Multi-trait assessment of early-in-life female, male and genomic measures for use in genetic selection to improve female reproductive performance of Brahman cattle

Early-in-life female and male measures with potential to be practical genetic indicators were chosen from earlier analyses and examined together with genomic measures for multi-trait use to improve female reproduction of Brahman cattle. Combinations of measures were evaluated on the genetic gains expected from selection of sires and dams for each of age at puberty (AGECL, i.e. first observation of a corpus luteum), lactation anoestrous interval in 3-year-old cows (LAI), and lifetime annual weaning rate (LAWR, i.e. the weaning rate of cows based on the number of annual matings they experienced over six possible matings). Selection was on an index of comparable records for each combination. Selection intensities were less than theoretically possible but assumed a concerted selection effort was able to be made across the Brahman breed. The results suggested that substantial genetic gains could be possible but need to be confirmed in other data. The estimated increase in LAWR in 10 years, for combinations without or with genomic measures, ranged from 8 to 12 calves weaned per 100 cows from selection of sires, and from 12 to 15 calves weaned per 100 cows from selection of sires and dams. Corresponding reductions in LAI were 60-103 days or 94-136 days, and those for AGECL were 95-125 or 141-176 days, respectively. Coat score (a measure of the sleekness or wooliness of the coat) and hip height in females, and preputial eversion and liveweight in males, were measures that may warrant wider recording for Brahman female reproduction genetic evaluation. Pregnancy-test outcomes from Matings 1 and 2 also should be recorded. Percentage normal sperm may be important to record for reducing LAI and scrotal size and serum insulin-like growth factor-I concentration in heifers at 18 months for reducing AGECL. Use of a genomic estimated breeding value (EBV) in combination with other measures added to genetic gains, especially at genomic EBV accuracies of 40%. Accuracies of genomic EBVs needed to approach 60% for the genomic EBV to be the most important contributor to gains in the combinations of measures studied.

Estimating an Aggregate Economic Genotype to Facilitate Breeding and Selection of Strawberry Genotypes in Southeast Queensland

The Queensland strawberry (Fragaria ×ananassa) breeding program in subtropical Australia aims to improve sustainable profitability for the producer. Selection must account for the relative economic importance of each trait and the genetic architecture underlying these traits in the breeding population. Our study used estimates of the influence of a trait on production costs and profitability to develop a profitability index (PI) and an economic weight (i.e., change in PI for a unit change in level of trait) for each trait. The economic weights were then combined with the breeding values for 12 plant and fruit traits on over 3000 genotypes that were represented in either the current breeding population or as progenitors in the pedigree of these individuals. The resulting linear combination (i.e., sum of economic weight × breeding value for all 12 traits) estimated the overall economic worth of each genotype as H, the aggregate economic genotype. H values were validated by comparisons among commercial cultivars and were also compared with the estimated gross margins. When the H value of ‘Festival’ was set as zero, the H values of genotypes in the pedigree ranged from –0.36 to +0.28. H was highly correlated (R2 = 0.77) with the year of selection (1945–98). The gross margins were highly linearly related (R2 > 0.98) to H values when the genotype was planted on less than 50% of available area, but the relationship was non-linear [quadratic with a maximum (R2 > 0.96)] when the planted area exceeded 50%. Additionally, with H values above zero, the variation in gross margin increased with increasing H values as the percentage of area planted to a genotype increased. High correlations among some traits allowed the omission of any one of three of the 12 traits with little or no effect on ranking (Spearman’s rank correlation 0.98 or greater). Thus, these traits may be dropped from the aggregate economic genotype, leading to either cost reductions in the breeding program or increased selection intensities for the same resources. H was efficient in identifying economically superior genotypes for breeding and deployment, but because of the non-linear relationship with gross margin, calculation of a gross margin for genotypes with high H is also necessary when cultivars are deployed across more than 50% of the available area.

Pleopod Cuticular Morphology as an Index of Moult Stage in the Ornate Rock Lobster, Panulirus ornatus (Fabricius 1789)

Seven discrete stages and substages of moulting in the ornate rock lobster, Panulirus ornatus, have been distinguished by microscopic examination of the cuticle and setae of the pleopods . The diagnostic features and the duration of each of the stages are described. Freezing did not visually alter the tissue features used to identify each moult stage. Pleopod morphology can reliably indicate whether a lobster has moulted within the previous 24 h or is within 72 h of the next ecdysis.

Genetic response to growth rate selection in pigs measured on two feeding levels

From the findings of McPhee et al. (1988), there is an expectation that selection in the growing pig for bodyweight gain measured on restricted feeding will result in favourable responses in the rate and efficiency of growth of lean pork on different levels of feeding. This paper examines this in two lines of Australian Large White pigs which have undergone 3 years of selection for high and for low growth rate over a 6-week period starting at 50 kg liveweight. Over this test period, pigs of both lines are all fed the same total amount of grower food, restricted to an estimated 80% of average ad libitum intake. 'Animal production for a consuming world': proceedings of 9th Congress of the AAAAP Societies and 23rd Biennial Conference of the ASAP and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, (DRF). Sydney, Australia.

Selection and characterisation of two attenuated vaccine lines of Eimeria tenella in Australia

Objective To attenuate two strains of Eimeria tenella by selecting for precocious development and evaluate the strains in characterisation trials and by field evaluation, to choose one precocious line for incorporation into an Australian live coccidiosis vaccine for poultry. Design Two strains from non-commercial flocks were passaged through chickens while selecting for precocious development. Each strain was characterised for drug sensitivity, pathogenicity, protection against homologous and heterologous challenge, and oocyst output in replicated experiments in which the experimental unit was a cage of three birds. Oocyst output and/or body weight gain data collected over a 10 to 12 day period following final inoculation were measured. Feed conversion ratios were also calculated where possible. Results Fifteen passages resulted in prepatent periods reduced by 24 h for the Redlands strain (from 144 h to 120 h)and 23 h for the Darryl strain (from 139 h to 116 h). Characterisation trials demonstrated that each precocious line was significantly less pathogenic than its parent strain and each effectively induced immunity that protected chickens against challenge with both the parent strain and other virulent field strains. Both lines had oocyst outputs that, although significantly reduced relative to the parent strains, remained sufficiently high for commercial vaccine production, and both showed susceptibility to coccidiostats. Conclusion Two attenuated lines have been produced that exhibit the appropriate characteristics for use in an Australian live coccidiosis vaccine.

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

Development of a stable isotope index to assess decadal-scale vegetation change and application to woodlands of the Burdekin catchment, Australia

Forty-four study sites were established in remnant woodland in the Burdekin River catchment in tropical north-east Queensland, Australia, to assess recent (decadal) vegetation change. The aim of this study was further to evaluate whether wide-scale vegetation 'thickening' (proliferation of woody plants in formerly more open woodlands) had occurred during the last century, coinciding with significant changes in land management. Soil samples from several depth intervals were size separated into different soil organic carbon (SOC) fractions, which differed from one another by chemical composition and turnover times. Tropical (C4) grasses dominate in the Burdekin catchment, and thus δ13C analyses of SOC fractions with different turnover times can be used to assess whether the relative proportion of trees (C3) and grasses (C4) had changed over time. However, a method was required to permit standardized assessment of the δ13C data for the individual sites within the 13 Mha catchment, which varied in soil and vegetation characteristics. Thus, an index was developed using data from three detailed study sites and global literature to standardize individual isotopic data from different soil depths and SOC fractions to reflect only the changed proportion of trees (C3) to grasses (C3) over decadal timescales. When applied to the 44 individual sites distributed throughout the Burdekin catchment, 64% of the sites were shown to have experienced decadal vegetation thickening, while 29% had remained stable and the remaining 7% had thinned. Thus, the development of this index enabled regional scale assessment and comparison of decadal vegetation patterns without having to rely on prior knowledge of vegetation changes or aerial photography.

International Society for Applied Ethology. Special issue: a Selection of Papers from the 38th International Congress of the ISAE, Helsinki, Finland, August 2004

Welcome to the latest collection of papers selected from the International Society for Applied Ethology's (ISAE's) annual congress. The ISAE is a multi-faceted scientific society that supports applied research on animals under the influence of humankind. Every year, we aim to invite congress participants who have submitted papers, plenary talks, run workshops, or presented the memorial lecture on theoretical, review or discussion papers of topical interest to contribute to the Special Issue. These papers are peer-reviewed before being published here in Applied Animal Behaviour Science. International Society for Applied Ethology (ISAE) Special Issue 2004.

International Society for Applied Ethology. Special issue: a selection of papers from the 39th International Congress of the International Society for Applied Ethology (ISAE), Tokyo, Japan, August 2005

Welcome to the latest collection of papers selected from the International Society for Applied Ethology's (ISAE's) annual congress. The ISAE is a multi-faceted scientific society that supports applied research on animals that are managed by humans. Every year, we aim to invite congress participants who have submitted papers, plenary talks, run workshops, or presented the memorial lecture on theoretical, review or discussion papers of topical interest to contribute to the Special Issue. These papers are peer-reviewed before being published here in Applied Animal Behaviour Science. This year, we have a variety of papers to bring to your attention. The David Wood-Gush Memorial lecture, the keynote address of the congress, was given by Shigeru Watanabe on animal cognition and welfare. His paper highlights how animal's sensory capabilities relate to their welfare. On the topic of human–animal bonds, Stine Christiansen and Björn Forkman explore how animal welfare is assessed in a veterinary context, and how those assessments might be improved by ethologists. Yoshie Kakuma and co-authors report on the discussions from a workshop on the welfare of working and companion dogs in five different countries. Based on their plenary lectures, Michael Cockram discusses the factors that affect farmed animals during road transport and how these might contribute in making decisions to restrict journey times, while Clive Phillips and co-author Danica Peck examine how personality influences the behaviour and interactions between zoo-housed tigers and their keepers. We hope you enjoy these papers. Our sincere thanks go to both the authors and referees, without whom these special issues would not be possible. A selection of papers from the 39th International Congress of the International Society for Applied Ethology (ISAE), Tokyo, Japan, August 2005.

Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

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.

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.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Improving the agent selection, release and evaluation process: the role of bioclimatic modelling

The value of CLIMEX models to inform biocontrol programs was assessed, including predicting the potential distribution of biocontrol agents and their subsequent population dynamics, using bioclimatic models for the weed Parkinsonia aculeata, two Lantana camara biocontrol agents, and five Mimosa pigra biocontrol agents. The results showed the contribution of data types to CLIMEX models and the capacity of these models to inform and improve the selection, release and post release evaluation of biocontrol agents. Foremost among these was the quality of spatial and temporal information as well as the extent to which overseas range data samples the species’ climatic envelope. Post hoc evaluation and refinement of these models requires improved long-term monitoring of introduced agents and their dynamics at well selected study sites. The authors described the findings of these case studies, highlighted their implications, and considered how to incorporate models effectively into biocontrol programs.