SSR analysis of cultivated groundnut (Arachis hypogaea L.) germplasm resistant to rust and late leaf spot diseases

Cultivated groundnut (Arachis hypogaea L.) is an agronomically and economically important oilseed crop grown extensively throughout the semi-arid tropics of Asia, Africa and Latin America. Rust (Puccinia arachidis) and late leaf spot (LLS, Phaseoisariopsis personata) are among the major diseases causing significant yield loss in groundnut. The development of varieties with high levels of resistance has been constrained by adaptation of disease isolates to resistance sources and incomplete resistance in resistant sources. Despite the wide range of morphological diversity observed in the cultivated groundnut gene pool, molecular marker analyses have thus far been unable to detect a parallel level of genetic diversity. However, the recent development of simple sequence repeat (SSR) markers presents new opportunities for molecular diversity analysis of cultivate groundnut. The current study was conducted to identify diverse disease resistant germplasm for the development of mapping populations and for their introduction into breeding programs. Twenty-three SSRs were screened across 22 groundnut genotypes with differing levels of resistance to rust and LLS. Overall, 135 alleles across 23 loci were observed in the 22 genotypes screened. Twelve of the 23 SSRs (52%) showed a high level of polymorphism, with PIC values ≥0.5. This is the first report detecting such high levels of genetic polymorphism in cultivated groundnut. Multi-dimensional scaling and cluster analyses revealed three well-separated groups of genotypes. Locus by locus AMOVA and Kruskal-Wallis one-way ANOVA identified candidate SSR loci that may be valuable for mapping rust and LLS resistance. The molecular diversity analysis presented here provides valuable information for groundnut breeders designing strategies for incorporating and pyramiding rust and late leaf spot resistances and for molecular biologists wishing to create recombinant inbred line populations to map these traits.

A multi-field bio-economic model of irrigated grain-cotton farming systems.

We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.

Integrating different approaches in the definition of biological stocks: A northern Australian multi-jurisdictional fisheries example using grey mackerel, Scomberomorus semifasciatus

A holistic approach to stock structure studies utilises multiple different techniques on the same individuals sampled from selected populations and combines results across spatial and temporal scales to produce a weight of evidence conclusion. It is the most powerful and reliable source of information to use in formulating resource management and monitoring plans. Few examples of the use of a holistic approach in stock structure studies exist, although more recently this is changing. Using such an approach makes integration of results from each technique challenging. An integrated stock definition (ISD) approach for holistic stock structure studies was developed in this study to aid in the appropriate interpretation of stock structure results to guide the determination of fishery management units. The ISD approach is applied herein to a study of the northern Australian endemic grey mackerel, Scomberomorus semifasciatus (Scombridae). Analyses of genetic (mitochondrial DNA and microsatellites), parasite, otolith stable isotope, and growth data are synthesised to determine the stock structure of S. semifasciatus across northern Australia. Integration of the results from all techniques identified at least six S. semifasciatus stocks for management purposes. Further, the use of the ISD approach provided a simple basis for integrating multiple techniques and for their interpretation. The use of this holistic approach was a powerful tool in providing greater certainty about the appropriate management units for S. semifasciatus. Future stock structure studies investigating spatial management questions in the fisheries context should adopt a holistic approach and apply the ISD approach for a more accurate definition of biological stocks to improve fisheries management.