Australian canola (Brassica napus L.) has been relatively isolated from the global gene pool and limited knowledge is available for genetic variability based on DNA profiling. In the present study, genetic diversity of recent Australian canola cultivars was determined by simple sequence repeat (SSR) marker analysis. In total, 405 individuals from 48 varieties were genotyped with 18 primer pairs, resulting in 112 polymorphic features. The number of polymorphic features amplified by each SSR primer pair varied from 3 to 16. Analysis of molecular variance (AMOVA) detected 53.7% and 46.3% within- and between-cultivar variation, respectively. Intra-cultivar genetic variability differed according to cultivar. The number of polymorphic features per cultivar varied from 35 (Ag-Spectrum) to 72 (Ag-Insignia), while mean sum of squares (MSS) varied from 6.29 (Tornado TT) to 24.76 (Ag-Emblem). Genetic differentiation of cultivars generally reflected pedigree structure and origin by breeding organisation. Clustering and principal coordinate analysis (PCoA) indicated that the individuals were separated into 4 major groups. The genetic diversity information from this study will be useful for future Australian canola breeding programs.

Due to the complex genetic architecture of perennial ryegrass, based on an obligate outbreeding reproductive habit, association-mapping approaches to genetic dissection offer the potential for effective identification of genetic marker–trait linkages. Associations with genes for agronomic characters, such as components of herbage nutritive quality, may then be utilised for accelerated cultivar improvement using advanced molecular breeding practices. The objective of the present study was to evaluate the presence of such associations for a broad range of candidate genes involved in pathways of cell wall biosynthesis and carbohydrate metabolism. An association-mapping panel composed from a broad range of non-domesticated and varietal sources was assembled and assessed for genome-wide sequence polymorphism. Removal of significant population structure obtained a diverse meta-population (220 genotypes) suitable for association studies. The meta-population was established with replication as a spaced-plant field trial. All plants were genotyped with a cohort of candidate gene-derived single nucleotide polymorphism (SNP) markers. Herbage samples were harvested at both vegetative and reproductive stages and were measured for a range of herbage quality traits using near infrared reflectance spectroscopy. Significant associations were identified for ~50% of the genes, accounting for small but significant components of phenotypic variance. The identities of genes with associated SNPs were largely consistent with detailed knowledge of ryegrass biology, and they are interpreted in terms of known biochemical and physiological processes. Magnitudes of effect of observed marker–trait gene association were small, indicating that future activities should focus on genome-wide association studies in order to identify the majority of causal mutations for complex traits such as forage quality.

Quantification of forage quality is essential for the identification of elite genotypes in forage grass breeding. Perennial ryegrass is the most important temperate species for global pastoral agriculture. However, the protein content of ryegrass generally exceeds the requirements of a grazing animal, and the ratio of water soluble carbohydrate (WSC) to protein is too low for efficient protein utilisation. This results in poor nitrogen use efficiency (NUE) in the farming system by livestock, and hence limits optimal animal production. New ryegrass cultivars with optimised WSC and protein content are desirable for farming efficiencies. Several methods are available for quantification of WSC and plant protein (such as near-infrared spectroscopy [NIRS] and high performance liquid chromatography [HPLC]). However, such methods are labour-intensive, low-throughput and cost-prohibitive for commercial breeding programs, which typically need to assess thousands of samples annually. An accurate high-throughput micro-plate-based protocol has been developed and validated, with the ability to simultaneously process and quantify WSC and plant protein with a high level of automation, and an increase in sample processing of ~10-fold compared with commonly-used methods, along with a 3-fold cost reduction. As WSC and protein are extracted simultaneously and quantified within micro-plates, consumable costs are minimised with optimal reagent use efficiency, resulting in a low per sample cost that is suitable for commercial pasture breeding companies. This is the first demonstration of a forage quality phenotyping protocol suitable for broad-scale application, and will allow breeders to select elite genotypes based not only on visual assessment but also on WSC : protein ratios for improved ruminant nutrition.