The Talking Plant Science seminar series showcases experts from different disciplines to explore the challenges, discoveries and transformations impacting plant science globally.

Presented by The ARC Centre of Excellence for Plant Success in Nature and Agriculture, this public lecture series explores diverse topics to help join the dots between different approaches and transform plant science for the next generation.

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Please note that all dates and times displayed are in Australian Eastern Standard Time (AEST).

CONTACT

Phoebe Baldwin
p.baldwin@uq.edu.au

UPCOMING EVENTS

Talking Plant Science with Vanessa Adams

Vanessa Adams
University of Tasmania

Abstract to come.

Date: 13 November 2024
Time: 11am-12pm (AEST) / 12-1pm (AEDT)
Register here >

PAST EVENTS

From trait dynamics to GxE for the target trait: Utilizing Stay Green and Multiple Physiological Traits for Enhanced Wheat Adaptation to Contrasting Drought Conditions

Daniela Bustos-Korts
Universidad Austral de Chile

Understanding and predicting genotype adaptation to complex stresses such as drought can be significantly enhanced by integrating information from secondary phenotypes. These phenotypes may include various yield components measured at a single time point or encompass trait dynamics over time. The stay green trait, which reflects a genotype's ability to maintain greener canopies under drought conditions, has emerged as a promising candidate for yield prediction; genotypes exhibiting this trait tend to sustain grain filling rates, resulting in improved yields during drought events. However, modelling these traits presents challenges due to the hierarchical error structure inherent in high-throughput phenotyping, which encompasses measurement, plot, and genotypic errors, alongside the complex dynamics of the trait itself. In this study, we employ one-dimensional and two-dimensional P-splines to disentangle measurement and plot errors from true genotypic signals. This approach enables us to effectively model the dynamics of the stay green trait and its interaction with genotype-by-environment (GxE) effects over time, as demonstrated with a diverse panel of spring wheat grown in contrasting water regimes in Chile.

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Redesigning plants to support long-term Space exploration and for on Earth sustainability

Jenny Mortimer
The University of Adelaide / ARC CoE in Plants for Space

Humans are planning to explore Space further than ever before, with a return to the lunar surface happening as part of the Artemis III mission in 2026, and with a crewed landing planned for the surface of Mars in the 2030s. Important to this is the ability to support astronauts to thrive in space, as opposed to just survive. Food is a key part of this, and with ~10 tonnes of food required for a 4-person mission to Mars, there is an urgent need to produce food in situ, as well as materials and therapeutics. Growth of plants on planetary surfaces will be in closed environment agriculture (CEA) facilities, similar to vertical farming systems being developed here on Earth. However, plants did not evolve to grow in these environments. Here, I will discuss how we can use the lens of Space to innovate for sustainable agriculture. Beyond that, we can use the strict circular economy of Space to develop robust and sustainable in plantabiomanufacturing, supporting a transition to a bioeconomy. 

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Crop modelling for informing leaf photosynthesis and crop yield improvement

Alex Wu
The University of Queensland

An increasing global food demand begs new strategy for crop yield improvement. Leaf CO2 assimilation is an important driver of crop growth and yield. However, the translation of leaf photosynthetic manipulation to crop yield performance is less straightforward. Yield is a complex emergent property driven by instantaneous leaf CO2 assimilation, summed over the whole canopy of the crop and across the entire crop life cycle, all interacting with environmental effects on growth and development of the crop. Here, I will present a ‘cross-scale’ crop modelling effort used to develop integrative leaf-to-field modelling tools, offering new predictive capabilities to aid photosynthesis and yield improvement. This: (i) enables in silico field testing of putative strategies for leaf photosynthetic manipulation in target population of environments; (ii) offers a platform for the dissection of crop growth components and identification of key photosynthetic properties for growth enhancement. The two-pronged, but complementary pathways are generating new information on the value proposition of photosynthetic manipulation and informing fundamental and applied research directions, helping to discover and support new strategies for crop yield improvement. Potential synergies with other crop research technologies are discussed.

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Translational Research in Agriculture: How effectively does it work?

John Passioura
Australian National University

‘Translational research’ became an increasingly common term when it was realised that much agriculturally inspired basic research failed to contribute to the improvement of crops. Most of the failure has come from laboratory-based attempts to ameliorate abiotic stresses. Dealing with biotic stress has been much more successful; the control of pests and weeds is often enabled by transforming crops with single genes, for such genes have little or no influence on a crop’s metabolism. By contrast, abiotic stress varies with the weather; i.e. crops respond systemically, over a range of levels of organisation (e.g. organelles, cells, tissues, organs), with many feedbacks and feedforwards. Drought is the most pervasive form of abiotic stress. There are several thousand papers that have searched, ineffectively, for ‘drought resistance’, a term that usually defies useful definition. By contrast, dealing with a limited water supply (e.g. inadequate seasonal rainfall), rather than with ‘drought’, has effectively increased water-limited yield through agronomic innovation based on improving water-use efficiency. A major reason for the predominant failure of translational research from laboratory to field is that the peer-review system is too narrow; i.e. reviewers have the same backgrounds as the authors. Effective translation requires the addition of reviewers who can assess effective pathways from laboratory to field.

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Hydromechanical forces in transpiring leaves: how the reversible collapse of minor vein xylem conduits protects against cavitation

N. Michele (Missy) Holbrook
Harvard University

Vascular plants transport water in a metastable state putting their lifeline to the soil at risk of embolism formation. Stomata are essential for protecting xylem from developing potentially damaging tensions, yet angiosperm stomata are mechanically and physiologically constrained in their ability to respond to rapid increases in transpiration rate. Here I discuss how the reversible collapse of xylem conduits in the highest vein orders protects xylem conduits during environmentally-driven fluctuations in transpiration rate. The goal of my talk is to illuminate what happens inside a transpiring leaf and to connect this massive movement of water and energy to the functioning of plants at larger scales.

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Plant capacities to adapt to abiotic stresses

Rana Munns
University of Western Australia, Centre of Excellence in Plant Energy Biology

Climate change and the challenge of feeding an increasing world population pose two existential threats. Climate change causes increased global temperatures that reduce crop yield, and the increasing world population demands higher productivity of crops and pastures on decreasing areas of traditional agricultural land. To understand the responses in common to the various abiotic stresses, we distinguish seven capacities that plants possess for adapting to abiotic stresses that result in continued growth and a productive yield. These include the capacities to take up essential resources, supply them to different plant parts, generate the energy required to maintain cellular functions, communicate between plant parts, and manage structural assets in the face of changed circumstances. We show how these capacities are crucial for reproductive success of major crops during drought, salinity, temperature extremes, flooding, and nutrient stress. This helps us to focus on the strategies that enhance plant adaptation to all stresses and identify key responses that can be targets for plant breeding.

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Digging deeper into the GWAS signal with a little machine learning along the way

David Kainer
Oak Ridge National Laboratory

Genome Wide Association Studies, or GWAS, have become a standard tool for the discovery of the genetic basis of complex traits. For over a decade, results from GWAS have been used to guide experimentation, marker assisted selection and genetic engineering efforts. But for complex traits where we don’t have huge sample numbers (as with most plant studies!), GWAS outcomes can be very limited by multiple testing correction. Only loci that make it below the magic p-value threshold are deemed interesting. These loci often explain only a small fraction of the trait’s heritability, yet we know intuitively that many causal loci sit just ‘out of reach’. Here I will relate our efforts to relax those thresholds with the goal of reliably obtaining more of the trait genetic architecture. To deal with the peril of increasing false positives, multi-omic data sources such as gene expression and metabolic pathways can be fused into multiplex networks upon which network propagation algorithms tease apart the false positives from the true positives. I will demonstrate the process with examples in Arabidopsis and other species.

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The nature of exploitable variation

Bruce Walsh
University of Arizona

Bruce Walsh is a population and quantitative geneticist with very diverse interests in plant and animal breeding, evolutionary biology, and statistical methods.  He obtained a BS in Mathematical Population Biology from UC Davis, and a PhD in genetics from the University of Washington. He is currently a Professor of Ecology and Evolutionary Biology, Plant Sciences, and Public Health at the University of Arizona. He is perhaps best known for the two graduate textbooks on quantitative genetics that he coauthored with Mike Lynch (Lynch & Walsh, 1998, Genetics and Analysis of Quantitative Traits [a new version, along with Peter Visscher at UQ, is in the works]; and Walsh & Lynch 2018, Evolution and Selection of Quantitative Traits). He has taught almost 100 short courses on quantitative genetics in over two dozen countries, on all continents (except for Antarctica, where he is still awaiting an invitation). He is also an avid Lepidopterist, having described almost 30 new species of moths and has three species named after him.

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Plant Breeding for circular bioeconomy systems

Charlie Messina
University of Florida

Charlie Messina is a Professor of Predictive Breeding in the Department of Horticultural Sciences at the University of Florida. His program focuses on the development of prediction methods for agriculture and horticulture.

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