Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they sample. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 'near-isolines' of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 'drought environment types' (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - II. Testing simulation capabilities of wheat growth

To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

Improving wheat simulation capabilities in Australia from a cropping systems perspective: water and nitrogen effects on spring wheat in a semi-arid environment

Systems approaches can help to evaluate and improve the agronomic and economic viability of nitrogen application in the frequently water-limited environments. This requires a sound understanding of crop physiological processes and well tested simulation models. Thus, this experiment on spring wheat aimed to better quantify water x nitrogen effects on wheat by deriving some key crop physiological parameters that have proven useful in simulating crop growth. For spring wheat grown in Northern Australia under four levels of nitrogen (0 to 360 kg N ha(-1)) and either entirely on stored soil moisture or under full irrigation, kernel yields ranged from 343 to 719 g m(-2). Yield increases were strongly associated with increases in kernel number (9150-19950 kernels m(-2)), indicating the sensitivity of this parameter to water and N availability. Total water extraction under a rain shelter was 240 mm with a maximum extraction depth of 1.5 m. A substantial amount of mineral nitrogen available deep in the profile (below 0.9 m) was taken up by the crop. This was the source of nitrogen uptake observed after anthesis. Under dry conditions this late uptake accounted for approximately 50% of total nitrogen uptake and resulted in high (>2%) kernel nitrogen percentages even when no nitrogen was applied,Anthesis LAI values under sub-optimal water supply were reduced by 63% and under sub-optimal nitrogen supply by 50%. Radiation use efficiency (RUE) based on total incident short-wave radiation was 1.34 g MJ(-1) and did not differ among treatments. The conservative nature of RUE was the result of the crop reducing leaf area rather than leaf nitrogen content (which would have affected photosynthetic activity) under these moderate levels of nitrogen limitation. The transpiration efficiency coefficient was also conservative and averaged 4.7 Pa in the dry treatments. Kernel nitrogen percentage varied from 2.08 to 2.42%. The study provides a data set and a basis to consider ways to improve simulation capabilities of water and nitrogen effects on spring wheat. (C) 1997 Elsevier Science B.V.

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIM's structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Developing high yielding wheat for water limited environments in northern Australia

A novel strategy linking physiology with plant breeding, molecular biology and computer simulation modelling is outlined here which aims to enhance selection of high yielding wheats with superior performance under conditions of water scarcity for the northern, subtropical, winter cereals region of Australia. In previous research, a source of high yield and performance under dry conditions for the target region was identified in a drought resistant parent. A large population of fixed lines for molecular genetic studies has been developed using the drought resistant line and widely grown current Australian variety. A preliminary study comparing the parent varieties was conducted in the winter of 2003. The two varieties were similar in many aspects of phenology, morphology and physiology. However, several important traits were identified that likely contribute to higher grain mass and yield of the drought resistant parent, including differences in the number and dry mass of tillers and spikes during development and the ability of drought resistant line to retain green leaves longer during grain filling.

Virtual training environments to improve train driver's crisis decision making

This paper reports on a current research project in which virtual reality simulators are being investigated as a means of simulating hazardous Rail work conditions in order to allow train drivers to practice decision-making under stress. When working under high stress conditions train drivers need to move beyond procedural responses into a response activated through their own problem-solving and decision-making skills. This study focuses on the use of stress inoculation training which aims to build driver’s confidence in the use of new decision-making skills by being repeatedly required to respond to hazardous driving conditions. In particular, the study makes use of a train cab driving simulator to reproduce potentially stress inducing real-world scenarios. Initial pilot research has been undertaken in which drivers have experienced the training simulation and subsequently completed surveys on the level of immersion experienced. Concurrently drivers have also participated in a velocity perception experiment designed to objectively measure the fidelity of the virtual training environment. Baseline data, against which decision-making skills post training will be measured, is being gathered via cognitive task analysis designed to identify primary decision requirements for specific rail events. While considerable efforts have been invested in improving Virtual Reality technology, little is known about how to best use this technology for training personnel to respond to workplace conditions in the Rail Industry. To enable the best use of simulators for training in the Rail context the project aims to identify those factors within virtual reality that support required learning outcomes and use this information to design training simulations that reliably and safely train staff in required workplace accident response skills.

Distribution of major, minor, and trace metals in lake environments of Antarctica

The concentrations of major, minor and trace metals were measured in water samples collected from five shallow Antarctic lakes (Carezza, Edmonson Point (No 14 and 15a), Inexpressible Island and Tarn Flat) found in Terra Nova Bay (northern Victoria Land, Antarctica) during the Italian Expeditions of 1993-2001. The total concentrations of a large suite of elements (Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Gd, K, La, Li, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, Rb, Sc, Si, Sr, Ta, Ti, U, V, Y, W, Zn and Zr) were determined using spectroscopic techniques (ICP-AES, GF-AAS and ICP-MS). The results are similar to those obtained for the freshwater lakes of the Larsemann Hills, East Antarctica, and for the McMurdo Dry Valleys. Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed to identify groups of samples with similar characteristics and to find correlations between the variables. The variability observed within the water samples is closely connected to the sea spray input; hence, it is primarily a consequence of geographical and meteorological factors, such as distance from the ocean and time of year. The trace element levels, in particular those of heavy metals, are very low, suggesting an origin from natural sources rather than from anthropogenic contamination.

Population subdivision in marine environments: the contributions of biogeography, geographic distance, and discontinuous habitat to genetic differentiation in a blennioid

The relative importance of factors that may promote genetic differentiation in marine organisms is largely unknown. Here, contributions to population structure from biogeography, habitat distribution, and isolation by distance were investigated in Axoclinus nigricaudus, a small subtidal rock reef fish, throughout its range in the Gulf of California. A 408 basepair fragment of the mitochondrial control region was sequenced from 105 individuals. Variation was significantly partitioned between many pairs of populations. Phylogenetic analyses, hierarchical analyses of variance, and general linear models substantiated a major break between two putative biogeographic regions. This genetic discontinuity coincides with an abrupt change in ecological characteristics (including temperature and salinity) but does not coincide with known oceanographic circulation patterns. Geographic distance and the nature of habitat separating populations (continuous habitat along a shoreline, discontinuous habitat along a shoreline, and open water) also contributed to population structure in general linear model analyses. To verify that local populations are genetically stable over time, one population was resampled on four occasions over eighteen months; it showed no evidence of a temporal component to diversity. These results indicate that having a planktonic life stage does not preclude geographically partitioned genetic variation over relatively small geographic distances in marine environments. Moreover, levels of genetic differentiation among populations of Axoclinus nigricaudus cannot be explained by a single factor, but are due to the combined influences of a biogeographic boundary, habitat, and geographic distance.

XSophe-Sophe-XeprView (R). A computer simulation software suite (v. 1.1.3) for the analysis of continuous wave EPR spectra

The XSophe-Sophe-XeprView((R)) computer simulation software suite enables scientists to easily determine spin Hamiltonian parameters from isotropic, randomly oriented and single crystal continuous wave electron paramagnetic resonance (CW EPR) spectra from radicals and isolated paramagnetic metal ion centers or clusters found in metalloproteins, chemical systems and materials science. XSophe provides an X-windows graphical user interface to the Sophe programme and allows: creation of multiple input files, local and remote execution of Sophe, the display of sophelog (output from Sophe) and input parameters/files. Sophe is a sophisticated computer simulation software programme employing a number of innovative technologies including; the Sydney OPera HousE (SOPHE) partition and interpolation schemes, a field segmentation algorithm, the mosaic misorientation linewidth model, parallelization and spectral optimisation. In conjunction with the SOPHE partition scheme and the field segmentation algorithm, the SOPHE interpolation scheme and the mosaic misorientation linewidth model greatly increase the speed of simulations for most spin systems. Employing brute force matrix diagonalization in the simulation of an EPR spectrum from a high spin Cr(III) complex with the spin Hamiltonian parameters g(e) = 2.00, D = 0.10 cm(-1), E/D = 0.25, A(x) = 120.0, A(y) = 120.0, A(z) = 240.0 x 10(-4) cm(-1) requires a SOPHE grid size of N = 400 (to produce a good signal to noise ratio) and takes 229.47 s. In contrast the use of either the SOPHE interpolation scheme or the mosaic misorientation linewidth model requires a SOPHE grid size of only N = 18 and takes 44.08 and 0.79 s, respectively. Results from Sophe are transferred via the Common Object Request Broker Architecture (CORBA) to XSophe and subsequently to XeprView((R)) where the simulated CW EPR spectra (1D and 2D) can be compared to the experimental spectra. Energy level diagrams, transition roadmaps and transition surfaces aid the interpretation of complicated randomly oriented CW EPR spectra and can be viewed with a web browser and an OpenInventor scene graph viewer.