Smarter satellite winds: AI model boosts ocean weather forecasting

Aerospace Information Research Institute, Chinese Academy of Sciences

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Spatial performance of the CNN-SENet model. The subfigure a depicts RMSE of grid cells in the research area and subfigure b depicts land distribution within the research area.

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Credit: Satellite Navigation

Accurate monitoring of ocean surface winds is critical for predicting storms, ensuring maritime safety, and understanding climate dynamics. Yet traditional sensing techniques often fall short in coverage and efficiency. Now, a team of scientists has developed Convolutional Neural Network (CNN)-Squeeze-and-Excitation Network (SENet)—a new deep learning model that leverages satellite-based Global Navigation Satellite System-Reflectometry (GNSS-R) data to vastly improve wind speed retrieval. By integrating a specialized attention mechanism known as SENet into a convolutional neural network, the model hones in on the most relevant features, accelerating training and boosting accuracy. In tests across more than one million data points, CNN-SENet significantly outperformed conventional models in both speed and precision, opening new avenues for real-time, global ocean wind monitoring.

Monitoring wind over the ocean is not just about data—it's about survival. Ships, offshore platforms, and coastal cities depend on timely wind forecasts, particularly during extreme weather events. Traditionally, wind speeds have been measured using buoys, ships, and specialized satellites, but these approaches are expensive and offer limited spatial or temporal reach. Global Navigation Satellite System-Reflectometry (GNSS-R), which repurposes satellite navigation signals reflected off the sea surface, offers a more scalable and cost-effective alternative. Its ability to operate under all weather conditions and deploy on microsatellites makes it ideal for global applications. Yet despite its promise, extracting accurate wind data from GNSS-R signals remains a technical hurdle. Due to these challenges, there is a pressing need to develop advanced models capable of precise, efficient retrieval.

Addressing this challenge, researchers from Nanjing Tech University and the Chinese Academy of Sciences have introduced a novel model called CNN-SENet. The study (DOI: 10.1186/s43020-024-00157-2) was published in Satellite Navigation in June 2025. This model blends convolutional neural networks (CNNs) with the Squeeze-and-Excitation Network (SENet) attention mechanism to enhance feature extraction from GNSS-R Delay Doppler Maps. Trained on more than one million data points from NASA’s CYGNSS satellite and ERA5 reanalysis datasets, CNN-SENet aims to deliver more accurate and computationally efficient wind speed retrievals across global oceans.

CNN-SENet elevates traditional CNN architecture by embedding SENet modules between convolutional layers. These attention modules dynamically emphasize the most informative parts of the input, enabling the model to learn more effectively while cutting training iterations. The model was tested across a broad dataset compiled from CYGNSS satellite observations and ERA5 reanalysis wind speeds, spanning wind conditions from calm seas to 40 m/s gales.

The results were striking. CNN-SENet achieved a root mean square error (RMSE) of 1.29 m/s and an R² of 62.4%, outperforming the standard CNN (RMSE: 1.43 m/s) and the widely used Geophysical Model Function (GMF) method (RMSE: 1.91 m/s). Even under high wind conditions, where retrieval is most difficult, CNN-SENet maintained superior performance, with an RMSE of just 3.01 m/s—substantially lower than its counterparts.

The model also showed faster training efficiency, completing its learning in half the time of standard CNNs across various hardware configurations. Spatially, it performed best over open ocean regions, with 82% of analyzed areas achieving RMSE below 1.5 m/s. Temporal tests across different months confirmed the model’s consistency, indicating robust generalization over time. Together, these results highlight CNN-SENet as a promising tool for global, high-resolution ocean wind monitoring.

“Our aim was to create a smarter, faster model that can adapt to real-world variability in ocean environments,” said Dr. Dongliang Guan, co-author of the study. “By integrating SENet into the CNN framework, we've empowered the system to focus on what matters most—improving both efficiency and accuracy. This is especially critical for monitoring extreme weather systems like typhoons, where every minute counts.” The researchers believe this advancement will contribute significantly to building more agile, data-driven marine forecasting networks.

The practical implications of CNN-SENet extend far beyond academic performance. Its lightweight design and computational efficiency make it ideal for deployment on microsatellite constellations, offering the potential for near real-time global wind field monitoring. Such capabilities are vital for marine weather forecasting, disaster preparedness, and climate modeling. Looking ahead, the team plans to enhance the model by integrating additional environmental parameters—such as wave height and sea state—and refining the architecture for even faster processing. With continued innovation, CNN-SENet could become a core component in next-generation satellite observation systems, delivering smarter and more scalable solutions for ocean monitoring worldwide.

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References

DOI

10.1186/s43020-024-00157-2

Original Source URL

https://doi.org/10.1186/s43020-024-00157-2

Funding information

This research was supported by the National Key R&D Program of China (2021YFB3901301), the National Natural Science Foundation of China (42271420), the Natural Science Foundation for Young Scholars of Jiangsu Province, China (BK20220366) and Jiangsu Province Department of Natural Resources Science and Technology Innovation Project (JSZRKJ202406).

About Satellite Navigation

Satellite Navigation (E-ISSN: 2662-1363; ISSN: 2662-9291) is the official journal of Aerospace Information Research Institute, Chinese Academy of Sciences. The journal aims to report innovative ideas, new results or progress on the theoretical techniques and applications of satellite navigation. The journal welcomes original articles, reviews and commentaries.

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Journal

Satellite Navigation

DOI

10.1186/s43020-024-00157-2 

Subject of Research

Not applicable

Article Title

CNN-SENet: a GNSS-R ocean wind speed retrieval model integrating CNN and SENet attention mechanism

Article Publication Date

28-Jun-2025

 

Dangerous variant of salmonella still not eradicated – researchers point to the solutions

University of Copenhagen - Faculty of Science

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While we’ve all heard of salmonella in chickens, salmonella in cows is likely unknown to many. Nevertheless, Salmonella Dublin is a disease that has been present in cattle herds for decades – in Denmark as well as many other countries. And it is on the rise globally. It causes pneumonia, blood poisoning and abortions and kills many thousands of calves and cows every year.

Although Salmonella Dublin infects humans far less frequently than the more regular salmonella, there is every reason to take it seriously: it is significantly more dangerous and kills up to 12% of those who become infected. At the same time, it is often resistant to antibiotics. Infection can occur through contact with animals as well as through unpasteurised dairy products and undercooked meat.

Still, Denmark has not managed to eradicate the disease – despite a national eradication plan launched in 2008, which set out to completely eliminate the disease. Today, the infection rate is estimated to be around 5% of Danish cattle herds, down from 20-25% in 2008. In contrast, the infection has increased in recent years to about 18% of herds in the United States and as much as 60% in the United Kingdom.

“Salmonella Dublin is not just a serious threat in the barn. Globally, it is a potential public health risk that is likely to grow as antibiotic resistance spreads. This is a bacterium that kills people every year, and it is high time we do more to combat it,” says Dagim Belay, Assistant Professor at the Department of Food and Resource Economics.

He and fellow researcher Jakob Vesterlund Olsen are behind a new study examining the economic impact of Salmonella Dublin across all Danish dairy farms over a 10-year period.

Invisible Infection, High Cost

"Denmark has made great progress in the fight against this disease – so why have we not yet reached the goal? One possible reason is that farmers may not have a strong enough incentive to fight it. However, our research shows that the consequences are not only a matter of health – there are also hidden financial losses associated with infection,” says Senior Advisor Jakob Vesterlund Olsen from the Department of Food and Resource Economics.

The study shows that Salmonella Dublin leads to increased calf mortality, lower milk yield, higher medication costs and more veterinary treatments.

“The tricky thing about Salmonella Dublin is that it often flies under the radar. Many herds are infected without visible symptoms, meaning both the disease and the economic losses can develop gradually without being noticed. Infection reduces productivity and weakens the animals year after year – and the financial losses accumulate over time,” says Dagim Belay.

Cattle farms with high levels of infection face average additional annual costs of around EUR 11,300. But even herds with low levels of infection face financial losses. A typical herd of 200 dairy cows with low-level infection incurs extra variable costs of approximately EUR 6700 per year.

“Our estimates are conservative. They are based on data from a Danish system that already has a control programme – unlike most other countries. If similar estimates were made in the UK or the US, the economic costs would be significantly higher,” says Dagim Belay.

Time for Stronger Action

The researchers highlight a key problem in how Danish authorities currently monitor Salmonella Dublin. The Danish Veterinary and Food Administration measures the level of antibodies against the bacterium in the farm’s milk tank, and if the antibody level is below a certain threshold, the herd is deemed salmonella-free.

“Threshold-based regulation has been instrumental in helping Denmark substantially reduce the prevalence of Salmonella Dublin to its current low level. But the current threshold is rather arbitrarily set. And our data shows that production losses already occur at infection levels well below that threshold,” says Jakob Vesterlund Olsen.

“So, it is also crucial to give farmers stronger incentives to eradicate the problem. For example, by offering subsidies to farmers who invest in prevention, early detection and control measures, or by introducing a discounted milk price for milk from chronically infected herds,” says Dagim Belay.

Finally, the researchers urge authorities to provide targeted information to cattle producers about the hidden costs of Salmonella Dublin and about effective control strategies.

 

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ABOUT THE STUDY

• The researchers analysed how Salmonella Dublin impacted all Danish dairy farms during the period 2011–2021.
• The study is published in the journal Agricultural Economics.
   

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FACTS ABOUT SALMONELLA DUBLIN

• Salmonella Dublin is an infectious and multidrug-resistant variant of the Salmonella bacterium, adapted to cattle but capable of infecting humans and other animals.
• For cattle, Salmonella Dublin can cause pneumonia, blood poisoning, abortions and death. In humans – especially the elderly, children, and immunocompromised individuals – it often leads to blood poisoning, hospitalisation, and has a fatality rate of up to 12%.
• According to the Statens Serum Institut, 20–30 human cases are recorded annually in Denmark.
• There are documented cases of infection from contact with cattle, manure and equipment - even in people who have not eaten untreated food.
• Read more about Denmark’s efforts to combat Salmonella Dublin on the Danish Veterinary and Food Administration’s website.

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Journal

Agricultural Economics

DOI

10.1111/agec.70016 

Article Title

Economic Impacts of Salmonella Dublin in Dairy Farms:Panel Evidence From Denmark

Cool is cool wherever you are

Cool personality traits are surprisingly similar across cultures, study finds

American Psychological Association

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From Chile to China, cultures vary greatly around the globe, but people in at least a dozen countries agree about what it means to be cool, according to research published by the American Psychological Association.   

The researchers conducted experiments with almost 6,000 participants from countries around the world and found that cool people have surprisingly similar personalities. Even though Eastern and Western cultures often differ in many cultural attitudes, cool people were universally perceived to be more extraverted, hedonistic, powerful, adventurous, open and autonomous. 

“Everyone wants to be cool, or at least avoid the stigma of being uncool, and society needs cool people because they challenge norms, inspire change, and advance culture,” said co-lead researcher Todd Pezzuti, PhD, an associate professor of marketing at the Universidad Adolfo Ibáñez in Chile. 

The research was published online in the Journal of Experimental Psychology: General. 

The study included experiments from 2018 to 2022 in the United States, Australia, Chile, China (mainland and Hong Kong), Germany, India, Mexico, Nigeria, Spain, South Africa, South Korea and Turkey. The participants were asked to think of someone who they thought was cool, not cool, good or not good. They then rated the person’s personality and values. The researchers used the data to explore how cool people differ from uncool people and good people. 

Good people were perceived as more conforming, traditional, secure, warm, agreeable, universalistic, conscientious and calm. Cool people and good people aren’t the same, but there are some overlapping traits, said co-lead researcher Caleb Warren, PhD, an associate professor of marketing at the University of Arizona. 

“To be seen as cool, someone usually needs to be somewhat likable or admirable, which makes them similar to good people,” Warren said. “However, cool people often have other traits that aren’t necessarily considered ‘good’ in a moral sense, like being hedonistic and powerful.”

As the reach of the fashion, music and film industries grows worldwide, the meaning of cool “has crystallized on a similar set of values and traits around the globe" and has become “more commercially friendly," the journal article stated.

Does that mean coolness has lost its edge if Apple or Marvel movies are telling us what it means to be cool?

“Coolness has definitely evolved over time, but I don’t think it has lost its edge. It’s just become more functional,” Pezzuti said. “The concept of coolness started in small, rebellious sub-cultures, including Black jazz musicians in the 1940s and the beatniks in the 1950s. As society moves faster and puts more value on creativity and change, cool people are more essential than ever.” 

Only participants who were familiar with the slang meaning of the word “cool” were included in the study. Most of the experiments were conducted online so the findings may not be generalizable to rural areas without internet access.

Article: “Cool People,” Todd Pezzuti, PhD, Universidad Adolfo Ibáñez, Caleb Warren, PhD, University of Arizona, and Jinjie Chen, PhD, University of Georgia; Journal of Experimental Psychology: General, published online June 30, 2025.

Contact: Todd Pezzuti, PhD, may be contacted at todd.pezzuti@uai.cl.    

The American Psychological Association, in Washington, D.C., is the largest scientific and professional organization representing psychology in the United States. APA’s membership includes  173,000 researchers, educators, clinicians, consultants and students. Through its divisions in 54 subfields of psychology and affiliations with 60 state, territorial and Canadian provincial associations, APA works to advance the creation, communication and application of psychological knowledge to benefit society and improve lives.

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Journal

Journal of Experimental Psychology

DOI

10.1037/xge0001799 

Method of Research

Experimental study

Subject of Research

People

Article Title

Cool People

Article Publication Date

30-Jun-2025

Labels are everything: New study reveals role of popularity in news articles

‘Most read’ versus ‘most shared’ titles influence audience engagement

University of Georgia

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News readers often click on articles not based on topic but rather the behavior of their fellow audience members, according to new research from the University of Georgia.

And the way that news organizations label those articles could directly influence how much attention they receive and ultimately impact their revenue.

When you go to a news organization’s homepage, they typically label articles that readers are engaging with the most. The researchers focused on two common labels: “most shared” and “most read.”

“These types of labels are not going anywhere. Popularity even in news labels is a psychological phenomenon,” said Tari Dagago-Jack, lead author of the study and an assistant professor of marketing in the UGA Terry College of Business. “Popularity labels on news outlets are taking advantage of the idea that we follow the lead of others and that our decision-making is influenced by what other people are doing.”

Article section labels influence click rate

At first glance, you may assume that these labels, “most shared” and “most read,” mean the same thing: A lot of people checked out the article. But there’s a clear difference that consumers pick up on.

“If something is most shared, we might assume that means many people had to read it and then deem it interesting enough or important enough to pass it on,” Dagogo-Jack said. “But then there’s this other reality where we know a lot of things that are widely shared are often extremely frivolous like cat videos or funny memes.”

In nine surveys and experiments involving hundreds of people, the study found respondents interpreted “most read” stories as being more informative. “Most shared” articles were viewed as less serious and more entertainment based.

"The primary goal for reading news is to gain information, and the label ‘most read’ is a stronger signal of an article’s information value.” —Tari Dagago-Jack, Terry College

“We as readers have two primary motives: to be informed or to be entertained — that is, for a welcome diversion,” said Dagogo-Jack. “At a baseline level, we were finding that people were choosing ‘most read’ at a way higher rate than ‘most shared.’ The primary goal for reading news is to gain information, and the label ‘most read’ is a stronger signal of an article’s information value.”

That means if editors want certain articles to get more attention, they should tailor the label to the readers’ goals.

Knowing your audience, content is key for engagement

The same went for articles advertised on social media. Posts from faux news organizations that had captions describing a more educational article as “most shared” received fewer clicks.

This wasn’t the case, however, for news stories that were less serious and newsworthy. In that case, the “most shared” label worked as well as the “most read” label.

It’s a key message for reporters, editors and web developers: Know your audience and your content.

"People should ask themselves: Why am I even clicking on this thing? Is it just because everyone else read it?” —Tari Dagago-Jack

“For pop culture, sports or music — more entertainment — in those sections you should highlight what is ‘most shared,’” Dagogo-Jack said. “But for world news, politics and science sections, you should be using things like ‘most read’ or ‘most viewed.’”

Dagogo-Jack also recommends putting thought into labels. Ambiguous choices like “trending” or “most popular” may stump readers altogether, as there are so many things this could mean.

“Providing these lists helps us get over information overload or choice paralysis,” he said. “It’s a crutch and makes the decision process easier, but I often wonder: At what cost?

“You’re clicking on something that a lot of people like and social proof is valuable, but it may not necessarily provide what you are looking for, and you just gave up on the search. People should ask themselves: Why am I even clicking on this thing? Is it just because everyone else read it?”

This study was published in the Journal of Consumer Research and was co-authored by New York University assistant professor Jared Watson.

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Journal

Journal of Consumer Research

DOI

10.1093/jcr/ucaf017 

Article Title

Most Read Versus Most Shared: How Less (vs. More) Social Popularity Labels Influence News Media Consumption

 

Groundbreaking mobile app captures and documents bruises to help survivors of interpersonal violence

An interdisciplinary George Mason University research team is breaking new ground in using artificial intelligence to support victims of interpersonal violence

George Mason University

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The EAS-ID (Evidence-based AI Software for Injury Detection) project has successfully completed Phase 1: development of a working prototype of a mobile app designed to accurately capture and document bruises. Photo by Mary Cunningham, George Mason University

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Credit: Photo by Mary Cunningham, George Mason University

An interdisciplinary George Mason University research team is breaking new ground in using artificial intelligence to support victims of interpersonal violence. Led by Kat Scafide and Janusz Wojtusiak of the College of Public Health and David Lattanzi of the College of Engineering and Computing, the Evidence-based AI Software for Injury Detection (EAS-ID) project has successfully completed Phase 1: development of a working prototype of a mobile app designed to accurately capture and document bruises. 

The tool has the potential to transform how clinicians and frontline professionals identify, record, and communicate evidence of injury, particularly in cases of interpersonal violence.

The EAS-ID app acts as a digital guidance system—similar to mobile check-deposit apps that help users capture clear, usable images. When a clinician uses the tablet-based tool, the app detects the presence of a bruise and provides real-time guidance to ensure the image meets clinical and legal standards. A rectangle tracks the injury area, much like facial recognition technology, ensuring the final image captures exactly what’s needed to document the bruise effectively.

The research team announced $4.85 million in initial funding from the same anonymous donor in March 2024. 

“Initially, we were laser-focused on detection—how to identify whether a bruise was present,” said Scafide, a forensic nurse. “But Phase 1 taught us that detection is only a small part of the clinical and legal challenge. The real complexity lies in documentation.”

That documentation must be both clinically sound and legally reliable. Forensic nurses—the app’s initial target users—often assess injuries while juggling multiple tasks: shining a light, holding a camera, completing paperwork. The EAS-ID tool reduces that burden by enabling simultaneous photo capture and structured documentation.

The app’s workflow is tailored to the real-world conditions of forensic nursing. It walks users through a standardized documentation process built directly into the interface, making it possible to create accurate, consistent records that can hold up in court—even years later. 

“The documentation that nurses create is reviewed by many others in the criminal justice system,” noted Lattanzi, a civil engineer. “It must be reliable—not a liability.”

To ensure the app meets forensic standards, the team conducted extensive focus groups with practicing forensic nurses. These sessions were crucial to understanding not just what needed to be documented, but how clinicians make decisions in real time under pressure. Their insights helped shape the app into a useful tool with intuitive guide rails and legal relevance.

Based on Phase 1 progress, the team is preparing to broaden its focus to include a wider range of users. “We’re exploring how to adapt the app for clinicians—and even nonclinicians—who don’t have a forensic background but still need to document injuries,” said Scafide.

Wojtusiak, a machine learning expert, added: “Think of it like TurboTax. You don’t need to be a CPA to file your taxes. We want to make it possible for someone who sees fewer IPV cases—or who isn’t an expert in injury documentation—to still collect reliable evidence.”

Behind the app, a powerful AI engine is being trained to distinguish bruises from other skin discolorations and guide users through appropriate documentation steps. To train the AI, the team is building a massive, diverse dataset. So far, they’ve partnered with Inova Health System and Adventist Healthcare Shady Grove Medical Center to collect tens of thousands of images across different skin tones, body types, and medical conditions.

“Deep learning requires scale—and the team has set a goal of collecting one million images,” said Wojtusiak.

This summer, the team will launch a crowdsourcing initiative to expand the dataset beyond clinical settings. “All of our current data was collected in labs, under controlled conditions,” explained Scafide. “But real-world data is messier. We need to understand what the photos and data will look like when collected by the public, outside of protocols.”

The app’s architecture was designed with that in mind. Using machine learning, the app evolves over time—each new image improves its performance. This allows for continual refinement, even after the app is deployed.

The project has moved at an unusually fast pace for an academic endeavor, thanks in part to the support of students and research assistants whose contributions have accelerated development while gaining invaluable experience. Continued progress has been made possible by a second round of funding from the same anonymous donor.

With a patent pending on the app’s innovative integration of image capture and health assessment data, the EAS-ID team is now preparing to scale development, deepen partnerships, and explore commercialization pathways.

“Our goal is to get this technology into the hands of people who need it—quickly,” said Scafide. “The faster we can deploy, the faster we can support the professionals working to protect and care for victims.”

 

A surprising ally in the fight against the spotted lanternfly: Ants

Virginia Tech

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An ant on a leaf covered with spotted lanternfly honeydew.

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Credit: Photo by Scotty Yang for Virginia Tech.

Virginia may have a new ally in the fight against one of the most invasive insects threatening trees, crops, and other commodities.

Virginia Tech researchers, led by Assistant Professor Scotty Yang, in the Department of Entomology in the College of Agriculture and Life Sciences, have found a new way to use ants and determine if spotted lanternflies have invaded a new area.

The findings were published in two journal articles in Pest Management Science and Neobiota. 

Spotted lanternflies, originally from Asia, have been spreading across parts of the United States since their introduction to the country in 2014, damaging vineyards, ornamental trees, and even backyard gardens. The spotted lanternfly uses its straw-like mouthparts to feed on sap and then leaves behind a sugary substance called honeydew, which not only makes a sticky mess but also contains the insect's DNA.

Here’s where it gets interesting: Ants love honeydew. They search for it, eat it, bring it back to their nests, and share it with other ants. This connection planted an idea in Yang’s mind: Could these honeydew-collecting ants serve as an early warning system for spotted lanternflies?

Turns out, they can.

Yang, an affiliate with the Virginia Tech Global Change Center's Invasive Species Collaborative, found that ants that foraged in areas with spotted lanternflies carried traces of the bugs' DNA in their bodies — specifically, in the honeydew they’d eaten. By analyzing the ants in a lab, scientists could reliably detect whether spotted lanternflies were present in an area, even if the bugs themselves weren’t spotted directly.

“Ants are nature’s sugar seekers,” Yang said. “If there’s even a tiny drop of honeydew left behind by a spotted lanternfly, ants are likely to find it. They’re constantly on the move, searching for food, and their ability to cover a lot of ground makes them surprisingly effective at picking up traces of the spotted lanternfly.”

To check the ants for lanternfly DNA, the team used a method called environmental DNA testing. Just like people leave behind skin cells or hair, spotted lanternflies leave behind tiny bits of DNA in the honeydew they excrete as waste.

When the researchers collect the ants, they can analyze them for spotted lanternfly DNA using polymerase chain reaction, or PCR, testing that can identify even tiny traces of DNA specific to the lanternfly. 

The newly introduced method, called antDNA by Yang and his lab, proved to be both accurate and powerful. Ants that ate just one meal of honeydew from spotted lanternfly still carried the pest’s DNA up to five days later, and because ants roam widely, they detected lanternfly presence up to 100 meters, or 328 feet, away from known infestation spots.

Why early detection matters

The spotted lanternfly is a serious threat to economically important crops and can even be a nuisance in your backyard. It feeds on many types of plants, including grapevine, hops, and hardwood trees. As it feeds, it weakens plants and covers them in honeydew, which can lead to sooty mold growth and further weakening of the plant.

Lanternflies are a complex pest species, and once they invade an area, it may require several methods to get rid of them. Catching them early is preferred. The sooner they’re detected, the easier it is to stop them from spreading.

That’s what makes the antDNA method so exciting, Yang said. Current detection efforts often rely on people physically spotting the insects or their egg masses, which can be challenging until they appear in large numbers, but by then, lanternflies are much harder to combat. With this new approach, teams could simply collect the ants and run a the antDNA test, saving time, money, and the health of the spotted lanternfly host plants.

“One of the biggest advantages of using ants is that they live almost everywhere, such as forests, farms, cities – you name it,” Yang said. “Their constant search for food makes them ideal frontline samplers for spotted lanternfly DNA. This approach isn’t limited by habitat type, and thanks to well-established ant collection methods, we can easily scale it up.”

The implications of Yang’s findings go far beyond just the spotted lanternfly. Any insect that produces honeydew and leaves behind its DNA in doing so could potentially be tracked using this method. That means an earlier, smarter way to protect vulnerable crops, forests, and natural ecosystems.

Yang and his lab are now developing a field-ready antDNA kit that allows the molecular analysis to be done on site, giving results faster, sometimes even within the same day, making it easier to track and respond to new spotted lanternfly invasions in real time.

Original study: https://doi.org/10.1002/ps.8814

Original study: https://doi.org/10.3897/neobiota.98.151420

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Journal

NeoBiota

Article Title

Let ants find them: Using ants as eDNA samplers for detecting the invasive spotted lanternfly