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.

Rice molecular breeding laboratories in the genomics era: Current status and future considerations

Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

Development of a New Zealand database of plant virus and virus-like organisms.

The recent 8th Australasian plant virology workshop in Rotorua, New Zealand, discussed the development of a New Zealand database of plant virus and virus-like organisms. Key points of discussion included: (i) the purpose of such a database; (ii) who would benefit from the information in a database; (iii) the scope of a database and its associated collections; (iv) database information and format; and (v) potential funding of such a database. From the workshop and further research, we conclude that the preservation and verification of specimens within the collections and the development of a New Zealand database of plant virus and virus-like organisms is essential. Such a collection will help to fulfil statutory requirements in New Zealand and assist in fulfilling international obligations under the International Plant Protection Convention. Sustaining such a database will assist New Zealand virologists and statutory bodies to undertake scientifically sound research. Establishing reliable records and an interactive database will help to ensure accurate and timely diagnoses of diseases caused by plant viruses and virus-like organisms. Detection of new incursions and their diagnosis will be further enhanced by the use of such reference collections and their associated database. Connecting and associating this information to similar overseas databases would assist international collaborations and allow access to the latest taxonomic and diagnostic resources. Associated scientists working in the areas of plant breeding, export phytosanitary assurance and in the area of the conservation estate would also benefit from access to verified specimens of plant viruses and virus-like organisms. We conclude that funding of a New Zealand database of virus and virus-like organisms and its associated collections should be based partly on Crown funds, as it is a nationally significant biological resource.

Rapid phenotyping for adult-plant resistance to stripe rust in wheat

Stripe or yellow rust (YR) is a significant problem in wheat crops worldwide. The deployment of adult-plant resistance (APR) genes in wheat cultivars is considered a sustainable management strategy, as these genes confer partial resistance that is usually non-race specific. Screening for APR typically involves assessment of adult plants in the field, where expression may be influenced by environmental factors. We report a high-throughput screening method for YR APR that can be used to assess fixed lines or segregating populations grown under controlled environmental conditions (CEC). Inoculation of 3-week-old wheat plants from lines with known APR responses to YR, when grown under constant light and temperature, provided disease responses typical of adult plants. Two F-2 populations ('H45' x 'ST93' and 'Wyalkatchem' x 'ST93') segregating for APR were assessed under both CEC and field conditions. These populations showed similar variation in disease response and lines assessed in both environments attained similar rankings. Phenotypic screening using CEC and continuous light provides an opportunity to accelerate the development of new wheat cultivars with durable resistance.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.

Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

Genetic analysis of resistance to root-lesion nematode (Pratylenchus thornei) in wheat

The inheritance of resistance to root-lesion nematode was investigated in five synthetic hexaploid wheat lines and two bread wheat lines using a half-diallel design of F1 and F2 crosses. The combining ability of resistance genes in the synthetic hexaploid wheat lines was compared with the performance of the bread wheat line 'GS50a', the source of resistance to Pratylenchus thornei used in Australian wheat breeding programmes. Replicated glasshouse trials identified P. thornei resistance as polygenic and additive in gene action. General combining ability (GCA) of the parents was more important than specific combining ability (SCA) effects in the inheritance of P. thornei resistance in both F1 and F2 populations. The synthetic hexaploid wheat line 'CPI133872' was identified as the best general combiner, however, all five synthetic hexaploid wheat lines possessed better GCA than 'GS50a'. The synthetic hexaploid wheat lines contain novel sources of P. thornei resistance that will provide alternative and more effective sources of resistance to be utilized in wheat breeding programmes

In Vitro Conditions for a Successful Biolistics transformation System of Pineapples (ananas comosus merr.), in 'Contributing to a Sustainable Future'

In order to develop an efficient and reliable biolistics transformation system for pineapples parameters need to be optimised for growth, survival and development of explants pre- and post transformation. We have optimised in vitro conditions for culture media for the various stages of plant and callus initiation and development, and for effective selection of putative transgenic material. Shoot multiplication and proliferation is best on medium containing MS basic nutrients and vitamins with the addition of 0.1 mg/L myo-inositol, 20 g/L sucrose, 2.5 mg/L BAP and 3 g/L Phytagel, followed by transfer to basic MS medium for further development. Callus production on leaf base explants is best on MS nutrients and vitamins, to which 10 mg/L of BAP and NAA each was added. Optimum explant age for bombardment is 17-35 week old callus, while a pre-bombardment osmoticum treatment in the medium is not required. By comparing several antibiotics as selective agent, it has been established that a two-step selection of 2 fortnightly sub-cultures on 50 μg/mL of geneticin in the culture medium, followed by monthly sub-cultures on 100 μg/mL geneticin is optimal for survival of transgenic callus. Shoot regeneration from callus cultures is optimal on medium containing MS nutrients and vitamins, 5% coconut water and 400 mg/L casein hydrolysate. Plants can be readily regenerated and multiplied from transgenic callus through organogenesis. Rooting of shoots does not require any additional plant hormones to the medium. A transformation efficiency of 1 – 3.5% can be achieved, depending on the gene construct applied.

The Introduction of Transgenes to Control Blackheart in Pineapple: Biolistics Vs Agrobacterium Transformation, in 'Contributing to a Sustainable Future'

Techniques for the introduction of transgenes to control blackheart by particle bombardment and Agrobacterium co-transformation have been developed for pineapple cv. Smooth Cayenne. Polyphenol oxidase (PPO) is the enzyme responsible for blackheart development in pineapple fruit following chilling injury. Sense, anti-sense and hairpin constructs were used as a means to suppress PPO expression in plants. Average transformation efficiency for biolistics was approximately 1% and for Agrobacterium was approximately 1.5%. These results were considered acceptable given the high regeneration potential of between 80-90% from callus cultures. Southern blot analysis revealed stable integration of transgenes with lower copy number found in plants transformed with Agrobacterium compared to those transformed by biolistics. Over 5000 plants from 55 transgenic lines are now undergoing field evaluation in Australia

An assessment of the genetic relationship between sweet and grain sorghums, within Sorghum bicolor ssp. bicolor (L.) Moench, using AFLP markers

Compared to grain sorghums, sweet sorghums typically have lower grain yield and thick, tall stalks which accumulate high levels of sugar (sucrose, fructose and glucose). Unlike commercial grain sorghum (S. bicolor ssp. bicolor) cultivars, which are usually F1 hybrids, commercial sweet sorghums were selected as wild accessions or have undergone limited plant breeding. Although all sweet sorghums are classified within S. bicolor ssp. bicolor, their genetic relationship with grain sorghums is yet to be investigated. Ninety-five genotypes, including 31 sweet sorghums and 64 grain sorghums, representing all five races within the subspecies bicolor, were screened with 277 polymorphic amplified fragment length polymorphism (AFLP) markers. Cluster analysis separated older sweet sorghum accessions (collected in mid 1800s) from those developed and released during the early to mid 1900s. These groups were emphasised in a principle component analysis of the results such that sweet sorghum lines were largely distinguished from the others, particularly by a group of markers located on sorghum chromosomes SBI-08 and SBI-10. Other studies have shown that QTL and ESTs for sugar-related traits, as well as for height and anthesis, map to SBI-10. Although the clusters obtained did not group clearly on the basis of racial classification, the sweet sorghum lines often cluster with grain sorghums of similar racial origin thus suggesting that sweet sorghum is of polyphyletic origin within S. bicolor ssp. bicolor.

Root-lesion nematodes (Pratylenchus thornei and P. neglectus): A review of recent progress in managing a significant pest of grain crops in northern Australia

Two species of root-lesion nematode (predominantly Pratylenchus thornei but also P. neglectus) are widespread pathogens of wheat and other crops in Australia's northern grain belt, a subtropical region with deep, fertile clay soils and a summer-dominant rainfall pattern. Losses in grain yield from P. thornei can be as high as 70% for intolerant wheat cultivars. This review focuses on research which has led to the development of effective integrated management programs for these nematodes. It highlights the importance of correct identification in managing Pratylenchus species, reviews the plant breeding work done in developing tolerant and resistant cultivars, outlines the methods used to screen for tolerance and resistance, and discusses how planned crop sequencing with tolerant and partially resistant wheat cultivars, together with crops such as sorghum, sunflower, millets and canaryseed, can be used to reduce nematode populations and limit crop damage. The declining levels of soil organic matter in cropped soils are also discussed with reference to their effect on soil health and biological suppression of root-lesion nematodes.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Resistance to the root-lesion nematode Pratylenchus thornei of Iranian landrace wheat.

Pratylenchus thornei is widespread throughout the wheat-growing regions in Australia and overseas and can cause yield losses of up to 70% in some intolerant cultivars. The most effective forms of management of P. thornei populations are crop rotation and plant breeding. There have been no wheat accessions identified as completely resistant to P. thornei, therefore breeding programs have used moderately resistant parents. The objective of the present research was to evaluate 274 Iranian landrace wheats for resistance to P. thornei and identify accessions with resistance superior to the current best resistance source (GS50a). Plants were grown in P. thornei inoculated soil under controlled conditions in a glasshouse pot experiment for 16 weeks. Ninety-two accessions found to be resistant or moderately so were retested in a second experiment. From combined analysis of these experiments, 34 accessions were identified as resistant with reproduction factors (final population per kg soil/initial inoculum rate per kg soil) <= 1. In total, 25 accessions were more resistant than GS50a, with AUS28470 significantly (P < 0.05) more resistant. The resistant Iranian landraces identified in the present study are a valuable untapped genetic pool offering improved levels of P. thornei resistance over current parents in Australian wheat-breeding programs.

Quantitative trait loci and epistatic interactions in barley conferring resistance to net type net blotch (Pyrenophora teres f. teres) isolates.

Net type net blotch (NTNB) is an important barley disease in Australia and elsewhere, with significant yield reduction. This trait is important in selection along with other traits of quality and agronomic value. Two-hundred doubled-haploid lines were generated through anther culture from a cross between 'Pompadour' and 'Stirling'. Quantitative trait loci (QTL) were identified against five isolates of Pyrenophora teres f. teres, which represent virulences across Australia. QTL were mapped on chromosomes 3H and 6H using simple sequence repeat (SSR) markers. The resistance locus on 6H was detected with all isolates while the 3H locus was detected with two isolates. The 6H QTL from 'Pompadour' contributed resistance to isolates 97NB1, 95NB100 and NB81, whereas 6H QTL from 'Stirling' contributed resistance to isolates NB50 and NB52B. The 3H QTL from 'Pompadour' contributed resistance to NB50 and NB52B. Significant epistatic interactions were detected between QTL on 3H and 6H. These resistance QTL are a useful resource and identifying closely linked SSR markers with allelic combinations will facilitate in marker-assisted selection to develop NTNB resistant breeding lines.

Agronomy looking forward, thinking broadly.

Global trends in human population and agriculture dictate that future calls made on the resources (physical, human, financial) and systems involved in producing food will be increasingly more demanding and complex. Both plant breeding and improved agronomy lift the potential yield of crops, a key component in progressing farm yield, so society can reasonably expect both agronomy as a science and agronomists as practitioners to contribute to the successful delivery of necessary change. By reflecting on current trends in agricultural production (diversification, intensification, integration, industrialisation, automation) and deconstructing a futuristic scenario of attempting agricultural production on Mars, it seems the skills agronomists will require involve not only the mandatory elements of their discipline but also additional skills that enable engagement with, even leadership of, teams who integrate (in sum or part) engineering, (agri-)business, economics and operational management, and build the social capital required to create and maintain a diverse array of enhanced and new ethical production systems and achieve increasing efficiencies within them.