The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models

Laboratory-based relationships that model the phytotoxicity of metals using soil properties have been developed. This paper presents the first field-based phytotoxicity relationships. Wheat(Triticum aestivum L) was grown at 11 Australian field sites at which soil was spiked with copper (Cu) and zinc (Zn) salts. Toxicity was measured as inhibition of plant growth at 8 weeks and grain yield at harvest. The added Cu and Zn EC10 values for both endpoints ranged from approximately 3 to 4760 mg/kg. There were no relationships between field-based 8-week biomass and grain yield toxicity values for either metal. Cu toxicity was best modelled using pH and organic carbon content while Zn toxicity was best modelled using pH and the cation exchange capacity. The best relationships estimated toxicity within a factor of two of measured values. Laboratory-based phytotoxicity relationships could not accurately predict field-based phytotoxicity responses.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Reassessing the earthquake hazard in Kerala based on the historical and current seismicity

Given the lack of proper constraints in understanding earthquake mechanisms in the cratonic interiors and the general absence of good quality database, here we reassess the seismic hazard in the province of Kerala, a part of the aEuro cent stable continental interioraEuro cent, based on an improved historical and instrumental database. The temporal pattern of the current seismicity suggests that > 60% of the microtremors in Kerala occurs with a time lag after the peak rainfall, indicating that hydroseismicity may be a plausible model to explain the low-level seismicity in this region. Further, an increment in overall seismicity rate in the region in the recent years is explained as due to increased anthropogenic activities, which includes changes in hydrological pathways as a consequence of rapid landscape changes. Our analyses of the historical database eliminate a few events that are ascribed to this region; this exercise has also led to identification of a few events, not previously noted. The improved historical database essentially suggests that the central midland region is more prone to seismic activity compared to other parts of Kerala. This region appears to have generated larger number of significant earthquakes; the most prominent being the multiple events (doublets) of 1856 and 1953, whose magnitudes are comparable to that of the 2000/2001 (central Kerala) events. Occurrences of these historical events and the recent earthquakes, and the local geology indicative of pervasive faulting as shown by widely distributed pseudotachylite veins suggest that the NNW-SSE trending faults in central midland Kerala may host discrete potentially active sources that may be capable of generating light to moderate size earthquakes. The frequency of earthquakes in central Kerala evident from the historical database requires that the seismic codes stipulated for this region are made mandatory.

Liquefaction Hazard Mapping of Bangalore, South India

his paper presents identification and mapping of vulnerable and safe zones for liquefaction hazard. About 850 bore logs data collected from geotechnical investigation reports have been used to estimate the liquefaction factor of safety for Bangalore Mahanagara palike (BMP) area of about 220 km(2). Liquefaction factor of safety is arrived based on surface level peak ground acceleration presented by Anbazhagan and Sitharam(5) and liquefaction resistance, using corrected standard penetration test (SPT) N values. The estimated factor of safety against liquefaction is used to estimate liquefaction potential index and liquefaction severity index. These values are mapped using Geographical information system (GIS) to identify the vulnerable and safe zones in Bangalore. This study shows that more than 95% of the BMP area is safe against liquefaction potential. However the western part of the BMP is not safe against liquefaction, as it may be subjected to liquefaction with probability of 35 to 65%. Three approaches used in this study show that 1) mapping least factor of safety irrespective of depth may be used to find liquefiable area for worst case. 2) mapping liquefaction potential index can be used to assess the liquefaction severity of the area by considering layer thickness and factor of safety and 3) mapping of liquefaction severity index can be used to access the probability of liquefaction of area.

The sensitivity of updated NIR PLS models for fruit sorting to initial parameter settings

Partial least squares regression models on NIR spectra are often optimised (for wavelength range, mathematical pretreatment and outlier elimination) in terms of calibration terms of validation performance with reference to totally independent populations.

Optimization models for expanding a railway’s theoretical capacity

Changing the topology of a railway network can greatly affect its capacity. Railway networks however can be altered in a multitude of different ways. As each way has significant immediate and long term financial ramifications, it is a difficult task to decide how and where to expand the network. In response some railway capacity expansion models (RCEM) have been developed to help capacity planning activities, and to remove physical bottlenecks in the current railway system. The exact purpose of these models is to decide given a fixed budget, where track duplications and track sub divisions should be made, in order to increase theoretical capacity most. These models are high level and strategic, and this is why increases to the theoretical capacity is concentrated upon. The optimization models have been applied to a case study to demonstrate their application and their worth. The case study evidently shows how automated approaches of this nature could be a formidable alternative to current manual planning techniques and simulation. If the exact effect of track duplications and sub-divisions can be sufficiently approximated, this approach will be very applicable.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.

Reconciling transport models across scales: The role of volume exclusion

Diffusive transport is a universal phenomenon, throughout both biological and physical sciences, and models of diffusion are routinely used to interrogate diffusion-driven processes. However, most models neglect to take into account the role of volume exclusion, which can significantly alter diffusive transport, particularly within biological systems where the diffusing particles might occupy a significant fraction of the available space. In this work we use a random walk approach to provide a means to reconcile models that incorporate crowding effects on different spatial scales. Our work demonstrates that coarse-grained models incorporating simplified descriptions of excluded volume can be used in many circumstances, but that care must be taken in pushing the coarse-graining process too far.

Evidence of episodic brittle faulting in the cratonic part of the Peninsular India and its implications for seismic hazard in slow deforming regions

The region around Waclakkancheri, in the province of Kerala, India, which lies in the vicinity of Palghat-Cauvery ;hear zone (within the Precambrian crystalline terrain), has been a site of microseismic activity since 1989. Earlier studies had identified a prominent WNW-ESE structure overprinting on the E-W trending lineaments associated with Palghat-Cauvery shear zone. We have mapped this structure, located in a chamockite quarry near Desamangalam, Waclakkancheri, which we identify as a ca. 30 km-long south dipping reverse fault. This article presents the characteristics of this fault zone exposed on the exhumed crystalline basement and discusses its significance in understanding the earthquake potential of the region. This brittle deformation zone consists of fracture sets with small-scale displacement and slip planes with embedded fault gouges. The macroscopic as well as the microscopic studies of this fault zone indicate that it evolved through different episodes of faulting in the presence of fluids. The distinct zones within consolidated gouge and the cross cutting relationship of fractures indicate episodic fault activity. At least four faulting episodes can be recognized based on the sequential development of different structural elements in the fault rocks. The repeated ruptures are evident along this shear zone and the cyclic behavior of this fault consists of co-seismic ruptures alternating with inter-seismic periods, which is characterized by the sealed fractures and consolidated gouge. The fault zone shows a minimum accumulated dip/oblique slip of 2.1 m in the reverse direction with a possible characteristic slip of 52 cm (for each event). The ESR dating of fault gouge indicates that the deformation zone records a major event in the Middle Quaternary. The empirical relationships between fault length and slip show that this fault may generate events M >= 6. The above factors suggest that this fault may be characterized as potentially active. Our study offers some new pointers that can be used in other slow deforming cratonic hinterlands in exploring the discrete active faults.

The effect of data sources and quality on the predictive capacity of CLIMEX models: an assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.

Synthesis, Binding and Bioactivity of [gamma]-Methylene [gamma]-Lactam Ecdysone Receptor Ligands: Advantages of QSAR Models for Flexible Receptors

Nuclear hormone receptors, such as the ecdysone receptor, often display a large amount of induced fit to ligands. The size and shape of the binding pocket in the EcR subunit changes markedly on ligand binding, making modelling methods such as docking extremely challenging. It is, however, possible to generate excellent 3D QSAR models for a given type of ligand, suggesting that the receptor adopts a relatively restricted number of binding site configurations or [`]attractors'. We describe the synthesis, in vitro binding and selected in vivo toxicity data for [gamma]-methylene [gamma]-lactams, a new class of high-affinity ligands for ecdysone receptors from Bovicola ovis (Phthiraptera) and Lucilia cuprina (Diptera). The results of a 3D QSAR study of the binding of methylene lactams to recombinant ecdysone receptor protein suggest that this class of ligands is indeed recognized by a single conformation of the EcR binding pocket.

Nitrogen use for high productivity and sustainability in cashew.

Interest in cashew production in Australia has been stimulated by domestic and export market opportunities and suitability of large areas of tropical Australia. Economic models indicate that cashew production is profitable at 2.8 t ha-1 nut-in-shell (NIS). Balanced plant nutrition is essential to achieve economic yields in Australia, with nitrogen (N) of particular importance because of its capacity to modify growth, affect nut yield and cause environmental degradation through soil acidification and off-site contamination. The study on a commercial cashew plantation at Dimbulah, Australia, investigated the effect of N rate and timing on cashew growth, nut production, N leaching and soil chemical properties over five growth cycles (1995-1999). Nitrogen was applied during the main periods of vegetative (December-April) and reproductive (June-October) growth. Commercial NIS yields (up to 4.4 t ha-1 from individual trees) that exceeded the economic threshold of 2.8 t ha-1 were achieved. The yield response was mainly determined by canopy size as mean nut weight, panicle density and nuts per panicle were largely unaffected by N treatments. Nitrogen application confined to the main period of vegetative growth (December-April) produced a seasonal growth pattern that corresponded most consistently with highest NIS yield. This N timing also reduced late season flowering and undesirable post-November nut drop. Higher yields were not produced at N rates greater than 17 g m-2 of canopy surface area (equating to 210 kg N ha-1 for mature size trees). High yields were attained when N concentrations in Mveg leaves in May-June were about 2%, but this assessment occurs at a time when it is not feasible to correct N deficiency. The Mflor leaf of the preceding November, used in conjunction with the Mveg leaf, was proposed as a diagnostic tool to guide N rate decisions. Leaching of nitrate-N and acidification of the soil profile was recorded to 0.9 m. This is an environmental and sustainability hazard, and demonstrates that improved methods of N management are required.