices to achieve high yield and N-use efficiency for super rice varieties in WDS.

Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics

Stay-green plants retain green leaves longer after anthesis and can have improved yield, particularly under water limitation. As senescence is a dynamic process, genotypes with different senescence patterns may exhibit similar final normalised difference vegetative index (NDVI). By monitoring NDVI from as early as awn emergence to maturity, we demonstrate that analysing senescence dynamics improves insight into genotypic stay-green variation. A senescence evaluation tool was developed to fit a logistic function to NDVI data and used to analyse data from three environments for a wheat (Triticum aestivum L.) population whose lines contrast for stay-green. Key stay-green traits were estimated including, maximum NDVI, senescence rate and a trait integrating NDVI variation after anthesis, as well as the timing from anthesis to onset, midpoint and conclusion of senescence. The integrative trait and the timing to onset and mid-senescence exhibited high positive correlations with yield and a high heritability in the three studied environments. Senescence rate was correlated with yield in some environments, whereas maximum NDVI was associated with yield in a drought-stressed environment. Where resources preclude frequent measurements, we found that NDVI measurements may be restricted to the period of rapid senescence, but caution is required when dealing with lines of different phenology. In contrast, regular monitoring during the whole period after flowering allows the estimation of senescence dynamics traits that may be reliably compared across genotypes and environments. We anticipate that selection for stay-green traits will enhance genetic progress towards high-yielding, stay-green germplasm.

Discovering hidden structures in molecular data using a Bayesian partition model approach

Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

Sugarcane productivity response to different fallow and soybean residue management practices in the Bundaberg district

GRAIN LEGUME ROTATIONS underpin the sustainability of the Australian sugarcane farming system, offering a number of soil health and environmental benefits. Recent studies have highlighted the potential for these breaks to exacerbate nitrous oxide (N2O) emissions. An experiment was implemented in 2012 to evaluate the impact of two fallow management options (bare fallow and soybean break crop) and different soybean residue management practices on N2O emissions and sugarcane productivity. The bare fallow plots were conventionally tilled, whereas the soybean treatments were either tilled, not tilled, residue sprayed with nitrification inhibitor (DMPP) prior to tillage or had a triticale ‘catch crop’ sown between the soybean and sugarcane crops. The fallow plots received either no nitrogen (N0) or fully fertilised (N145) whereas the soybean treatments received 25 kg N/ha at planting only. The Fallow N145 treatment yielded 8% more cane than the soybean tilled treatment. However there was no statistical difference in sugar productivity. Cane yield was correlated with stalk number that was correlated to soil mineral nitrogen status in January. There was only 30% more N/ha in the above-ground biomass between the Fallow N145 and the Fallow N0 treatment; highlighting poor fertiliser nitrogen use efficiency. Supplying adequate nitrogen to meet productivity requirements without causing environmental harm remains a challenge for the Australian sugar industry. The soybean direct drill treatment significantly reduced N2O emissions and produced similar yields and profitability to the soybean tilled treatment (outlined in a companion paper by Wang et.al. in these proceedings). Furthermore, this study has highlighted that the soybean direct drill technique provides an opportunity to enable grain legume cropping in the sugarcane farming system to capture all of the soil health/environmental benefits without exacerbating N2O emissions from Australian sugarcane soils.

‘How to’ guide for measuring fan performance and efficiency in meat chicken sheds

This ‘how to’ guide provides readers with method to measure fan performance and energy efficiency of fans installed in meat chicken sheds. These methods are also useful for identifying fans that are under-performing or require maintenance. For more information about fan energy efficiency, a complementary report is available on the RIRDC website ‘Review of fan efficiency in meat chicken sheds’ (RIRDC Publication No. 15/018). A spreadsheet was also developed under this project for comparing and ranking fans against others in terms of energy efficiency, air flow and costs (‘Tunnel Ventilation Fan Comparison Spreadsheet’), and is available on the RIRDC website.

Small-scale capture, transport and tank adaptation of live, medium-sized Scombrids using "Tuna Tubes"

The transport of live fish is a crucial step to establish fish culture in captivity, and is especially challenging for species that have not been commonly cultured before, therefore transport and handling methods need to be optimized and tailored. This study describes the use of tuna tubes for small-scale transport of medium-sized pelagic fish from the Scombridae family. Tuna tubes are an array of vertical tubes that hold the fish, while fresh seawater is pumped up the tubes and through the fish mouth and gills, providing oxygen and removing wastes. In this study, 19 fish were captured using rod and line and 42% of the captured fish were transported alive in the custom-designed tuna tubes to an on-shore holding tank: five mackerel tuna (Euthynnus affinis) and three leaping bonito (Cybiosarda elegans). Out of these, just three (15.8% of total fish) acclimatized to the tank's condition. Based on these results, we discuss an improved design of the tuna tubes that has the potential to increase survival rates and enable a simple and low cost method of transporting of live pelagic fish.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.