Artificial Intelligence is already helping to grow some of the food we eat.
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.”
Researchers are looking to engineer chocolate with less oil, which could reduce some of its detriments to health.
Building a 3D tongue
The team began by building a 3D tongue to analyze the physical process by which chocolate breaks down inside the mouth.
As part of the effort, reported earlier this year in the scientific journal ACS Applied Materials and Interfaces, the team studied a large variety of human tongues with the intention to build an “average” 3D model, says Soltanahmadi, a lubrication scientist. When it comes to edible substances, lubrication science looks at how food feels in the mouth and can help design foods that taste better and have more satisfying texture or health benefits.
There are variations in how people enjoy chocolate; some chew it while others “lick it” inside their mouths.
Tongue impressions from human participants studied using optical imaging helped the team build a tongue with key characteristics. “Our tongue is not a smooth muscle, it’s got some texture, it has got some roughness,” Soltanahmadi says. From those images, the team came up with a digital design of an average tongue and, using 3D printed molds, built a “mimic tongue.” They also added elastomers—such as silicone or polyurethane—to mimic the roughness, the texture and the mechanical properties of a real tongue. “Wettability" was another key component of the 3D tongue, Soltanahmadi says, referring to whether a surface mixes with water (hydrophilic) or, in the case of oil, resists it (hydrophobic).
Notably, the resulting artificial 3D-tongues looked nothing like the human version, but they were good mimics. The scientists also created “testing kits” that produced data on various physical parameters. One such parameter was viscosity, the measure of how gooey a food or liquid is — honey is more viscous compared to water, for example. Another was tribology, which defines how slippery something is — high fat yogurt is more slippery than low fat yogurt; milk can be more slippery than water. The researchers then mixed chocolate with artificial saliva and spread it on the 3D tongue to measure the tribology and the viscosity. From there they were able to study what happens inside the mouth when we eat chocolate.
The team focused on the stages of lubrication and the location of the fat in the chocolate, a process that has rarely been researched.
The artificial 3D-tongues look nothing like human tongues, but they function well enough to do the job.
Courtesy Anwesha Sarkar and University of Leeds
The oral processing of chocolate
We process food in our mouths in several stages, Soltanahmadi says. And there is variation in these stages depending on the type of food. So, the oral processing of a piece of meat would be different from, say, the processing of jelly or popcorn.
There are variations with chocolate, in particular; some people chew it while others use their tongues to explore it (within their mouths), Soltanahmadi explains. “Usually, from a consumer perspective, what we find is that if you have a luxury kind of a chocolate, then people tend to start with licking the chocolate rather than chewing it.” The researchers used a luxury brand of dark chocolate and focused on the process of licking rather than chewing.
As solid cocoa particles and fat are released, the emulsion envelops the tongue and coats the palette creating a smooth feeling of chocolate all over the mouth. That tactile sensation is part of the chocolate’s hedonistic appeal we crave.
Understanding the make-up of the chocolate was also an important step in the study. “Chocolate is a composite material. So, it has cocoa butter, which is oil, it has some particles in it, which is cocoa solid, and it has sugars," Soltanahmadi says. "Dark chocolate has less oil, for example, and less sugar in it, most of the time."
The researchers determined that the oral processing of chocolate begins as soon as it enters a person’s mouth; it starts melting upon exposure to one’s body temperature, even before the tongue starts moving, Soltanahmadi says. Then, lubrication begins. “[Saliva] mixes with the oily chocolate and it makes an emulsion." An emulsion is a fluid with a watery (or aqueous) phase and an oily phase. As chocolate breaks down in the mouth, that solid piece turns into a smooth emulsion with a fatty film. “The oil from the chocolate becomes droplets in a continuous aqueous phase,” says Soltanahmadi. In other words, as solid cocoa particles and fat are released, the emulsion envelops the tongue and coats the palette, creating a smooth feeling of chocolate all over the mouth. That tactile sensation is part of the chocolate’s hedonistic appeal we crave, says Soltanahmadi.
Finding the sweet spot
After determining how chocolate is orally processed, the research team wanted to find the exact sweet spot of the breakdown of solid cocoa particles and fat as they are released into the mouth. They determined that the epicurean pleasure comes only from the chocolate's outer layer of fat; the secondary fatty layers inside the chocolate don’t add to the sensation. It was this final discovery that helped the team determine that it might be possible to produce healthier chocolate that would contain less oil, says Soltanahmadi. And therefore, less fat.
Rongjia Tao, a physicist at Temple University in Philadelphia, thinks the Leeds study and the concept behind it is “very interesting.” Tao, himself, did a study in 2016 and found he could reduce fat in milk chocolate by 20 percent. He believes that the Leeds researchers’ discovery about the first layer of fat being more important for taste than the other layer can inform future chocolate manufacturing. “As a scientist I consider this significant and an important starting point,” he says.
Chocolate is rich in polyphenols, naturally occurring compounds also found in fruits and vegetables, such as grapes, apples and berries. Research found that plant polyphenols can protect against cancer, diabetes and osteoporosis as well as cardiovascular ad neurodegenerative diseases.
Not everyone thinks it’s a good idea, such as chef Michael Antonorsi, founder and owner of Chuao Chocolatier, one of the leading chocolate makers in the U.S. First, he says, “cacao fat is definitely a good fat.” Second, he’s not thrilled that science is trying to interfere with nature. “Every time we've tried to intervene and change nature, we get things out of balance,” says Antonorsi. “There’s a reason cacao is botanically known as food of the gods. The botanical name is the Theobroma cacao: Theobroma in ancient Greek, Theo is God and Brahma is food. So it's a food of the gods,” Antonorsi explains. He’s doubtful that a chocolate made only with a top layer of fat will produce the same epicurean satisfaction. “You're not going to achieve the same sensation because that surface fat is going to dissipate and there is no fat from behind coming to take over,” he says.
Without layers of fat, Antonorsi fears the deeply satisfying experiential part of savoring chocolate will be lost. The University of Leeds team, however, thinks that it may be possible to make chocolate healthier - when consumed in limited amounts - without sacrificing its taste. They believe the concept of less fatty but no less slick chocolate will resonate with at least some chocolate-makers and consumers, too.
Chocolate already contains some healthful compounds. Its cocoa particles have “loads of health benefits,” says Soltanahmadi. Dark chocolate usually has more cocoa than milk chocolate. Some experts recommend that dark chocolate should contain at least 70 percent cocoa in order for it to offer some health benefit. Research has shown that the cocoa in chocolate is rich in polyphenols, naturally occurring compounds also found in fruits and vegetables, such as grapes, apples and berries. Research has shown that consuming plant polyphenols can be protective against cancer, diabetes and osteoporosis as well as cardiovascular and neurodegenerative diseases.
“So keeping the healthy part of it and reducing the oily part of it, which is not healthy, but is giving you that indulgence of it … that was the final aim,” Soltanahmadi says. He adds that the team has been approached by individuals in the chocolate industry about their research. “Everyone wants to have a healthy chocolate, which at the same time tastes brilliant and gives you that self-indulging experience.”
Probiotic bacteria can be engineered to fight antibiotic-resistant superbugs by releasing chemicals that kill them.
In recent years, researchers have been exploring a promising avenue: the use of synthetic biology to engineer new bacteria that may work better than antibiotics. The need continues to grow, as a Lancet study linked antibiotic resistance to over 1.27 million deaths worldwide in 2019, surpassing HIV/AIDS and malaria. The western sub-Saharan Africa region had the highest death rate (27.3 people per 100,000).
Researchers warn that if nothing changes, by 2050, antibiotic resistance could kill 10 million people annually.
To make it worse, our remedy pipelines are drying up. Out of the 18 biggest pharmaceutical companies, 15 abandoned antibiotic development by 2013. According to the AMR Action Fund, venture capital has remained indifferent towards biotech start-ups developing new antibiotics. In 2019, at least two antibiotic start-ups filed for bankruptcy. As of December 2020, there were 43 new antibiotics in clinical development. But because they are based on previously known molecules, scientists say they are inadequate for treating multidrug-resistant bacteria. Researchers warn that if nothing changes, by 2050, antibiotic resistance could kill 10 million people annually.
The rise of synthetic biology
To circumvent this dire future, scientists have been working on alternative solutions using synthetic biology tools, meaning genetically modifying good bacteria to fight the bad ones.
From the time life evolved on earth around 3.8 billion years ago, bacteria have engaged in biological warfare. They constantly strategize new methods to combat each other by synthesizing toxic proteins that kill competition.
For example, Escherichia coli produces bacteriocins or toxins to kill other strains of E.coli that attempt to colonize the same habitat. Microbes like E.coli (which are not all pathogenic) are also naturally present in the human microbiome. The human microbiome harbors up to 100 trillion symbiotic microbial cells. The majority of them are beneficial organisms residing in the gut at different compositions.
The chemicals that these “good bacteria” produce do not pose any health risks to us, but can be toxic to other bacteria, particularly to human pathogens. For the last three decades, scientists have been manipulating bacteria’s biological warfare tactics to our collective advantage.
In the late 1990s, researchers drew inspiration from electrical and computing engineering principles that involve constructing digital circuits to control devices. In certain ways, every cell in living organisms works like a tiny computer. The cell receives messages in the form of biochemical molecules that cling on to its surface. Those messages get processed within the cells through a series of complex molecular interactions.
Synthetic biologists can harness these living cells’ information processing skills and use them to construct genetic circuits that perform specific instructions—for example, secrete a toxin that kills pathogenic bacteria. “Any synthetic genetic circuit is merely a piece of information that hangs around in the bacteria’s cytoplasm,” explains José Rubén Morones-Ramírez, a professor at the Autonomous University of Nuevo León, Mexico. Then the ribosome, which synthesizes proteins in the cell, processes that new information, making the compounds scientists want bacteria to make. “The genetic circuit remains separated from the living cell’s DNA,” Morones-Ramírez explains. When the engineered bacteria replicates, the genetic circuit doesn’t become part of its genome.
Highly intelligent by bacterial standards, some multidrug resistant V. cholerae strains can also “collaborate” with other intestinal bacterial species to gain advantage and take hold of the gut.
In 2000, Boston-based researchers constructed an E.coli with a genetic switch that toggled between turning genes on and off two. Later, they built some safety checks into their bacteria. “To prevent unintentional or deleterious consequences, in 2009, we built a safety switch in the engineered bacteria’s genetic circuit that gets triggered after it gets exposed to a pathogen," says James Collins, a professor of biological engineering at MIT and faculty member at Harvard University’s Wyss Institute. “After getting rid of the pathogen, the engineered bacteria is designed to switch off and leave the patient's body.”
Overuse and misuse of antibiotics causes resistant strains to evolve
Adobe Stock
Seek and destroy
As the field of synthetic biology developed, scientists began using engineered bacteria to tackle superbugs. They first focused on Vibrio cholerae, which in the 19th and 20th century caused cholera pandemics in India, China, the Middle East, Europe, and Americas. Like many other bacteria, V. cholerae communicate with each other via quorum sensing, a process in which the microorganisms release different signaling molecules, to convey messages to its brethren. Highly intelligent by bacterial standards, some multidrug resistant V. cholerae strains can also “collaborate” with other intestinal bacterial species to gain advantage and take hold of the gut. When untreated, cholera has a mortality rate of 25 to 50 percent and outbreaks frequently occur in developing countries, especially during floods and droughts.
Sometimes, however, V. cholerae makes mistakes. In 2008, researchers at Cornell University observed that when quorum sensing V. cholerae accidentally released high concentrations of a signaling molecule called CAI-1, it had a counterproductive effect—the pathogen couldn’t colonize the gut.
So the group, led by John March, professor of biological and environmental engineering, developed a novel strategy to combat V. cholerae. They genetically engineered E.coli to eavesdrop on V. cholerae communication networks and equipped it with the ability to release the CAI-1 molecules. That interfered with V. cholerae progress. Two years later, the Cornell team showed that V. cholerae-infected mice treated with engineered E.coli had a 92 percent survival rate.
These findings inspired researchers to sic the good bacteria present in foods like yogurt and kimchi onto the drug-resistant ones.
Three years later in 2011, Singapore-based scientists engineered E.coli to detect and destroy Pseudomonas aeruginosa, an often drug-resistant pathogen that causes pneumonia, urinary tract infections, and sepsis. Once the genetically engineered E.coli found its target through its quorum sensing molecules, it then released a peptide, that could eradicate 99 percent of P. aeruginosa cells in a test-tube experiment. The team outlined their work in a Molecular Systems Biology study.
“At the time, we knew that we were entering new, uncharted territory,” says lead author Matthew Chang, an associate professor and synthetic biologist at the National University of Singapore and lead author of the study. “To date, we are still in the process of trying to understand how long these microbes stay in our bodies and how they might continue to evolve.”
More teams followed the same path. In a 2013 study, MIT researchers also genetically engineered E.coli to detect P. aeruginosa via the pathogen’s quorum-sensing molecules. It then destroyed the pathogen by secreting a lab-made toxin.
Probiotics that fight
A year later in 2014, a Nature study found that the abundance of Ruminococcus obeum, a probiotic bacteria naturally occurring in the human microbiome, interrupts and reduces V.cholerae’s colonization— by detecting the pathogen’s quorum sensing molecules. The natural accumulation of R. obeum in Bangladeshi adults helped them recover from cholera despite living in an area with frequent outbreaks.
The findings from 2008 to 2014 inspired Collins and his team to delve into how good bacteria present in foods like yogurt and kimchi can attack drug-resistant bacteria. In 2018, Collins and his team developed the engineered probiotic strategy. They tweaked a bacteria commonly found in yogurt called Lactococcus lactis to treat cholera.
Engineered bacteria can be trained to target pathogens when they are at their most vulnerable metabolic stage in the human gut. --José Rubén Morones-Ramírez.
More scientists followed with more experiments. So far, researchers have engineered various probiotic organisms to fight pathogenic bacteria like Staphylococcus aureus (leading cause of skin, tissue, bone, joint and blood infections) and Clostridium perfringens (which causes watery diarrhea) in test-tube and animal experiments. In 2020, Russian scientists engineered a probiotic called Pichia pastoris to produce an enzyme called lysostaphin that eradicated S. aureus in vitro. Another 2020 study from China used an engineered probiotic bacteria Lactobacilli casei as a vaccine to prevent C. perfringens infection in rabbits.
In a study last year, Ramírez’s group at the Autonomous University of Nuevo León, engineered E. coli to detect quorum-sensing molecules from Methicillin-resistant Staphylococcus aureus or MRSA, a notorious superbug. The E. coli then releases a bacteriocin that kills MRSA. “An antibiotic is just a molecule that is not intelligent,” says Ramírez. “On the other hand, engineered bacteria can be trained to target pathogens when they are at their most vulnerable metabolic stage in the human gut.”
Collins and Timothy Lu, an associate professor of biological engineering at MIT, found that engineered E. coli can help treat other conditions—such as phenylketonuria, a rare metabolic disorder, that causes the build-up of an amino acid phenylalanine. Their start-up Synlogic aims to commercialize the technology, and has completed a phase 2 clinical trial.
Circumventing the challenges
The bacteria-engineering technique is not without pitfalls. One major challenge is that beneficial gut bacteria produce their own quorum-sensing molecules that can be similar to those that pathogens secrete. If an engineered bacteria’s biosensor is not specific enough, it will be ineffective.
Another concern is whether engineered bacteria might mutate after entering the gut. “As with any technology, there are risks where bad actors could have the capability to engineer a microbe to act quite nastily,” says Collins of MIT. But Collins and Ramírez both insist that the chances of the engineered bacteria mutating on its own are virtually non-existent. “It is extremely unlikely for the engineered bacteria to mutate,” Ramírez says. “Coaxing a living cell to do anything on command is immensely challenging. Usually, the greater risk is that the engineered bacteria entirely lose its functionality.”
However, the biggest challenge is bringing the curative bacteria to consumers. Pharmaceutical companies aren’t interested in antibiotics or their alternatives because it’s less profitable than developing new medicines for non-infectious diseases. Unlike the more chronic conditions like diabetes or cancer that require long-term medications, infectious diseases are usually treated much quicker. Running clinical trials are expensive and antibiotic-alternatives aren’t lucrative enough.
“Unfortunately, new medications for antibiotic resistant infections have been pushed to the bottom of the field,” says Lu of MIT. “It's not because the technology does not work. This is more of a market issue. Because clinical trials cost hundreds of millions of dollars, the only solution is that governments will need to fund them.” Lu stresses that societies must lobby to change how the modern healthcare industry works. “The whole world needs better treatments for antibiotic resistance.”