Autonomous, indoor farming gives a boost to crops
The glass-encased cabinet looks like a display meant to hold reasonably priced watches, or drugstore beauty creams shipped from France. But instead of this stagnant merchandise, each of its five shelves is overgrown with leaves — moss-soft pea sprouts, spikes of Lolla rosa lettuces, pale bok choy, dark kale, purple basil or red-veined sorrel or green wisps of dill. The glass structure isn’t a cabinet, but rather a “micro farm.”
The gadget is on display at the Richmond, Virginia headquarters of Babylon Micro-Farms, a company that aims to make indoor farming in the U.S. more accessible and sustainable. Babylon’s soilless hydroponic growing system, which feeds plants via nutrient-enriched water, allows chefs on cruise ships, cafeterias and elsewhere to provide home-grown produce to patrons, just seconds after it’s harvested. Currently, there are over 200 functioning systems, either sold or leased to customers, and more of them are on the way.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
A newly discovered brain cell may lead to better treatments for cognitive disorders
Swiss researchers have discovered a third type of brain cell that appears to be a hybrid of the two other primary types — and it could lead to new treatments for many brain disorders.
The challenge: Most of the cells in the brain are either neurons or glial cells. While neurons use electrical and chemical signals to send messages to one another across small gaps called synapses, glial cells exist to support and protect neurons.
Astrocytes are a type of glial cell found near synapses. This close proximity to the place where brain signals are sent and received has led researchers to suspect that astrocytes might play an active role in the transmission of information inside the brain — a.k.a. “neurotransmission” — but no one has been able to prove the theory.
A new brain cell: Researchers at the Wyss Center for Bio and Neuroengineering and the University of Lausanne believe they’ve definitively proven that some astrocytes do actively participate in neurotransmission, making them a sort of hybrid of neurons and glial cells.
According to the researchers, this third type of brain cell, which they call a “glutamatergic astrocyte,” could offer a way to treat Alzheimer’s, Parkinson’s, and other disorders of the nervous system.
“Its discovery opens up immense research prospects,” said study co-director Andrea Volterra.
The study: Neurotransmission starts with a neuron releasing a chemical called a neurotransmitter, so the first thing the researchers did in their study was look at whether astrocytes can release the main neurotransmitter used by neurons: glutamate.
By analyzing astrocytes taken from the brains of mice, they discovered that certain astrocytes in the brain’s hippocampus did include the “molecular machinery” needed to excrete glutamate. They found evidence of the same machinery when they looked at datasets of human glial cells.
Finally, to demonstrate that these hybrid cells are actually playing a role in brain signaling, the researchers suppressed their ability to secrete glutamate in the brains of mice. This caused the rodents to experience memory problems.
“Our next studies will explore the potential protective role of this type of cell against memory impairment in Alzheimer’s disease, as well as its role in other regions and pathologies than those explored here,” said Andrea Volterra, University of Lausanne.
But why? The researchers aren’t sure why the brain needs glutamatergic astrocytes when it already has neurons, but Volterra suspects the hybrid brain cells may help with the distribution of signals — a single astrocyte can be in contact with thousands of synapses.
“Often, we have neuronal information that needs to spread to larger ensembles, and neurons are not very good for the coordination of this,” researcher Ludovic Telley told New Scientist.
Looking ahead: More research is needed to see how the new brain cell functions in people, but the discovery that it plays a role in memory in mice suggests it might be a worthwhile target for Alzheimer’s disease treatments.
The researchers also found evidence during their study that the cell might play a role in brain circuits linked to seizures and voluntary movements, meaning it’s also a new lead in the hunt for better epilepsy and Parkinson’s treatments.
“Our next studies will explore the potential protective role of this type of cell against memory impairment in Alzheimer’s disease, as well as its role in other regions and pathologies than those explored here,” said Volterra.
Researchers claimed they built a breakthrough superconductor. Social media shot it down almost instantly.
Harsh Mathur was a graduate physics student at Yale University in late 1989 when faculty announced they had failed to replicate claims made by scientists at the University of Utah and the University of Wolverhampton in England.
Such work is routine. Replicating or attempting to replicate the contraptions, calculations and conclusions crafted by colleagues is foundational to the scientific method. But in this instance, Yale’s findings were reported globally.
“I had a ringside view, and it was crazy,” recalls Mathur, now a professor of physics at Case Western Reserve University in Ohio.
Yale’s findings drew so much attention because initial experiments by Stanley Pons of Utah and Martin Fleischmann of Wolverhampton led to a startling claim: They were able to fuse atoms at room temperature – a scientific El Dorado known as “cold fusion.”
Nuclear fusion powers the stars in the universe. However, star cores must be at least 23.4 million degrees Fahrenheit and under extraordinary pressure to achieve fusion. Pons and Fleischmann claimed they had created an almost limitless source of power achievable at any temperature.
Like fusion, superconductivity can only be achieved in mostly impractical circumstances.
But about six months after they made their startling announcement, the pair’s findings were discredited by researchers at Yale and the California Institute of Technology. It was one of the first instances of a major scientific debunking covered by mass media.
Some scholars say the media attention for cold fusion stemmed partly from a dazzling announcement made three years prior in 1986: Scientists had created the first “superconductor” – material that could transmit electrical current with little or no resistance. It drew global headlines – and whetted the public’s appetite for announcements of scientific breakthroughs that could cause economic transformations.
But like fusion, superconductivity can only be achieved in mostly impractical circumstances: It must operate either at temperatures of at least negative 100 degrees Fahrenheit, or under pressures of around 150,000 pounds per square inch. Superconductivity that functions in closer to a normal environment would cut energy costs dramatically while also opening infinite possibilities for computing, space travel and other applications.
In July, a group of South Korean scientists posted material claiming they had created an iron crystalline substance called LK-99 that could achieve superconductivity at slightly above room temperature and at ambient pressure. The group partners with the Quantum Energy Research Centre, a privately-held enterprise in Seoul, and their claims drew global headlines.
Their work was also debunked. But in the age of internet and social media, the process was compressed from half-a-year into days. And it did not require researchers at world-class universities.
One of the most compelling critiques came from Derrick VanGennep. Although he works in finance, he holds a Ph.D. in physics and held a postdoctoral position at Harvard. The South Korean researchers had posted a video of a nugget of LK-99 in what they claimed was the throes of the Meissner effect – an expulsion of the substance’s magnetic field that would cause it to levitate above a magnet. Unless Hollywood magic is involved, only superconducting material can hover in this manner.
That claim made VanGennep skeptical, particularly since LK-99’s levitation appeared unenthusiastic at best. In fact, a corner of the material still adhered to the magnet near its center. He thought the video demonstrated ferromagnetism – two magnets repulsing one another. He mixed powdered graphite with super glue, stuck iron filings to its surface and mimicked the behavior of LK-99 in his own video, which was posted alongside the researchers’ video.
VanGennep believes the boldness of the South Korean claim was what led to him and others in the scientific community questioning it so quickly.
“The swift replication attempts stemmed from the combination of the extreme claim, the fact that the synthesis for this material is very straightforward and fast, and the amount of attention that this story was getting on social media,” he says.
But practicing scientists were suspicious of the data as well. Michael Norman, director of the Argonne Quantum Institute at the Argonne National Laboratory just outside of Chicago, had doubts immediately.
Will this saga hurt or even affect the careers of the South Korean researchers? Possibly not, if the previous fusion example is any indication.
“It wasn’t a very polished paper,” Norman says of the Korean scientists’ work. That opinion was reinforced, he adds, when it turned out the paper had been posted online by one of the researchers prior to seeking publication in a peer-reviewed journal. Although Norman and Mathur say that is routine with scientific research these days, Norman notes it was posted by one of the junior researchers over the doubts of two more senior scientists on the project.
Norman also raises doubts about the data reported. Among other issues, he observes that the samples created by the South Korean researchers contained traces of copper sulfide that could inadvertently amplify findings of conductivity.
The lack of the Meissner effect also caught Mathur’s attention. “Ferromagnets tend to be unstable when they levitate,” he says, adding that the video “just made me feel unconvinced. And it made me feel like they hadn't made a very good case for themselves.”
Will this saga hurt or even affect the careers of the South Korean researchers? Possibly not, if the previous fusion example is any indication. Despite being debunked, cold fusion claimants Pons and Fleischmann didn’t disappear. They moved their research to automaker Toyota’s IMRA laboratory in France, which along with the Japanese government spent tens of millions of dollars on their work before finally pulling the plug in 1998.
Fusion has since been created in laboratories, but being unable to reproduce the density of a star’s core would require excruciatingly high temperatures to achieve – about 160 million degrees Fahrenheit. A recently released Government Accountability Office report concludes practical fusion likely remains at least decades away.
However, like Pons and Fleischman, the South Korean researchers are not going anywhere. They claim that LK-99’s Meissner effect is being obscured by the fact the substance is both ferromagnetic and diamagnetic. They have filed for a patent in their country. But for now, those claims remain chimerical.
In the meantime, the consensus as to when a room temperature superconductor will be achieved is mixed. VenGennep – who studied the issue during his graduate and postgraduate work – puts the chance of creating such a superconductor by 2050 at perhaps 50-50. Mathur believes it could happen sooner, but adds that research on the topic has been going on for nearly a century, and that it has seen many plateaus.
“There's always this possibility that there's going to be something out there that we're going to discover unexpectedly,” Norman notes. The only certainty in this age of social media is that it will be put through the rigors of replication instantly.