Meat Shortages Are Here to Stay. Is Lab-Grown Food a Solution?
The coronavirus pandemic exposed significant weaknesses in the country's food supply chain. Grocery store meat counters were bare. Transportation interruptions influenced supply. Finding beef, poultry, and pork at the store has been, in some places, as challenging as finding toilet paper.
In traditional agriculture models, it takes at least three months to raise chicken, six to nine months for pigs, and 18 months for cattle.
It wasn't a lack of supply -- millions of animals were in the pipeline.
"There's certainly enough food out there, but it can't get anywhere because of the way our system is set up," said Amy Rowat, an associate professor of integrative biology and physiology at UCLA. "Having a more self-contained, self-sufficient way to produce meat could make the supply chain more robust."
Cultured meat could be one way of making the meat supply chain more resilient despite disruptions due to pandemics such as COVID-19. But is the country ready to embrace lab-grown food?
According to a Good Food Institute study, GenZ is almost twice as likely to embrace meat alternatives for reasons related to social and environmental awareness, even prior to the pandemic. That's because this group wants food choices that reflect their values around food justice, equity, and animal welfare.
Largely, the interest in protein alternatives has been plant-based foods. However, factors directly related to COVID-19 may accelerate consumer interest in the scaling up of cell-grown products, according to Liz Specht, the associate director of science and technology at The Good Food Institute. The latter is a nonprofit organization that supports scientists, investors, and entrepreneurs working to develop food alternatives to conventional animal products.
While lab-grown food isn't ready yet to definitively crisis-proof the food supply chain, experts say it offers promise.
Matching Supply and Demand
Companies developing cell-grown meat claim it can take as few as two months to develop a cell into an edible product, according to Anthony Chow, CFA at Agronomics Limited, an investment company focused on meat alternatives. Tissue is taken from an animal and placed in a culture that contains nutrients and proteins the cells need to grow and expand. He cites a Good Food Institute report that claims a 2.5-millimeter sample can grow three and a half tons of meat in 40 days, allowing for exponential growth when needed.
In traditional agriculture models, it takes at least three months to raise chicken, six to nine months for pigs, and 18 months for cattle. To keep enough maturing animals in the pipeline, farms must plan the number of animals to raise months -- even years -- in advance. Lab-grown meat advocates say that because cultured meat supplies can be flexible, it theoretically allows for scaling up or down in significantly less time.
"Supply and demand has drastically changed in some way around the world and cultivated meat processing would be able to adapt much quicker than conventional farming," Chow said.
Scaling Up
Lab-grown meat may provide an eventual solution, but not in the immediate future, said Paul Mozdziak, a professor of physiology at North Carolina State University who researches animal cell culture techniques, transgenic animal production, and muscle biology.
"The challenge is in culture media," he said. "It's going to take some innovation to get the cells to grow at quantities that are going to be similar to what you can get from an animal. These are questions that everybody in the space is working on."
Chow says some of the most advanced cultured meat companies, such as BlueNal, anticipate introducing products to the market midway through next year. However, he thinks COVID-19 has slowed the process. Once introduced, they will be at a premium price, most likely available at restaurants before they hit grocery store shelves.
"I think in five years' time it will be in a different place," he said. "I don't think that this will have relevance for this pandemic, but certainly beyond that."
"Plant-based meats may be perceived as 'alternatives' to meat, whereas lab-grown meat is producing the same meat, just in a much more efficient manner, without the environmental implications."
Of course, all the technological solutions in the world won't solve the problem unless people are open-minded about embracing them. At least for now, a lab-grown burger or bluefin tuna might still be too strange for many people, especially in the U.S.
For instance, a 2019 article published by "Frontiers in Sustainable Food Systems" reflects results from a study of 3,030 consumers showing that 29 percent of U.S. customers, 59 percent of Chinese consumers, and 56 percent of Indian consumers were either 'very' or 'extremely likely' to try cultivated meat.
"Lab-grown meat is genuine meat, at the cellular level, and therefore will match conventional meat with regard to its nutritional content and overall sensory experience. It could be argued that plant-based meat will never be able to achieve this," says Laura Turner, who works with Chow at Agronomics Limited. "Plant-based meats may be perceived as 'alternatives' to meat, whereas lab-grown meat is producing the same meat, just in a much more efficient manner, without the environmental implications."
A Solution Beyond This Pandemic
The coronavirus has done more than raise awareness of the fragility of food supply chains. It has also been a wakeup call for consumers and policy makers that it is time to radically rethink our meat, Specht says. Those factors have elevated the profile of lab-grown meat.
"I think the economy is getting a little bit more steam and if I was an investor, I would be getting excited about it," adds Mozdziak.
Beyond crises, Mozdziak explains that as affluence continues to increase globally, meat consumption increases exponentially. Yet farm animals can only grow so quickly and traditional farming won't be able to keep up.
"Even Tyson is saying that by 2050, there's not going to be enough capacity in the animal meat space to meet demand," he notes. "If we don't look at some innovative technologies, how are we going to overcome that?"
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.”
Scientists make progress with growing organs for transplants
Story by Big Think
For over a century, scientists have dreamed of growing human organs sans humans. This technology could put an end to the scarcity of organs for transplants. But that’s just the tip of the iceberg. The capability to grow fully functional organs would revolutionize research. For example, scientists could observe mysterious biological processes, such as how human cells and organs develop a disease and respond (or fail to respond) to medication without involving human subjects.
Recently, a team of researchers from the University of Cambridge has laid the foundations not just for growing functional organs but functional synthetic embryos capable of developing a beating heart, gut, and brain. Their report was published in Nature.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.