Collaboration to develop sorghum hybrids to reduce synthetic fertilizer use and farmer costs

Donald Danforth Plant Science Center

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Veena Veena, PhD, MBA, principal investigator and director of the Plant Transformation Core Facility at the Donald Danforth Plant Science Center

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Credit: Donald Danforth Plant Science Center

ST. LOUIS, MO, January 24, 2025 - A new collaborative research team of leading plant scientists are developing sorghums with nitrogen-saving traits by utilizing the genetic diversity of wild relatives to improve resilience and productivity for grain sorghum producers. 

The project is part of a $38 million investment in nine projects by the U.S. Department of Energy, DOE, Advanced Research Projects Agency-Energy, ARPA-E, to develop advanced technologies for plants to increase nitrogen-use efficiency and reduce nitrogen pollution from U.S. bioenergy feedstocks.

Veena Veena, PhD, MBA, principal investigator and director of the Plant Transformation Core Facility at the Donald Danforth Plant Science Center is serving as a Co-PI on the project. Veena will provide specialized knowledge in genome modification technologies and will utilize advanced genetic engineering techniques to develop sorghum lines with enhanced traits, including improved nutrient cycling, increased resilience, productivity, drought resistance and.

The project is led by Sakiko Okumoto, PhD, AgriLife Research plant physiologist and associate professor at Texas A&M College of Agriculture and Life Sciences Department of Soil and Crop Sciences. 

The Texas A&M AgriLife Research team has been studying the potential of biological nitrification inhibition, BNI, a unique trait found in wild relatives, through previous research efforts to reduce fertilizer application and enhance environmental benefits. 

The technologies developed in the project will target the grain ethanol sorghum market, Okumoto said. By leveraging genetic diversity from wild varieties, new sorghum hybrids will offer unique opportunities for both growers and sorghum grain buyers to reduce costs by lowering fertilizer application levels.

Co-PIs at Texas A&M include, Nithya Rajan, PhD., Center for Greenhouse Gas Management in Agriculture and Forestry director, crop physiologist and professor;  Bill Rooney, PhD., sorghum breeder, professor and Borlaug-Monsanto Chair for Plant Breeding and International Crop Improvement; Sanjay Antony-Babu, PhD., microbiologist and assistant professor in the Department of Plant Pathology and Microbiology; and Aniruddha Datta, PhD., professor in the Department of Electrical and Computer Engineering in the College of Engineering.

About the Donald Danforth Plant Science Center
Founded in 1998, the Donald Danforth Plant Science Center is a not-for-profit research institute with a mission to improve the human condition through plant science. Research, education, and outreach aim to have impact at the nexus of food security and the environment and position the St. Louis region as a world center for plant science. The Center’s work is funded through competitive grants from many sources, including the National Science Foundation, National Institutes of Health, U.S. Department of Energy, U.S. Agency for International Development, and the Bill & Melinda Gates Foundation, and through the generosity of individual, corporate, and foundation donors.

For more information contact:
Karla Roeber, Vice President, Public and Government Affairs, kroeber@danforthcenter.org

New twist in mystery of dinosaurs' origin

University College London

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Nyasasaurus could be the earliest known dinosaur, or else a close relative of early dinosaurs.

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Credit: Mark Witton/The Trustees of the Natural History Museum, London

The remains of the earliest dinosaurs may lie undiscovered in the Amazon and other equatorial regions of South America and Africa, suggests a new study led by UCL (University College London) researchers.

Currently, the oldest known dinosaur fossils date back about 230 million years and were unearthed further south in places including Brazil, Argentina and Zimbabwe. But the differences between these fossils suggest dinosaurs had already been evolving for some time, pointing to an origin millions of years earlier.

The new study, published in the journal Current Biology, accounted for gaps in the fossil record and concluded that the earliest dinosaurs likely emerged in a hot equatorial region in what was then the supercontinent Gondwana – an area of land that encompasses the Amazon, Congo basin, and Sahara Desert today.

Lead author and PhD student Joel Heath (UCL Earth Sciences and the Natural History Museum, London) said: “Dinosaurs are well studied but we still don’t really know where they came from. The fossil record has such large gaps that it can’t be taken at face value.

“Our modelling suggests that the earliest dinosaurs might have originated in western, low-latitude Gondwana. This is a hotter and drier environment than previously thought, made up of desert- and savannah-like areas.

“So far, no dinosaur fossils have been found in the regions of Africa and South America that once formed this part of Gondwana. However, this might be because researchers haven’t stumbled across the right rocks yet, due to a mix of inaccessibility and a relative lack of research efforts in these areas.”

The modelling study drew on fossils and evolutionary trees of dinosaurs and their close reptile relatives, as well as the geography of the period. It accounted for gaps in the fossil record by treating areas of the globe where no fossils had been found as missing information rather than areas where no fossils exist.

Initially, early dinosaurs were vastly outnumbered by their reptile cousins.

These included the ancestors of crocodiles, the pseudosuchians (an abundant group including enormous species up to 10 metres long), and pterosaurs, the first animals to evolve powered flight (flying by flapping wings rather than gliding), who grew as big as fighter jets.

By contrast, the earliest dinosaurs were much smaller than their descendants – more the size of a chicken or dog than a Diplodocus. They walked on two legs (were bipedal) and most are thought to have been omnivores.

Dinosaurs became dominant after volcanic eruptions wiped out many of their reptile relatives 201 million years ago.

The new modelling results suggested that dinosaurs as well as other reptiles may have originated in low-latitude Gondwana, before radiating outwards, spreading to southern Gondwana and to Laurasia, the adjacent northern supercontinent that later split into Europe, Asia and North America.

Support for this origin comes from the fact it is a midpoint between where the earliest dinosaurs have been found in southern Gondwana and where the fossils of many of their close relatives have been discovered to the north in Laurasia.

As there is uncertainty about how the most ancient dinosaurs were related to one another and to their close relatives, the researchers ran their model on three proposed evolutionary trees.

They found strongest support for a low-latitude Gondwanan origin of the dinosaurs in the model that counted silesaurids, traditionally regarded as cousins of dinosaurs but not dinosaurs themselves, as ancestors of ornithischian dinosaurs.  

Ornithischians, one of the three main dinosaur groups that later included plant eaters Stegosaurus and Triceratops, are mysteriously absent from the fossil record of these early years of the dinosaur era. If silesaurids are the ancestors of ornithischians, this helps to fill in this gap in the evolutionary tree.

Senior author Professor Philip Mannion (UCL Earth Sciences) said: “Our results suggest early dinosaurs may have been well adapted to hot and arid environments. Out of the three main dinosaur groups, one group, sauropods, which includes the Brontosaurus and the Diplodocus, seemed to retain their preference for a warm climate, keeping to Earth’s lower latitudes.

“Evidence suggests the other two groups, theropods and ornithischians, may have developed the ability to generate their own body heat some millions of years later in the Jurassic period, allowing them to thrive in colder regions, including the poles.”

The earliest known dinosaurs include Eoraptor, Herrerasaurus, Coelophysis, and Eodromaeus.

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Journal

Current Biology

DOI

10.1016/j.cub.2024.12.053 

Method of Research

Computational simulation/modeling

 

Researchers enhance flood season rainfall predictions by combining machine learning and climate system model

Institute of Atmospheric Physics, Chinese Academy of Sciences

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As climate change leads to more frequent and intense extreme precipitation events, accurately predicting rainfall during the flood season has become increasingly critical.

A recent study has employed machine learning (ML) algorithms to address the nonlinear challenges faced by traditional models in predicting flood season rainfall, resulting in significant improvements in accuracy. The findings were published in Advances in Atmospheric Sciences.

Current predictions for flood season rainfall rely largely on outputs from climate system numerical models, which often contain systematic biases. To correct these outputs and reduce errors, researchers traditionally combine historical observational data with statistical methods.

This approach, known as the dynamical-statistical method, has its limitations. Prediction errors from numerical models tend to grow nonlinearly over time, and traditional correction methods, which primarily rely on linear approaches, struggle to effectively address these errors.

Recognizing ML’s strength in managing nonlinear relationships, the study applied the LightGBM algorithm to enhance the dynamical-statistical correction method. In trials conducted from 2019 to 2022, the predictions improved significantly, with the prediction score (PS) increasing from 68.6 to 74—an improvement of 7.87%. This represents a 6.63% enhancement over traditional dynamical-statistical methods, substantially boosting the accuracy of flood season rainfall predictions.

Many data-driven ML methods used for climate prediction often lack sufficient physical interpretability. To address this issue, the researchers carefully selected meteorological factors with clear physical connections to rainfall and integrated them into the climate system model. The team also quantified the contribution of each forecasting factor, offering a clearer understanding of the physical significance of the predictors used.

The study emphasizes a key point: relying solely on either physical models or ML models to improve predictions of flood season rainfall has inherent limitations. This study explores a climate prediction method that effectively integrates ML with physical models.

The rapidly evolving fields of artificial intelligence and big data offer new opportunities to optimize and refine model outputs, addressing nonlinear and complex challenges that traditional dynamic-statistical methods cannot resolve.

This study proposed a feasible approach to developing the traditional dynamic-statistical method into a dynamic-ML method.

Despite the progress, challenges remain.

“Our next steps will focus on extracting pre-existing and real-time signals from research on flood season precipitation formation mechanisms to develop dynamic-ML method with stronger physical interpretability,” said Dr. YU Haipeng, the corresponding author from Northwest Institute of Eco-Environment and Resources of the Chinese Academy of Sciences.

This research marks a significant step forward in precipitation prediction and offers valuable insights for developing future meteorological methods that integrate artificial intelligence and big data.

“Our ultimate goal is to create an efficient, stable, and interpretable system combining climate system models and ML techniques for predicting flood season rainfall, helping to mitigate the impacts of extreme precipitation and related disasters,” said Dr. YU.

As technology continues to advance, integrating physical mechanisms with ML-based prediction methods holds great potential for addressing the challenges posed by climate change.

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Journal

Advances in Atmospheric Sciences

DOI

10.1007/s00376-024-4191-x 

Article Title

A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

Battery-powered electric vehicles now match petrol and diesel counterparts for longevity

University of Birmingham

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Battery-powered electric vehicles are now more reliable and can match the lifespans of traditional cars and vans with petrol and diesel engines - marking a pivotal moment in the drive towards sustainable transportation, a new study reveals. 

Researchers used nearly 300 million UK Ministry of Transport (MOT) test records charting the ‘health’ of every vehicle on the United Kingdom’s roads between 2005 and 2022 to estimate vehicle longevity and provide a comprehensive analysis of survival rates for different powertrains. 

The international research team found that, although early Battery Electric Vehicles (BEVs) were less reliable than internal combustion engine vehicles (ICEVs), rapid advances in technology have enabled newer BEVs to achieve comparable lifespans, even under more intensive use.  

Researchers found that BEVs demonstrated the most rapid improvement in reliability, with a 12% lower likelihood of failure (hazard rate) for each successive year of production, compared to 6.7% for petrol and 1.9% for diesel vehicles. 

Publishing their findings today (24 Jan) in Nature Energy, researchers from the University of Birmingham, London School of Economics and Political Science (LSE), University of California San Diego, and University of Bern, Switzerland, reveal that, on average, BEVs now have a lifespan of 18.4 years and can travel up to 124,000 miles, surpassing traditional petrol cars in mileage. 

They also identify top-performing brands in terms of vehicle longevity. Tesla leads among BEVs. For petrol and diesel vehicles, Audi and Skoda are the best performers, respectively. 

Co-author Dr Viet Nguyen-Tien, from the LSE, commented: “Our findings provide critical insights into the lifespan and environmental impact of electric vehicles. No longer just a niche option, BEVs are a viable and sustainable alternative to traditional vehicles - a significant step towards achieving a net-zero carbon future.” 

Co-author Robert Elliott, Professor of Economics at the University of Birmingham, commented: "BEVs offer significant environmental benefits, especially as Europe switches to a more renewable energy mix. Despite higher initial emissions from production, a long-lasting electric vehicle can quickly offset its carbon footprint, contributing to the fight against climate change - making them a more sustainable long-term option. 

"Our findings offer consumers reliable data to make informed decisions about their vehicle purchases, whilst policymakers can use our insights to shape regulations and incentives that promote the adoption of durable and environmentally friendly vehicles and plan ahead their end-of-life treatment." 

The study highlights the importance of advances in technology in promoting the adoption of BEVs. It also provides valuable insights for fleet replacement strategies and planning how to effectively recycle electric vehicles at the end of their working life.  

ENDS 

For more information, interviews or an embargoed copy of the research paper, please contact Tony Moran, International Communications Manager, University of Birmingham, tel: +44 (0)7827 832312: email: t.moran@bham.ac.uk  

Notes to editor: 

• The University of Birmingham is ranked amongst the world’s top 100 institutions. Its work brings people from across the world to Birmingham, including researchers, teachers and more than 8,000 international students from over 150 countries. 

• ‘The Closing Longevity Gap between Battery Electric Vehicles and Internal Combustion Vehicles in Great Britain’ - Viet Nguyen-Tien, Chengyu Zhang, Eric Strobl, and Robert J R Elliott is published by Nature Energy. 

 

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Journal

Nature Energy

Method of Research

Data/statistical analysis

Subject of Research

Not applicable

Article Title

The Closing Longevity Gap between Battery Electric Vehicles and Internal Combustion Vehicles in Great Britain

Article Publication Date

24-Jan-2025

 

Seagrass meadows as natural climate protectors

New major project investigates potential of seagrass meadows as carbon sinks

Helmholtz Centre for Ocean Research Kiel (GEOMAR)

Seagrass meadows promote biodiversity, contribute to coastal protection by attenuating waves and improve water quality. They are also highly effective at storing carbon dioxide (CO₂), as the underwater plants sequester carbon in their leaves and roots as well as in the surrounding sediments.

The GEOMAR Helmholtz Centre for Ocean Research Kiel, in cooperation with the Kiel University (CAU) and the State Office for the Environment of Schleswig-Holstein (Landesamt für Umwelt, LfU), has launched a new project to study the role of seagrass meadows as natural carbon sinks and to develop strategies for their conservation and restoration.

The name of the project, ZOBLUC, stands for “Zostera marina as a Blue Carbon Sink in the Baltic Sea” – Zostera marina being the scientific name for seagrass. The project is funded by the German Federal Environment Ministry's Nature-based Climate Action Programme (ANK) and state funds, with a total budget of around €6 million.

Three Focus Areas for Seagrass Conservation

“Seagrass meadows are like underwater peatlands,” explains the scientific project leader, Dr Thorsten Reusch, Professor of Marine Ecology at GEOMAR. “They store carbon, which is preserved in oxygen-poor sediments for centuries.” The project will examine under which conditions seagrass meadows store the most CO₂ to find blue carbon hot spots, which in turn would be prime areas for protection. Reusch: “For example, areas with strong wave-driven erosion store less carbon than calm bays with faster sedimentation.” The research will not only quantify the carbon storage capacity of seagrass meadows but also model how it might change under different environmental conditions.

Another focus of GEOMAR is the restoration of seagrass meadows. It is crucial to ensure that restored meadows are resilient and sustainable. “There’s little point in replanting seagrass that won’t survive rising water temperatures in a few years’ time”, says Reusch. Experimental studies will expose seagrass to various stressors in order to cultivate robust, climate-resilient populations and practice ‘assisted evolution’.

Community Involvement in Underwater Gardening

The third focus is on involving local people in the restoration process. After developing training programmes and testing small-scale seagrass restoration in previous years, GEOMAR now plans to significantly expand its efforts with the help of volunteers. Reusch: “The pilot phase has been successfully completed; now we’re scaling up.”

This support is urgently needed, as the most reliable way to restore lost seagrass meadows is still to plant individual shoots manually by diving. Reusch says: “It’s important to complete the training course and only use areas that we have checked for suitability for restoration.”

Diving clubs and NGOs will use volunteer divers to plant seagrass in scientifically selected restoration sites. Observational data collected during these efforts will be analysed at GEOMAR to refine future restoration practices.

The development of other planting techniques, such as seeding, is the focus of the parallel project SeaStore II, which started last September.

Mapping with Multibeam Sonar and Drones

The first step, however, is a comprehensive mapping of the existing seagrass meadows in the Baltic Sea. Professor Natascha Oppelt and Dr Jens Schneider von Deimling from CAU and their teams, will use remote sensing methods that combine advanced optical and acoustic surveying technologies. CAU will also be responsible for monitoring the newly planted areas using drones.

Results from ZOBLUC will be shared through workshops and policy recommendations to advance the protection and restoration of seagrass meadows in the Baltic Sea.

 

Background: Blue Carbon

Blue Carbon is the carbon dioxide stored by marine and coastal ecosystems such as mangroves, salt marshes, and seagrass meadows. Seagrass meadows sequester carbon in the form of dead biomass and organic sediment particles that remain in the oxygen-poor seabed for centuries – much like peatlands on land.

Background: Assisted Evolution

Assisted Evolution is a technique that aims to accelerate the evolutionary adaptation of organisms to make them more resilient to environmental change. In this project, seagrass plants are exposed to experimental heat waves in GEOMAR’s climate chambers. This approach identifies potentially heat-tolerant local populations and uses advanced methods – from cellular physiological reactions (metabolomics) to genetic analysis (gene expression studies) and microbiome research – to understand the mechanisms behind plant resilience.

 

Microbial solutions for boosting seaweed farming and carbon capture

KeAi Communications Co., Ltd.

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Illustration showing the overview of seaweed-associated microbes,  their beneficial functions functions that shape seaweed health and resilience against pathogens and environmental change. The right side of the seaweed shows the current challenges in seaweed microbiome manipulation.

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Credit: Shailesh Nair

Seaweed farming has captured global attention as a potential solution to remove atmospheric carbon dioxide and offer eco-friendly alternatives to carbon-intensive food and industrial products. However, the successful expansion of seaweed farming from a regional industry into a global solution faces major hurdles due to changing oceanic conditions, increasing pathogenic diseases and nutrient limitations.

In a study published in the KeAi journal Green Carbon, researchers from the Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT), Chinese Academy of Sciences (CAS), revealed how manipulating the microscopic life living on seaweed can contribute to developing  industrial-scale seaweed farming and boost its potential for fighting climate change.

 “A diverse community of microbes live on seaweed, much like probiotics for seaweed – specific microbes can protect seaweed from diseases, provide essential nutrients, and help them thrive in challenging conditions,” explains corresponding author Yongyu Zhang. "This is particularly important as our previous study has shown that rising ocean temperatures and acidification will likely increase seaweed pathogenic diseases.”

The research highlights the areas that need to be focused on to overcome current limitations in seaweed microbiome manipulation, such as complete knowledge regarding the total microbiome composition and timing of inoculation.

“Early life stages of seaweeds, being more susceptible to microbial colonization, present a critical window for establishing beneficial microbes that might persist throughout the seaweed's life cycle,” says first author Shailesh Nair., “Some seaweeds can even pass these beneficial microbes to their offspring, suggesting potential long-term benefits across generations.”

The researchers propose a framework for future seaweed microbiome manipulation, emphasizing the need for integration of advanced technologies like multi-omics, high-throughput isolation techniques, artificial intelligence-based tools and robust validation.

"Microbial solutions must be deployed for sustainable macroalgae farming,” adds Zhang. “By harnessing the power of beneficial microbes, farmers could potentially create more stable and productive seaweed farms, making large-scale ocean farming more feasible than ever before.”

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Journal

Green Carbon

DOI

10.1016/j.greenca.2024.11.001 

Method of Research

Systematic review

Subject of Research

Not applicable

Article Title

Engineering microbiomes to enhance macroalgal health, biomass yield, and carbon sequestration