An exploratory study on the commercialisation of heat pump-fluidised bed drying technology

Fluidised bed-heat pump drying technology offers distinctive advantages over the existing drying technology employed in the Australian food industry. However, as is the case with many other examples of innovations that have had clear relative advantages, the rates of adoption and diffusion of this technology have been very slow. "Why does this happen?" is the theme of this research study that has been undertaken with an objective to analyse a range of issues related to the market acceptance of technological innovations. The research methodology included the development of an integrated conceptual model based on an extensive review of literature in the areas of innovation diffusion, technology transfer and industrial marketing. Three major determinants associated with the market acceptance of innovations were identified as the characteristics of the innovation, adopter information processing capability and the influence of the innovation supplier on the adoption process. This was followed by a study involving more than 30 small and medium enterprises identified as potential adopters of fluidised bed-heat pump drying technology in the Australian food industry. The findings revealed that judgment was the key evaluation strategy employed by potential adopters in the particular industry sector. Further, it was evidenced that the innovations were evaluated against a predetermined criteria covering a range of aspects with emphasis on a selected set of attributes of the innovation. Implication of these findings on the commercialisation of fluidised bed-heat pump drying technology was established, and a series of recommendations was made to the innovation supplier (DPI/FT) enabling it to develop an effective commercialisation strategy.

Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Forest health surveillance methodology in hardwood plantations in Queensland, Australia

Forest health surveillance (FHS) of hardwood plantations commenced in Queensland in 1997 as plantations expanded following a state government planting initiative arising from the national 2020 forest policy vision. The estate was initially characterised by a large number of small plantations (10-50 ha), although this has changed more recently with the concentration of larger plantations in the central coast and South Burnett regions. Due to the disparate nature of the resource, drive- and walkthrough surveys of subsets of plantations have been undertaken in preference to aerial surveys. FHS has been effective in detecting a number of new hardwood pests in Queensland including erinose mites (Rhombacus and Acalox spp.), western white gum plate galler (Ophelimus sp.), Creiis psyllid and bronzing bug (Thaumastocoris sp.), in evaluating their potential impact and assisting in focussing future research efforts. Since 2003 there has been an increased emphasis on training operational staff to take a greater role in identifying and reporting on forest health issues. This has increased their awareness of forest health issues, but their limited time to specifically survey and report on pests and diseases, and high rates of staff turnover, necessitate frequent ongoing training. Consequently, common and widespread problems such as quambalaria shoot blight (Quambalaria pitereka), chrysomelid leaf beetles (mainly Paropsis atomaria) and erinose mites may be under-reported or not reported, and absence data may often not be recorded at all. Comment is made on the future directions that FHS may take in hardwood plantations in Queensland.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

High-resolution melt-curve analysis of random-amplified-polymorphic-DNA markers, for the characterisation of pathogenic Leptospira.

A new test for pathogenic Leptospira isolates, based on RAPD-PCR and high-resolution melt (HRM) analysis (which measures the melting temperature of amplicons in real time, using a fluorescent DNA-binding dye), has recently been developed. A characteristic profile of the amplicons can be used to define serovars or detect genotypes. Ten serovars, of leptospires from the species Leptospira interrogans (serovars Australis, Robinsoni, Hardjo, Pomona, Zanoni, Copenhageni and Szwajizak), L. borgpetersenii (serovar Arborea), L. kirschneri (serovar Cynopteri) and L. weilii (serovar Celledoni), were typed against 13 previously published RAPD primers, using a real-time cycler (the Corbett Life Science RotorGene 6000) and the optimised reagents from a commercial kit (Quantace SensiMix). RAPD-HRM at specific temperatures generated defining amplicon melt profiles for each of the tested serovars. These profiles were evaluated as difference-curve graphs generated using the RotorGene software package, with a cut-off of at least 8 'U' (plus or minus). The results demonstrated that RAPD-HRM can be used to measure serovar diversity and establish identity, with a high degree of stability. The characterisation of Leptospira serotypes using a DNA-based methodology is now possible. As an objective and relatively inexpensive and rapid method of serovar identification, at least for cultured isolates, RAPD-HRM assays show convincing potentia.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

Increasing vegetable consumption: a means-end chain approach

Purpose – The purpose of this study is to illustrate how means-end chain theory can inform communications that effectively convey the health messages of vegetable consumption to various publics. Design/methodology/approach – Laddering interviews were conducted with 61 participants who consumed at least two serves of vegetables a day and were responsible in part or whole for shopping in their household. A means-end chain value map was then constructed using mecanalyst software. Findings – Using means-end theory, an example communications strategy was developed from the dominant chain. The health and wellness features that respondents associated with vegetables were “freshness”, a “source of vitamins and minerals”, and “high nutritional value”. In the mind of the consumer, these features were linked to the benefit concept “maintain energy and vitality”, which in turn was connected to the consequence “maintain an active life”. The end-states or goals participants ultimately connected to the health and wellness features of vegetables were that of “enjoy life” and “achieve goals”. Research limitations/implications – The research is limited in so far as subjects who consume less than two serves of vegetables are not recruited for this study. Practical implications – It is suggested that social marketing initiatives designed to increase vegetable consumption may base messages on health-related values or end-states of being to resonate more effectively with consumers. Social implications – High vegetable consumption is associated with a reduced risk of chronic disease. Effective strategies designed to increase vegetable consumption amongst populations may reduce the burden on health systems. Originality/value – This study illustrates how consumers' cognitive processes can inform social marketing communications.

Breedcow and Dynama software redevelopment

The project renewed the Breedcow and Dynama software making it compatible with modern computer operating systems and platforms. Enhancements were also made to the linkages between the individual programs and their operation. The suite of programs is a critical component of the skill set required to make soundly based plans and production choices in the north Australian beef industry.

Improved methodology for introducing threatened hatchery reared fish

Eel tailed catfish, silver perch and Murray cod are three key recreational fishing species that have declined in the Murray-Darling Basin region. This research project will be an important step towards developing methods to restore and enhance stocks of these fish.

Australian Tropical Grains Germplasm Centre

DAQ00131 project activities aimed to: conserve tropical grains germplasm under long-term storage conditions; acquire new germplasm with unique traits of interest to clients (particularly to breeding programs); the maintenance of germplasm through viability testing and regeneration; and to increase awareness of the availability of tropical grains germplasm to clients. New project goals were to facilitate the creation of the national grains Genetic Resources Centre (GRC) and included training GRC staff in the use of GRIN-Global (GG), a software management system, so that grains data can be nationalised across Australia; and contribute to the action plan development for the relocation of tropical grains germplasm to both Tamworth and Horsham.

NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N-e) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.