Climatic-requirements models of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae) to prioritise areas for exploration and release of biological control agents

Climate matching software (CLIMEX) was used to prioritise areas to explore for biological control agents in the native range of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae), and to prioritise areas to release the agents in the introduced ranges of the plant. The native distribution of cat's claw creeper was used to predict the potential range of climatically suitable habitats for cat's claw creeper in its introduced ranges. A Composite Match Index (CMI) of cat's claw creeper was determined with the 'Match Climates' function in order to match the ranges in Australia and South Africa where the plant is introduced with its native range in South and Central America. This information was used to determine which areas might yield climatically-adapted agents. Locations in northern Argentina had CMI values which best matched sites with cat's claw creeper infestations in Australia and South Africa. None of the sites from where three currently prioritised biological control agents for cat's claw creeper were collected had CMI values higher than 0.8. The analysis showed that central and eastern Argentina, south Brazil, Uruguay and parts of Bolivia and Paraguay should be prioritised for exploration for new biological control agents for cat's claw creeper to be used in Australia and South Africa.

Using morphological traits to identify persistent lucernes for dryland agriculture in NSW, Australia

This paper reports on several studies conducted to better understand the variability between lucerne cultivars and lines, and use this to predict persistence in dryland grazing pastures in eastern Australia. Morphological traits of 20 cultivars/lines were measured in irrigated and dryland spaced plant experiments. Studies were also conducted to describe variation among lucernes in their utilisation of starch and responses to water deficit, pests and diseases. Multiple regression analyses were used to develop simple models where the measured traits could be used to predict persistence of lucerne lines in dryland evaluation experiments. Although there was significant variation among cultivars/lines in most measured traits, no single trait reliably predicted persistence of cultivars/lines in dryland evaluation experiments. However, variation in persistence at both sites could be explained by models developed by multiple regression using differences in the mean lengths of the longest stems at 10% flower in summer and winter. Persistent lucernes were those that had relatively long stems in summer and short stems in winter. Water use efficiencies, starch utilisation patterns and resistances to pests and diseases of different lucernes provided some improvement to this simple model, but these improvements were not consistent.

Detecting quantitative trait loci affecting beef tenderness on bovine chromosome 7 near calpastatin and lysyl oxidase

From a study of 3 large half-sib families of cattle, we describe linkage between DNA polymorphisms on bovine chromosome 7 and meat tenderness. Quantitative trait loci (QTL) for Longissimus lumborum peak force (LLPF) and Semitendonosis adhesion (STADH) were located to this map of DNA markers, which includes the calpastatin ( CAST) and lysyl oxidase (LOX) genes. The LLPF QTL has a maximum lodscore of 4.9 and allele substitution of approximately 0.80 of a phenotypic standard deviation, and the peak is located over the CAST gene. The STADH QTL has a maximum lodscore of 3.5 and an allele substitution of approximately 0.37 of a phenotypic standard deviation, and the peak is located over the LOX gene. This suggests 2 separate likelihood peaks on the chromosome. Further analyses of meat tenderness measures in the Longissimus lumborum, LLPF and LL compression (LLC), in which outlier individuals or kill groups are removed, demonstrate large shifts in the location of LLPF QTL, as well as confirming that there are indeed 2 QTL on bovine chromosome 7. We found that both QTL are reflected in both LLPF and LLC measurements, suggesting that both these components of tenderness, myofibrillar and connective tissue, are detected by both measurements in this muscle.

Mapping quantitative trait loci for resistance to Pratylenchus thornei from synthetic hexaploid wheat in the International Triticeae Mapping Initiative (ITMI) population

Root-lesion nematode (Pratylenchus thornei) is a serious pathogen of wheat in many countries. The International Triticeae Mapping Initiative (ITMI) population of recombinant inbred lines (RILs) was assessed for resistance to P. thornei to determine the chromosome locations of the resistance genes. The ITMI population is derived from a cross between the resistant synthetic hexaploid wheat W-7984 and a susceptible bread wheat cultivar Opata 85. Two years of phenotypic data for resistance to P. thornei were obtained in replicated glasshouse trials. Quantitative trait locus (QTL) analysis was performed using available segregation and map data for 114 RILs. A QTL on chromosome 6DS showed consistent effects for reduced nematode numbers (partial resistance) across years and accounted for 11% and 23% of the phenotypic variation. A second QTL for P. thornei resistance on chromosome 2BS accounted for an additional 19% and 5%. Restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers associated with the QTLs are physically located in regions rich in major genes at the distal ends of the short chromosome arms of 6D and 2B. SSR markers with potential for marker-assisted selection of P. thornei resistance effective in different genetic backgrounds have been identified.

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%.

Genetic variation and responses in reproductive performance of sows in lines selected for growth rate under restricted feeding

The objective of this study was to examine genetic changes in reproduction traits in sows (total number born (TNB), number born alive (NBA), average piglet birth weight (ABW) and number of piglets weaned (NW), body weight prior to mating (MW), gestation length (GL) and daily food intake during lactation (DFI)) in lines of Large White pigs divergently selected over 4 years for high and low post-weaning growth rate on a restricted ration. Heritabilities and repeatabilities of the reproduction traits were also determined. The analyses were carried out on 913 litter records using average information-restricted maximum likelihood method applied to single trait animal models. Estimates of heritability for most traits were small, except for ABW (0·33) and MW (0·35). Estimates of repeatability were slightly higher than those of heritability for TNB, NBA and NW, but they were almost identical for ABW, MW, GL and DFI. After 4 years of selection, the high growth line sows had significantly heavier body weight prior to mating and produced significantly more piglets born alive with heavier average birth weight than the low line sows. There were, however, no statistical differences between the selected lines in TNB or NW. The lower food intake of high relative to low line sows during lactation was not significant, indicating that daily food intake differences found between grower pigs in the high and low lines (2·71 v. 2·76 kg/day, s.e.d. 0·024) on ad libitum feeding were not fully expressed in lactating sows. It is concluded that selection for growth rate on the restricted ration resulted in beneficial effects on important measures of reproductive performance of the sows.

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.

Identification of quantitative trait loci for resistance to two species of root-lesion nematode (Pratylenchus thornei and P. neglectus) in wheat

Pratylenchus thornei and P. neglectus are two species of root-lesion nematode that cause substantial yield losses in wheat. No commercially available wheat variety has resistance to both species. A doubled-haploid population developed from a cross between the synthetic hexaploid wheat line CPI133872 and the bread wheat Janz was used to locate and tag quantitative trait loci (QTLs) associated with resistance to both P. thornei and P. neglectus. Wheat plants were inoculated with both species of nematode in independent replicated glasshouse trials repeated over 2 years. Known locations of wheat microsatellite markers were used to construct a framework map. After an initial single-marker analysis to detect marker-trait linkages, chromosome regions associated with putative QTLs were targetted with microsatellite markers to increase map density in the chromosome regions of interest. In total, 148 wheat microsatellite markers and 21 amplified fragment length polymorphism markers were mapped. The codominant microsatellite marker Xbarc183 on the distal end of chromosome 6DS was allelic for resistance to both P. thornei and P. neglectus. The QTL were designated QRlnt.lrc-6D.1 and QRlnn.lrc-6D.1, for the 2 traits, respectively. The allele inherited from CPI133872 explained 22.0-24.2% of the phenotypic variation for P. thornei resistance, and the allele inherited from Janz accounted for 11.3-14.0% of the phenotypic variation for P. neglectus resistance. Composite interval mapping identified markers that flank a second major QTL on chromosome 6DL (QRlnt.lrc-6D.2) that explained 8.3-13.4% of the phenotypic variation for P. thornei resistance. An additional major QTL associated with P. neglectus resistance was detected on chromosome 4DS (QRlnn.lrc-4D.1) and explained a further 10.3-15.4% of the phenotypic variation. The identification and tagging of nematode resistance genes with molecular markers will allow appropriate allele combinations to be selected, which will aid the successful breeding of wheat with dual nematode resistance.

Simple sequence repeat markers associated with three quantitative trait loci for black point resistance can be used to enrich selection populations in bread wheat

Black point in wheat has the potential to cost the Australian industry $A30.4 million a year. It is difficult and expensive to screen for resistance, so the aim of this study was to validate 3 previously identified quantitative trait loci (QTLs) for black point resistance on chromosomes 2B, 4A, and 3D of the wheat variety Sunco. Black point resistance data and simple sequence repeat (SSR) markers, linked to the resistance QTLs and suited to high-throughput assay, were analysed in the doubled haploid population, Batavia (susceptible) × Pelsart (resistant). Sunco and Pelsart both have Cook in their pedigree and both have the Triticum timopheevii translocation on 2B. SSR markers identified for the 3 genetic regions were gwm319 (2B, T. timopheevii translocation), wmc048 (4AS), and gwm341 (3DS). Gwm319 and wmc048 were associated with black point resistance in the validation population. Gwm341 may have an epistatic influence on the trait because when resistance alleles were present at both gwm319 and wmc048, the Batavia-derived allele at gwm341 was associated with a higher proportion of resistant lines. Data are presented showing the level of enrichment achieved for black point resistance, using 1, 2, or 3 of these molecular markers, and the number of associated discarded resistant lines. The level of population enrichment was found to be 1.83-fold with 6 of 17 resistant lines discarded when gwm319 and wmc048 were both used for selection. Interactions among the 3 QTLs appear complex and other genetic and epigenetic factors influence susceptibility to black point. Polymorphism was assessed for these markers within potential breeding material. This indicated that alternative markers to wmc048 may be required for some parental combinations. Based on these results, marker-assisted selection for the major black point resistance QTLs can increase the rate of genetic gain by improving the selection efficiency and may facilitate stacking of black point resistances from different sources.

Approaches to selecting native plant replacements for fleshy-fruited invasive species

Invasive plants are a serious threat to biodiversity. Yet, in some cases, they may play an important ecological role in heavily modified landscapes, such as where fleshy-fruited invasive plants support populations of native frugivores. How can such conservation conflicts be managed? We advocate an approach in which native fleshy-fruited plants are ranked on their ability to provide the fruit food resources for native frugivores currently being provided by invasive plants. If these native taxa are preferentially used, where ecologically appropriate, in plantings for restoration and in park and garden settings, they could help support native frugivore populations in the event of extensive invasive plant control. We develop and critically examine six approaches to selecting candidate native plant taxa: a multivariate approach based on the frugivore assemblage, a scoring model, and several multivariate approaches (including trait combinations having the greatest correlation with the diet of the native frugivore assemblage) based on the functional traits of fruit morphology, phenology, conspicuousness, and accessibility. To illustrate these approaches, we use a case study with Bitou bush (Chrysanthemoides monilifera subsp. rotundata) (Asteraceae), an Australian Weed of National Significance. The model using a dissimilarity value generated from all available traits identified a set of species used by the frugivores of C. monilifera more than null models. A replacement approach using species ranked by either all traits available or the frugivore community appears best suited to guide selection of plants in restoration practice.

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.

Detection and use of QTL for complex traits in multiple environments.

QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.