Hundreds of US government drones have switched from border surveillance to a different surveillance mission this summer—looking for signs of screwworm infestations in wild animals and livestock herds.

The flesh-eating New World Screwworm is the parasitic larva that emerges from eggs laid by flies in the open wounds or body openings of warm-blooded animals and humans, with untreated cases potentially leading to severe injury or death. Since the first screwworm cases were detected in South Texas in June, the US Department of Agriculture and US Customs and Border Protection have been conducting “one of the most extensive animal-health surveillance operations in the country,” the USDA said on August 10 in social media posts on platforms like X and Facebook.

The effort involves at least 200 drones owned by the Department of Homeland Security, which includes the Customs and Border Protection (CBP) agency. But the actual number in use "varies depending on availability and need," a USDA spokesperson told Ars.

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Whether you’re looking for medical advice or tips on industrial agriculture, one thing is abundantly clear: never trust an AI chatbot without first getting a second opinion, preferably from a human who has actual expertise in the topic.

That’s the takeaway from an incident in the small city of Chuzhou, China, after a large langue model dispensed some advice that led to the untimely death of 25 acres worth of produce.

According to the Taiwanese publication CTWANT, a 67-year-old farmer surnamed Wu decided to start consulting an AI chatbot for advice nearly a year ago. He was reportedly skeptical at first, though the farmer began to let his guard down after some early successes with the AI’s farming tips.

Since that time, Wu has come to rely on his LLM for everything from fertilizing guidance to scheduling various tasks around the farm. After months of fruitful consultations, he decided to follow his AI chatbot’s new pesticide plan to the letter, letting loose on some 25 acres of precious sesame seedlings, all without ever double-checking with an expert or outside documentation.

The plan generated for him was basically a Long Island ice tea of agro-chemicals: a mix of “high-efficiency flupyridine” and “flufenazate” for pesky weeds, with plenty of “thiamethoxam” and “emamectin benzoate” for bugs and other pests, CT reported.

Not even a day after treatment, Wu says his juvenile sesame crop began to wither and die.

Per a video interview later translated by Tom’s Hardware, the farmer offered some hard-earned advice to any other growers looking to use his concoction: “If you spray it, the next day the seedlings won’t survive.”

“Both the grass and the seedlings will die, and the seedlings will die even faster,” Wu lamented.

It’s just the latest case of an LLM cooking up some slop that lands a professional in hot water. If nothing else, Wu’s in good company: he joins a host of other dupes across the legal, medical, financial, education, and media industries who’ve likewise fallen prey to an AI chatbot’s inaccurate output.

More on farms: The Diarrhea Lettuce Company Has Been Linked to Forced Labor

The post Farmer Horrified as AI Gives Bad Advice That Kills 25 Acres of Crops appeared first on Futurism.

Scientists in Arkansas have developed a machine-learning approach that can identify potentially disease-causing strains of a poultry bacterium by analyzing not only which genes are present, but also how those genes are arranged across the genome. The method focuses on the “genetic neighborhoods” surrounding genes, offering a new way to distinguish harmful strains of Enterococcus cecorum from closely related strains that do not cause disease.

E. cecorum is commonly found in poultry environments, and many of its strains are harmless. However, pathogenic strains can cause arthritis, bone infections and lameness, creating serious animal-welfare problems and economic losses for poultry producers. Because pathogenic and nonpathogenic strains can share many of the same genes, identifying the genetic features associated with disease has been challenging.

The research team, led by Aranyak Goswami of the Arkansas Agricultural Experiment Station’s Center for Agricultural Data Analytics, examined the organization of genes within genomic islands. These are segments of DNA that bacteria often acquire from other microorganisms through horizontal gene transfer. Genomic islands can carry genes involved in antibiotic resistance, bacterial survival, movement of DNA and virulence, making them important regions for understanding how pathogens emerge.

Rather than treating the bacterial genome as a simple list of genetic components, the researchers analyzed it as a structured map. They investigated which genes occurred near one another, the order in which they appeared and the way groups of neighboring genes formed recurring units known as genomic-island cassettes. This architecture provided information that could be missed when genes are examined individually.

“The machine-learning model recognizes patterns in gene order much like it recognizes patterns in language,” Goswami said. In the same way that a language model can learn that certain words frequently appear together, the computational system learned that particular combinations and arrangements of bacterial genes were associated with pathogenic strains. The approach therefore captures relationships among genes rather than relying only on the presence or absence of individual DNA sequences.

For the proof-of-concept study, the researchers analyzed the genomes of 145 E. cecorum strains isolated from poultry. The dataset included 95 nonpathogenic strains and 50 pathogenic strains capable of causing illness. The analysis found that disease-associated strains were more likely to contain genomic islands enriched in genes linked to antimicrobial resistance and the transfer of genetic material between bacteria.

Those findings do not mean that every bacterium carrying such genes will necessarily cause disease. Instead, the researchers describe the system as an exploratory classification and research tool. It identifies patterns that may help scientists investigate why some bacterial lineages become harmful, while also providing clues about how resistance and virulence traits move through bacterial populations.

Current monitoring methods for E. cecorum often depend on culturing the bacterium or screening for specific genes. Such techniques remain valuable, but they may overlook broader genomic relationships. The new pipeline could complement these approaches by evaluating the wider context in which genes occur. Additional testing with larger and more geographically diverse datasets will be necessary before the method can be used for routine flock surveillance or diagnostic decision-making.

The researchers believe the strategy could eventually be adapted to other bacterial species affecting animals, humans, wildlife and plants. Goswami’s team is beginning to examine Enterococcus faecalis, a close relative of E. cecorum and a frequent cause of hospital-acquired infections in humans. They also plan to apply the pipeline to Escherichia coli and other bacteria to study how nonpathogenic lineages acquire the genomic configurations associated with disease. The study, published in Frontiers in Microbiology, demonstrates how machine learning and comparative genomics can reveal hidden signals in bacterial DNA and may help researchers track the evolution of emerging pathogens.

Subject of Research: Animals

Article Title: Genomic-island cassette architecture provides interpretable signal for exploratory classification of poultry-associated Enterococcus cecorum lineages

News Publication Date: 7-Jul-2026

Web References: https://doi.org/10.3389/fmicb.2026.1882753

References: Frontiers in Microbiology, DOI: 10.3389/fmicb.2026.1882753

Image Credits: UA University Relations photo by Chieko Hara

Keywords: artificial intelligence, machine learning, deep learning, computational biology, bacterial pathogens, Enterococcus cecorum, genomic islands, genomic architecture, antibiotic resistance, poultry disease, pathogen surveillance, comparative genomics

The global expansion of chicken farming has created conditions that allow Campylobacter to spread, mix and adapt more readily. Commercial poultry farms now hold billions of chickens, creating a vast habitat where bacteria can move, mix and adapt. An analysis from the Ineos Oxford Institute for Antimicrobial Research at the University of Oxford found that [...]

A new simulation study from the University of Illinois Urbana-Champaign suggests winter canola could be profitable and environmentally beneficial if added to a conventional corn-soy rotation in the U.S. Midwest.

In the Bolivian Altiplano, fewer Aymara farmers are relying on local weather knowledge to schedule farming tasks, like choosing the best dates to plant crops and predicting a frost or drought. At the same time, there is growing doubt about whether these traditional indicators remain relevant today in the context of rapid social, economic, and climatic changes. 

Farmers are struggling because the National Weather Service of Bolivia (SEHNAMI) fails to provide useful weather forecasts due to the geographical complexity of the Andes and a scarcity of weather stations. In addition, many farmers can’t access this information because SEHNAMI lacks local outreach programs to deliver reports directly to them. In a region with a weak technical forecasting system, local knowledge is a vital resource, but its use is declining.

Scientists in the past focused on preserving local weather knowledge or discussing how it might help communities adapt to climate change. However, very few researchers have scientifically validated local weather indicators, since doing so requires many years of historical meteorological data to establish statistical “skill” in local forecasting. 

Faced with this gap, researchers in the US and Bolivia recently set out to validate indigenous indicators in 2 Bolivian municipalities: Umala in the Central Altiplano and Ancoraimes in the Northern Altiplano. To do this, they paired each traditional weather sign with a measurable variable, like temperature, that could approximate it. This approach allowed them to directly compare traditional observations with scientific data.

The researchers wanted to determine whether traditional weather knowledge is still accurate and relevant under current conditions, since validating these methods would strengthen local knowledge and benefit the schools and policies that promote it. To test this, the researchers worked with 6 Aymara communities. First, they conducted workshops with local leaders and experts to compile a set of weather-forecast indicators. Then, they surveyed 95 farmers to rank the reliability of these indicators. 

Through discussions with these communities, the team identified 13 weather indicators in the Central region and 20 in the Northern region. These indicators included specific plants, animals, and physical factors like constellations or winds that the farmers used to decide when and where to plant crops, and to predict weather conditions for the next season. The researchers focused on 2 key indicators that the farmers ranked as most reliable: the presence or absence of moisture under rocks on the Fiesta de San Juan on June 24th, and the flowering patterns of specific plants, called Thola and Sank’ayu. The farmers used the San Juan indicator to predict whether the upcoming year would be rainy or dry, and the plants to determine the most favorable dates for planting to avoid agricultural risks like frosts.

Finally, the researchers compared forecasts based on these 2 signs with over 30 years of meteorological data from nearby weather stations. In both cases, they used the minimum daily temperature as the measurable way to represent these local signs scientifically. Their results showed that the minimum daily temperature on the Fiesta de San Juan could explain more than half (55.5%) of the changes in rainfall during the growing season. They also confirmed that severe frosts that “burned” Thola and Sank’ayuthe flowers were followed by periods without rain, validating the farmers’ strategy of delayed planting.

The researchers concluded that local weather indicators used by Aymara farmers are most reliable for seasonal planning, especially in predicting the start of the rainy season. They stated that this result helps legitimize traditional knowledge and empower the community. For example, these communities now hold regular meetings to discuss forecasts and share this information with their neighbors via WhatsApp groups. 

However, the team acknowledged that local knowledge was limited to short-term forecasting, as it only provided warnings a few hours in advance. Farmers need alerts several days in advance to effectively reduce their vulnerability to events such as frosts or hail. For this reason, the researchers suggested that the next step will be to co-produce forecasts by combining meteorological science with traditional knowledge.

The post Testing local weather knowledge in the Bolivian Altiplano appeared first on Sciworthy.

A native Australian millet may carry the genetic fingerprints of thousands of years of Aboriginal harvesting, storage, and plant management. Seen from the air, Channel Country resembles a vibrant and vast tapestry, with a network of waterways crisscrossing the land. Spread across more than 280,000 square kilometers in outback Australia, it is one of the [...]

When the United States ratified the 13th amendment in 1865, federal lawmakers very nearly outlawed slavery for good — but not entirely. Tucked within arguably the most important corner of the US constitution is a massive caveat: “neither slavery nor involuntary servitude, except as a punishment for crime whereof the party shall have been duly convicted, shall exist within the United States” (emphasis added.)

In the 160-some years since that amendment, a quieter type of forced servitude has lived on in the US: prison labor. From the debt peonage of the post-Civil War reconstruction era to the privatized contracting of the 21st century, prison labor is a massive money maker, generating $11 billion worth of revenue in 2022 alone.

As horrifying a thought as it is, one of the companies still benefiting from the practice is in the news for another reason: spreading a gut-busting diarrhea parasite through mass-produced shredded lettuce in grocery stores and fast food outlets.

It turns out that Taylor Farms, the agricultural company widely believed to be behind the cyclospora outbreak currently raging throughout the US, is also heavily involved in modern-day forced labor.

In reporting from 2023 that was resurfaced this week on social media, the publication Prison Legal News revealed that Taylor Farms was contracting labor from the Arizona Department of Correction, Rehabilitation, and Reentry for the low, low price of just $4.75 an hour — far below the cost to pay a non-incarcerated worker the federal minimum wage. (And to be clear, that’s not the hourly wage paid to the inmate, which is capped at $1.50 in Arizona.)

Taylor Farms is just one firm involved in the practice in Arizona. Others include Hickman’s Egg Farms, NatureSweet, and Televerde, each of which contracted labor from Arizona DCRR’s for-profit arm, Arizona Correctional Industries. That company’s job is basically to churn out bulk goods for the state of Arizona, like license plates, though it also makes quite a bit of money selling the labor-hours of incarcerated people to private companies.

Worse yet, some of those incarcerated workers may have been here as non-citizens — meaning it would be illegal to employ them in the same low-wage jobs if they weren’t being held in detention. As Prison Legal noted at the time, at least 26 prisoners employed by these companies had been detained by ICE, meaning that outside of incarceration, hiring them would have been illegal. To put it bluntly: their status as prisoners was the only thing that made the arrangement legal.

In all, the DCRR told Prison Legal it had hired out 15,700 “Mexican nationals” between 2008 and 2023, though couldn’t say how many of those workers were undocumented immigrants.

As Ruben Reyes, director of the American Immigration Lawyers Association told the publication at the time: “I’m venturing a guess that a large majority of the people who are labeled a Mexican national by [DCRR] are unauthorized to work here.”

Put into context, the revelation is a horrifying twist in an already nauseating story of corporate greed and deregulation. Though the institution of slavery may have been formally abolished, its legacy lives on — fully embraced by the for-profit companies pumping our food supply full of parasites.

Taylor Farms didn’t respond to a request for comment.

More on incarceration: Prisoners Alarmed to Discover That a Startup Is Training an AI Based on Their Phone Calls

The post The Diarrhea Lettuce Company Has Been Linked to Forced Labor appeared first on Futurism.

Two plants that cause neurotoxicity and paralysis in the tiniest doses are also known to counter pain, malaria, cancer and pests. For the first time, researchers discovered a way to recreate these powerful compounds in the lab, helping lead the way to improved, naturally sourced therapeutics.

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Today, humans speak or use signs in approximately 7,500 different languages. However, this figure, impressive as it may seem, represents only a snapshot of a constantly changing history, and questions about the evolution of linguistic diversity have remained among the most elusive for science for decades. How many languages existed before the appearance of written […]

Consumers and agricultural workers rejoice: the Trump administration has killed a key regulation meant to keep toxic human and industrial waste sludge from our food supply, because toxic sludge is apparently not a threat to public health.

On Monday, the Guardian reported that the Environmental Protection Agency is tossing out a major body of research that formed the basis for regulations which would have effectively limited the amount of sewage byproduct we’re allowed to spray into the environment.

The research, published not even two years ago, was conducted in order to study the consequences of toxic PFAS “forever chemical” compounds in treated sewer sludge — called “biosolids” in the wastewater treatment industry. The findings showed that any amount of PFAS above 1 part per billion in sewer sludge used as fertilizer represents an increased cancer risk for farmers, as well as consumers.

That’s a problem, because previous EPA tests have found PFAS levels as high as 9.4 parts per billion in sludge used for agricultural purposes.

The Trump administration, however, says that’s not a problem, because it’s not like we’re spraying biosolids on everything — and so what if a few farm workers get cancer? In a nine-page draft memorandum released by the agency’s Office of Water, the EPA justified the decision by blasting previous EPA research, saying that earlier study created a “misconception” that “all biosolids and sewage sludge use and disposal practices will negatively affect the public.”

“Currently data does not indicate that there are widespread impacts to the food supply from biosolids containing PFOA and PFOS at the national level, and the general public is not likely to be exposed to sewage sludge-impacted foods,” the new draft insists. “The EPA estimates that sewage sludge is applied to less than 1 percent of America’s farmland annually.”

As with any data coming out of the Trump administration, these factual claims should be taken with a hefty grain of salt. Even assuming that basic assertion is correct, it still leaves the farmers and agricultural workers laboring on that farmland exposed.

“It’s shocking for the EPA to take a scientific assessment and simply throw it out,” Laura Dumais, an attorney with the non-profit Public Employees for Environmental Responsibility told the Guardian. “Basically, they’re saying: farmers’ lives don’t matter.”

It’s also a particularly grim decision in light of the cyclospora outbreak currently roiling the US. Though cyclospora is a parasite and not a type of PFAS, studies have identified agricultural biosolids as a potential source of the gut-busting organism in the food supply. (Also noteworthy is the fact that the company broadly suspected to be responsible for the outbreak, Taylor Farms, made a substantial donation to Donald Trump’s MAGA Inc just days after the FDA pushed back a major regulation on food traceability.)

And as the Trump administration strips regulations that would clamp down on sewer sludge contamination in industrial agriculture, it acknowledges that “approximately 20 percent of sewage sludge managed each year is sold directly to the public or applied to sites where the public might be exposed.”

Rather than continuing with regulations that would make the public safer, the new EPA memorandum advises Americans to “research the supplier of the sewage sludge” and avoid “application of sewage sludge in locations where children may have access to the soil.”

For public health advocates like Dumais, the move amounts to a complete dereliction of the EPA’s duty to the public.

She told the Guardian that “it’s shocking that the EPA is willing to throw all of these people under the bus and the EPA’s solution here is ‘do your own research — we’re not going to regulate anything, so if you think it’s dangerous then figure it out for yourself.'”

More on Trump: Trump Administration Scrapping Nuclear Energy Rules Requiring Plants to Keep Radiation Levels “As Low as Reasonably Achievable”

The post Trump Administration Declares Toxic Sewer Sludge Not a Threat to Public Health appeared first on Futurism.

Le café fait vivre environ 125 millions de personnes dans le monde. Pourtant, près d'un producteur sur deux vit encore sous le seuil de pauvreté, alors que jusqu'à la moitié des terres adaptées à la culture du café arabica pourrait disparaître d'ici 2050 sous l'effet du changement climatique.

Cadmium (Cd) contamination is a growing threat to food safety, and rice is one of the most vulnerable crops. Because rice plants can accumulate cadmium from contaminated soils more readily than many other staples, Cd can become a major dietary exposure route for large parts of the world’s population. Yet attempts to lower cadmium often create trade-offs—reducing uptake of essential nutrients or weakening plant performance.

A new study from Okayama University, Japan, and collaborating researchers in China reports a precision-editing strategy designed to avoid those trade-offs. The team focused on the rice metal transporter gene OsNramp5, which is known to move metals such as manganese and cadmium, and used base-editing to search for a beneficial point mutation within the gene rather than disabling it.

Using adenine and cytosine base editors, the researchers generated more than 1,600 genome-edited rice lines and screened them for reduced cadmium accumulation. Their saturation mutagenesis approach targeted OsNramp5 to identify variants that kept normal plant physiology while limiting Cd buildup in grain.

The key breakthrough was the I441T substitution: changing isoleucine to threonine at amino acid position 441. This single change reduced cadmium levels in both shoots and brown rice without altering gene expression, protein abundance, or the subcellular localization of the transporter.

Importantly, the mutation did not come at the cost of micronutrients. Field trials on cadmium-contaminated soil showed a 48% decrease in cadmium concentration in brown rice, from 0.14 mg/kg in wild type to 0.07 mg/kg in the edited plants, while iron, manganese, and zinc levels remained essentially unchanged.

The researchers then explored the mechanism behind the selective effect. Although OsNramp5 transports multiple metals, the I441T mutation shifted its selectivity—enhancing zinc transport preference. Increased zinc accumulation in root cells promoted competitive inhibition against cadmium during root-to-shoot movement.

Instead of completely blocking cadmium uptake, the edited transporter selectively limited cadmium translocation, reducing grain contamination while preserving essential mineral delivery. The team supported these conclusions with physiological assessments, gene and protein analyses, yeast transport assays, and agronomic evaluation.

Overall, the work demonstrates how precision genome editing can address a long-standing breeding challenge: lowering toxic metal accumulation without disrupting nutrient homeostasis. The researchers propose that the OsNramp5^I441T allele could accelerate development of safer rice varieties for mildly contaminated regions.

Subject of Research: Not applicable
Article Title: Genome-edited rice variety with low-cadmium accumulation in the grain
News Publication Date: 18-Jun-2026
Web References: http://dx.doi.org/10.1073/pnas.2610609123
References: DOI: 10.1073/pnas.2610609123 (Proceedings of the National Academy of Sciences)
Image Credits: Credit: Professor Jian Feng Ma from Okayama University, Japan

Keywords: cadmium, rice, OsNramp5, base editing, genome editing, metal transporters, food safety, micronutrients, zinc competition, plant breeding

Nitrogen is an essential building block of proteins, amino acids, and DNA. Without nitrogen, cells can’t function or reproduce. Nitrogen is abundant in the atmosphere as dinitrogen gas, but plants and animals can’t access atmospheric nitrogen. Instead, we rely on biologically available forms like ammonia and nitrate. 

Specialized microbes can transform atmospheric nitrogen into ammonia via a process called biological nitrogen fixation. Nitrogen-fixing soil bacteria have a unique protein complex, the nitrogenase complex, that facilitates this nitrogen transformation. The nitrogenase complex is activated by a group of genes known as nif genes. 

Legume plants like peanuts, peas, and beans have nitrogen-fixing bacteria in the soil zone around their roots, called the rhizosphere. The symbiotic relationship between nitrogen-fixing soil bacteria and legume plants supplies most of the biologically available nitrogen to life on Earth.

However, one piece of the puzzle remains unexplored: the role of soil viruses in these nitrogen transformations, referred to as the nitrogen cycle. Viruses are microscopic particles made up of genetic material and proteins, but they can’t reproduce without a host cell. Scientists consider viruses to be biological entities that are halfway between living and non-living.

To reproduce, viruses contact a host cell and inject their genetic material into it. The virus’s genetic material takes over the host cell’s genome and forces the cell to produce proteins that assemble into new viruses. As new viruses are created, they can incorporate genes from the host cell into their own genetic material. Genes that are transferred from a host cell to a virus are known as auxiliary metabolic genes (AMGs). Viruses can carry AMGs and pass them to other hosts or use them to increase their own ecological fitness. 

Scientists from China, Spain, and the Czech Republic set out to investigate whether viruses from legume roots could increase local soil nitrogen fixation by expressing nif AMGs or by transferring nif genes to other bacteria. First, they determined the global distribution of viral nitrogen-fixing genes by analyzing about 8.6 million viral genomes from the Integrated Microbial Genomes/Virus database. They looked for the DNA sequences of known nitrogen-fixing genes and the locations where the viruses were sampled. They found that only 0.003% of the viruses in the database had at least 1 nitrogen-fixing gene, but they clustered in the same locations as nitrogen-fixing bacteria. 

The team also found 3 types of viruses that most commonly carried nitrogen-fixing genes: Kyanoviridae, Nudiviridae, and Bronfenbrennervirinae. Kyanoviridae viruses carried a nif gene called nifU. The researchers used a computer program called DRAM-v to confirm that nifU was a fully functional gene and a real tool that viruses could use. 

Next, the team collected soil samples from a cowpea field in Nanjing, China, to test whether the cowpea roots influenced the abundance of viruses using nitrogen-fixing genes. They collected soil from the cowpea rhizospheres and soil away from the plants. They analyzed both viral and bacterial RNA in the soil samples to identify active genes, using a sequencing process called metatranscriptomics. They found that the viral nifU gene was actively expressed in the cowpea rhizosphere samples more than in the non-crop soil. Although about 96% of nifU genes were being expressed by bacteria, viruses contributed about 4%. 

The researchers then assessed whether rhizospheric viruses changed the amount of nitrogen being fixed in these soils. They set up small, enclosed containers of sterile soil and added either bacteria or a mixture of bacteria and viruses extracted from the cowpea rhizospheres. They found that soil with viruses had higher total nitrogen (36 milligrams per kilogram, or mg/kg) than soil without viruses (17 mg/kg). 

Finally, they adjusted the air in each container to have a different form of dinitrogen gas. Atoms of the same element that have different atomic masses are known as isotopes. Nitrogen has 2 stable isotopes: lighter nitrogen-14 and heavier nitrogen-15. Bacteria or viruses that fix nitrogen at natural isotope abundances will take up nitrogen-14. But scientists can track who in the population fixes nitrogen by adding nitrogen-15 to the air, a process called nitrogen-15 stable isotope probing. Nitrogen-fixers will incorporate the heavy nitrogen-15 into their biomass over time and increase their weight, allowing researchers to separate and identify them.

The team grew the bacteria and viruses with nitrogen-15 for 35 days, then used stable isotope probing to separate the nitrogen fixers. They detected viral nifU AMGs among the heavier biomass, confirming that rhizospheric viruses were fixing nitrogen. 

The team concluded that rhizospheric viruses and the viral nifU AMG can increase nitrogen fixation in cowpea soils. The team suggested that although viruses with nitrogen-fixing genes are rare, they can influence the soil nitrogen cycle. They recommended that future researchers further test the contribution of viral nifU genes to plant nitrogen fixation with controlled infection experiments.

The post Viruses help plants obtain nitrogen appeared first on Sciworthy.

Europe has relaxed its gene-editing rules after years of debate but kept strict checks on herbicide-tolerant crops. India eased its rules too but dropped an early warning about the trait, even as illegal seeds spread across cotton-growing States.

A whole-genome analysis of Beefalo, a hybrid bison-cattle breed, suggests very few individuals have any bison DNA at all, a new study reports.

Corn sweat (noun, “KORN SWET”)

Corn sweat is moisture released by cornfields during summer heat, particularly in the central United States. The scientific term for corn sweat is evapotranspiration. This process combines evaporation and transpiration. Those are both ways that water moves from the land into the air during Earth’s water cycle.

Evaporation happens when liquid water turns into water vapor and rises into the air. In the case of corn sweat, water evaporates from the surface of the soil in farm fields.

Transpiration is the movement of water from a plant’s roots to its surfaces. There, water vapor escapes through tiny holes on the stems and leaves. These tiny holes are known as stomata. Releasing water vapor through transpiration is an essential function for plants.

The amount of water that plants add to the atmosphere varies. But in places with lots of cornfields, corn sweat can cause a spike in local humidity. The U.S. Department of Agriculture estimates that corn sweat releases about 13,000 to 19,000 liters (3,500 to 5,000 gallons) of water per acre per day. That’s about a quarter of the water held in most swimming pools.

Corn sweat is often blamed for muggy summer weather. But the water released by crops during heat waves is only an estimated 2 to 5 percent of the total humidity.

In a sentence

Humidity from crops is often attributed to corn sweat, but soybeans transpire too.

Check out the full list of Scientists Say.

Salty soil, one of the greatest threats to agriculture, may have a new remedy in the form of naturally occurring soil bacteria that allow plants to thrive under harsh conditions.

An international team led by Dr. Yanfen Zheng at the Chinese Academy of Agricultural Sciences presented their findings on increasing plant survivability in inhospitable environments in a recent paper published in Science Advances.

In their research, the international team demonstrated that maize, tomato, and rapeseed thrived in soil that would typically be unusable due to a previously unknown mechanism in these microbes, in a breakthrough for agriculture.

Salt and Agriculture

“The build-up of salt in farmland is a major and worsening problem – driven by climate change, irrigation and rising sea levels,” said co-author Prof Jonathan Todd, from the University of East Anglia’s School of Biological Sciences and the Quadram Institute on the Norwich Research Park. “Salt chokes plant growth, damages roots, and severely impacts entire harvests – putting global food supplies at risk.”

Agricultural scientists have long known that root microbiomes, the community of microbes living among a plant’s roots, are important for dealing with environmental stresses, yet they remained uncertain of the mechanics involved.

“We found that plants appear to recruit beneficial bacteria in salty soil conditions, which in turn trigger internal changes that strengthen their physical structure and resilience,” Todd continued. “If scientists can harness this natural process, it could mark the beginning of a new era in climate-resilient agriculture.”

Investigating Plant Root Microbiomes

The international team examined a variety of plant root microbiomes across different soil types and plant species, identifying pseudomonads, a type of naturally occurring soil bacterium, that are drawn to the roots of maize, tomato, and rapeseed in heavily salted environments. By noting the commonality of high salt content across a variety of crops, the researchers concluded that this was more than a mere coincidence and decided to analyze the genetic mechanisms behind the bacterium’s behavior.

“Compared to other microbes, pseudomonads carry specialised genes that help them tolerate high salt levels, including sodium transport systems and other stress resistance mechanisms,” Todd said.

Next, the researchers introduced various pseudomonad strains to soybean plants in laboratory and real-world soil experiments and observed that the bacteria colonized plant roots, resulting in increased growth in harsh, salty environments. Those soybean plants that received the bacteria demonstrated stronger root systems, more advanced development, and higher yields than those without.

“The most surprising thing was finding out how the bacteria helped plants cope,” Todd said. “For decades, it was thought that plants survive salinity by controlling sodium levels – essentially keeping harmful salt out. But we found no evidence that bacteria influenced sodium transport or ion balance.”

Lignin and Salt

“Instead of helping plants manage salt directly, the bacteria stimulated the plant to produce more of a substance called lignin,” Todd continued. “Roots of bacteria-treated plants showed a significant increase in lignin content, with some measurements rising by over 30 percent under salt stress.”

The tough, wood-like lignin acted as a shield against the salt, strengthening delicate tissues to endure a challenging environment. Unfortunately, in plants that couldn’t produce lignin, the pseudomonads produced no benefit. Building on the discovery, the researchers identified the genes in the plants involved in lignin synthesis and artificially overexpressed them to successfully confer salt resilience.

“We hope this discovery opens up new possibilities for agriculture,” Todd concluded. “With vast areas of farmland already affected by salinity and more under threat, microbial solutions could become an essential tool for maintaining crop yields and ensuring food security.”

The paper, “Pseudomonads Associated with Salt-Stressed Plants Facilitate Stress Adaptation of Soybean through Enhanced Lignin Biosynthesis,” appeared in Science Advances on June 24, 2026.

Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.

The United States is one of only a handful of countries that allows companies to hold patents on plant varieties. As a result, a small number of corporations can—and do—suppress competition in the seed industry, stifle innovation, and turn taxpayer subsidies intended for farmers into corporate profits.

The US Department of Agriculture has found that two companies control more than 70 percent of US corn and soybean seed sales, and the top four cottonseed companies control nearly 94 percent of that market.

In a May 2026 court filing in a legal dispute between two US seed companies, the Department of Justice said patents on seeds are obstructing competition and research in the agriculture industry.

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