Genetic analysis of multiple fruit quality traits in mango across sites and years

A key strategy to improve fruit quality and consumer appeal in mangoes is to breed trait improvements into new cultivars. There are several key fruit quality traits in mango. Knowledge of the heritability and relationship among these traits is important for breeding success. This paper implements a linear mixed model analysis including paternal information for analysis of 13 important fruit quality traits from mango cultivars planted across three environments and assessed over several seasons. The traits analysed were average fruit weight, skin background colour, blush colour, percentage blush, blush intensity, skin thickness, beak shape, stem-end shape, deformities, mesocarp colour, mesocarp texture, seed width and mesocarp recovery. The analysis allows investigation into trait heritabilities and stability of traits over years and sites, as well as genetic correlations among traits

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data

Genome-Wide Association Study for Abscission Failure of Fruit Pericarps (Stick-Tights) in Wild Macadamia Germplasm

Macadamia pericarps that fail to abscise (‘stick-tights’) are an important trait to select against in breeding as they can harbour pests and diseases. Traditional macadamia breeding cycles are lengthy and expensive due to long juvenilities and large tree sizes. Thus, genome-wide association studies (GWAS) are an important investigative tool to identify candidate trait-linked markers to enable potential reductions in evaluation and selection cycles via marker-assisted selection (MAS) in young seedlings. This study assessed 199 wild macadamia germplasm accessions for stick-tight prevalence across two years. As the number of stick-tights per tree is limited by the number of nuts per tree, we conducted association analyses to identify SNPs linked with the number of stick-tights per tree, and examined whether such SNPs were also associated with, and thus confounded with, the number of nuts per tree. We also assessed associations with the proportion of stick-tights per total number of nuts. Thirty-two SNPs were associated with at least one of the stick-tight traits in one year (p < 0.001). Of all such SNPs, only one was associated with the number of nuts per tree (p < 0.001), indicating that most associations were not confounded with yield

‘Red Rhapsody’ Strawberry

Queensland’s winter strawberry (Fragaria ×ananassa Duch.) industry would benefit by having an early ripening, more profitable cultivar to replace current cultivars. ‘Strawberry Festival’ (Chandler et al., 2000) and, more recently, ‘Florida Radiance’ (Chandler et al., 2009) were introduced to Queensland and rapidly became major early-season cultivars with fruit and plant attributes desirable to growers. ‘Florida Radiance’ is marketed in Australia as ‘Florida Fortuna’. The average fruit size of ‘Strawberry Festival’ is less than ‘Florida Radiance’, but the latter is more difficult to establish in the field. Numerous plant losses sometimes occur, especially when demand for early supply of runners results in premature digging and lower quality runners. The commercial desirability of strawberry cultivars for producers, distributors, retailers, and consumers depends on many traits. Supply volumes influence market prices and profitability to the producer. Producer profitability is a key need for a stable production system. Herrington et al., (2012) analyzed the production and marketing system in Queensland in relation to the effect of changes in plant traits on the notional profitability of production. When this information was combined with genetic parameters, they found (Herrington et al., 2014) the key drivers of greater profitability compared with the current profitability in subtropical Southeast Queensland were having a greater proportion of yield early in the season and having a larger fruit size. In the development of ‘Red Rhapsody’ (Fig. 1), we focused on selecting for these traits while maintaining levels of other traits at or above commercially acceptable threshold levels

Genetic variation for photosynthetic capacity and efficiency in spring wheat

One way to increase yield potential in wheat is screening for natural variation in photosynthesis. This study uses measured and modelled physiological parameters to explore genotypic diversity in photosynthetic capacity (Pc, Rubisco carboxylation capacity per unit leaf area at 25 °C) and efficiency (Peff, Pc per unit of leaf nitrogen) in wheat in relation to fertilizer, plant stage, and environment. Four experiments (Aus1, Aus2, Aus3, and Mex1) were carried out with diverse wheat collections to investigate genetic variation for Rubisco capacity (Vcmax25), electron transport rate (J), CO2 assimilation rate, stomatal conductance, and complementary plant functional traits: leaf nitrogen, leaf dry mass per unit area, and SPAD. Genotypes for Aus1 and Aus2 were grown in the glasshouse with two fertilizer levels. Genotypes for Aus3 and Mex1 experiments were grown in the field in Australia and Mexico, respectively. Results showed that Vcmax25 derived from gas exchange measurements is a robust parameter that does not depend on stomatal conductance and was positively correlated with Rubisco content measured in vitro. There was significant genotypic variation in most of the experiments for Pc and Peff. Heritability of Pc reached 0.7 and 0.9 for SPAD. Genotypic variation and heritability of traits show that there is scope for these traits to be used in pre-breeding programmes to improve photosynthesis with the ultimate objective of raising yield potential

Spatial and temporal modelling for perennial crop variety selection trials.

This thesis involves the investigation and development of methods for analysing data from variety selection trials in perennial crops. This involves identifying best varieties from data collected at multiple times in field trials, often from multiple locations and involving multiple traits. For accurate variety predictions the methods for analysis of such data need to account for the spatial correlation typically present in field trials and the temporal correlation induced by the repeated measures nature of the data. The methods also need to model the variety effects over time. The methods presented are based on the linear mixed model and estimation is performed using residual maximum likelihood (REML). Spatial analysis methods are applied to data from multiple harvest times for two perennial crop data sets. These analyses show that spatial correlation is evident and the spatial analysis methods improve model fit. Simulation studies also show the spatial analysis methods provide better predictions of variety effects (closer to the true effects). As the data from perennial crop variety selection trials is measured over time there is also a need to account for the temporal correlation between measurements. Separable models are presented that model the spatial and temporal residual covariance structure. These methods are suitable for large numbers of harvests. Application to a multi-harvest lucerne breeding data set shows these models to be an improvement on historical analysis approaches. At the genetic level the variety effects need to be modelled over time. Two approaches are presented. The first approach involves applying factor analytic models to variety by harvest effects and using clustering to aid in interpretation and selection. The second approach uses cubic smoothing spline random regression. These approaches are applied to data from two traits from a lucerne breeding trial and are shown to successfully model the variety by harvest effects and aid in selection. As data is usually obtained from multiple trials at different locations, the above approaches are extended to the multi-environment situation and applied to a multi-harvest, multi-environment lucerne data set. While the separable spatio-temporal residual models show an improvement on analysing each harvest time separately, they are very restrictive in that they assume common spatial correlation parameters across harvests (or traits). The initial spatial analyses on the two multi-harvest perennial crop data sets reveal that spatial correlation often varies between harvests and between traits. A more suitable non-separable covariance model is investigated that allows for differing spatial correlation across time or traits. The approach is based on the Multivariate Autoregressive model, initially for spatial correlation in one direction. Subsequently the model is extended to the two directional row-column situation using the theory of Multivariate Conditional Autoregressive models. These models are applied to the lucerne multi-harvest and multi-trait data using code written in R, and are shown in most cases to be a significant improvement to the separable residual models previously investigated.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 201

Resistance to Fusarium oxysporum f. sp fragariae and Predicted Breeding Values in Strawberry

Fusarium wilt of strawberry, incited by Fusarium oxysporum f. sp. fragariae (Fof), is a major disease of the cultivated strawberry (Fragaria xananassa) worldwide. An increase in disease outbreaks of the pathogen in Western Australia and Queensland plus the search for alternative disease management strategies place emphasis on the development of resistant cultivars. In response, a partial incomplete diallel cross involving four parents was performed for use in glasshouse resistance screenings. The resulting progeny were evaluated for their susceptibility to Fof. Best-performing progeny and suitability of progenies as parents were determined using data from disease severity ratings and analyzed using a linear mixed model incorporating a pedigree to produce best linear unbiased predictions of breeding values. Variation in disease response, ranging from highly susceptible to resistant, indicates a quantitative effect. The estimate of the narrow-sense heritability was 0.49 +/- 0.04 (SE), suggesting the population should be responsive to phenotypic recurrent selection. Several progeny genotypes have predicted breeding values higher than any of the parents. Knowledge of Fof resistance derived from this study can help select best parents for future crosses for the development of new strawberry cultivars with Fof resistance