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Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype × environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

Facing with growing data volumes and deeper analysis requirements, current development of Business Intelligence (BI) and Data warehousing systems (DWHs) is a challenging and complicated task, which largely involves in ad-hoc integration and data re-engineerng. This arises an increasing requirement for a scalable application framework which can be used for the implementation and administration of diverse BI appliations in a straight forward and cost-efficient way. In this context, this paper presents a large-scale application framework for standardized BI applications, suporting the ability to define and construct data warehouse processes, new data analytics capabilities as well as to support the deployment requirements of multiscalable front-end applications. The core of the framework consists of defined metadata repositories with pre-built and function specific information templates as well as application definition. Moreover, the application framework is also based on workflow mechanisms for developing and running automatic data processing tasks. Hence, the framework is capable of offering an unified reference architecture to end users, which spans various aspects of development lifecycle and can be adapted or extended to better meet application- specific BI engineering process.

In regions where rainfall is low and variable, water stored in the soil profile prior to sowing can alter yield expectation and hence management decisions. Thus, wheat farmers in Mediterranean regions may be able to benefit from knowing the amount of soil water at sowing by optimising their nitrogen (N) fertiliser management and by deciding on whether or not to sow a crop. We used the ASPIM-Nwheat model to explore how levels of plant available soil water (PAW) at sowing, N fertiliser rate, soil, site and season-type (below or above median rainfall) affected wheat yields at sites in the Mediterranean area of southwest Australia. Overall, the greatest influence on yield potential and the consequent N fertilisation requirement was season-type. The additional yield per mm PAW at sowing was generally higher in seasons with below median rainfall, except when yields were severely water-limited by below median rainfall of <222 mm combined with <40 mm PAW at sowing on light clay soil with 109 mm plant available water capacity (PAWC). Sowing was generally warranted; only on light clay soil with <10 mm PAW at sowing and below median rainfall of <222 mm was there an opportunity for a conditional sowing strategy. Scope for varying N fertiliser rates with PAW at sowing was limited to soils with higher PAWC (109 and 130 mm, respectively) in below median rainfall seasons at the wetter site (295 mm mean seasonal rainfall), and in both season-types at the drier site (225 mm mean seasonal rainfall). Only in these combinations, soil water at sowing modified the optimal N fertiliser rate for maximum average yield resulting in significant interactions between PAW at sowing and N fertiliser rates. Similar interactions were found for a site in the Mediterranean Basin and a site in the eastern Australian subtropics on soil with high PAWC (183 and 276 mm, respectively). In contrast, there was no benefit from modifying crop management based on PAW at sowing on soil with low PAWC (i.e. sandy s

Assessing the sustainability of crop and soil management practices in wheat-based rotations requires a well-tested model with the demonstrated ability to sensibly predict crop productivity and changes in the soil resource. The Agricultural Production Systems Simulator (APSIM) suite of models was parameterised and subsequently used to predict biomass production, yield, crop water and nitrogen (N) use, as well as long-term soil water and organic matter dynamics in wheat/chickpea systems at Tel Hadya, north-western Syria. The model satisfactorily simulated the productivity and water and N use of wheat and chickpea crops grown under different N and/or water supply levels in the 1998-99 and 1999-2000 experimental seasons. Analysis of soil-water dynamics showed that the 2-stage soil evaporation model in APSIM's cascading water-balance module did not sufficiently explain the actual soil drying following crop harvest under conditions where unused water remained in the soil profile. This might have been related to evaporation from soil cracks in the montmorillonitic clay soil, a process not explicitly simulated by APSIM. Soil-water dynamics in wheat-fallow and wheat-chickpea rotations (1987-98) were nevertheless well simulated when the soil water content in 0-0.45 m soil depth was set to 'air dry' at the end of the growing season each year. The model satisfactorily simulated the amounts of NO3-N in the soil, whereas it underestimated the amounts of NH 4-N. Ammonium fixation might be part of the soil mineral-N dynamics at the study site because montmorillonite is the major clay mineral. This process is not simulated by APSIM's nitrogen module. APSIM was capable of predicting long-term trends (1985-98) in soil organic matter in wheat-fallow and wheat-chickpea rotations at Tel Hadya as reported in literature. Overall, results showed that the model is generic and mature enough to be extended to this set of environmental conditions and can therefore be applied to assess the susta

We report on measurements of the temperature dependence of the gain and internal waveguide loss of a 3.4 micrometers, optically pumped InAs/InGaSb, type II, W laser. A high-resolution Fourier Transform Infrared (FTIR) spectrometer was used to measure the laser mode spectra below threshold. To obtain an accurate determination of the gain, a full curve fit to the spectral output of the Fabry-Perot cavity was utilized. Our results indicate very low waveguide loss (a = 2 /cm) at 78 K, with no apparent increase up to at least 120 K. Additional measurements of the gain properties of the device reveal a rapidly decreasing differential gain, dG/dP and a rapidly increasing transparency pump power with increasing temperature. Moreover, measurements of the peak gain at constant pumping show a rapid decline with increasing temperature. Theoretical superlattice empirical pseudopotential model (SEPM)-based calculations suggest that the substantial differences between the conduction and valence subband in-plane curvatures contribute to the rapid decline in gain with increasing temperature.