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.”
Biohackers Made a Cheap and Effective Home Covid Test -- But No One Is Allowed to Use It
Last summer, when fast and cheap Covid tests were in high demand and governments were struggling to manufacture and distribute them, a group of independent scientists working together had a bit of a breakthrough.
Working on the Just One Giant Lab platform, an online community that serves as a kind of clearing house for open science researchers to find each other and work together, they managed to create a simple, one-hour Covid test that anyone could take at home with just a cup of hot water. The group tested it across a network of home and professional laboratories before being listed as a semi-finalist team for the XPrize, a competition that rewards innovative solutions-based projects. Then, the group hit a wall: they couldn't commercialize the test.
They wanted to keep their project open source, making it accessible to people around the world, so they decided to forgo traditional means of intellectual property protection and didn't seek patents. (They couldn't afford lawyers anyway). And, as a loose-knit group that was not supported by a traditional scientific institution, working in community labs and homes around the world, they had no access to resources or financial support for manufacturing or distributing their test at scale.
But without ethical and regulatory approval for clinical testing, manufacture, and distribution, they were legally unable to create field tests for real people, leaving their inexpensive, $16-per-test, innovative product languishing behind, while other, more expensive over-the-counter tests made their way onto the market.
Who Are These Radical Scientists?
Independent, decentralized biomedical research has come of age. Also sometimes called DIYbio, biohacking, or community biology, depending on whom you ask, open research is today a global movement with thousands of members, from scientists with advanced degrees to middle-grade students. Their motivations and interests vary across a wide spectrum, but transparency and accessibility are key to the ethos of the movement. Teams are agile, focused on shoestring-budget R&D, and aim to disrupt business as usual in the ivory towers of the scientific establishment.
Ethics oversight is critical to ensuring that research is conducted responsibly, even by biohackers.
Initiatives developed within the community, such as Open Insulin, which hopes to engineer processes for affordable, small-batch insulin production, "Slybera," a provocative attempt to reverse engineer a $1 million dollar gene therapy, and the hundreds of projects posted on the collaboration platform Just One Giant Lab during the pandemic, all have one thing in common: to pursue testing in humans, they need an ethics oversight mechanism.
These groups, most of which operate collaboratively in community labs, homes, and online, recognize that some sort of oversight or guidance is useful—and that it's the right thing to do.
But also, and perhaps more immediately, they need it because federal rules require ethics oversight of any biomedical research that's headed in the direction of the consumer market. In addition, some individuals engaged in this work do want to publish their research in traditional scientific journals, which—you guessed it—also require that research has undergone an ethics evaluation. Ethics oversight is critical to ensuring that research is conducted responsibly, even by biohackers.
Bridging the Ethics Gap
The problem is that traditional oversight mechanisms, such as institutional review boards at government or academic research institutions, as well as the private boards utilized by pharmaceutical companies, are not accessible to most independent researchers. Traditional review boards are either closed to the public, or charge fees that are out of reach for many citizen science initiatives. This has created an "ethics gap" in nontraditional scientific research.
Biohackers are seen in some ways as the direct descendents of "white hat" computer hackers, or those focused on calling out security holes and contributing solutions to technical problems within self-regulating communities. In the case of health and biotechnology, those problems include both the absence of treatments and the availability of only expensive treatments for certain conditions. As the DIYbio community grows, there needs to be a way to provide assurance that, when the work is successful, the public is able to benefit from it eventually. The team that developed the one-hour Covid test found a potential commercial partner and so might well overcome the oversight hurdle, but it's been 14 months since they developed the test--and counting.
In short, without some kind of oversight mechanism for the work of independent biomedical researchers, the solutions they innovate will never have the opportunity to reach consumers.
In a new paper in the journal Citizen Science: Theory & Practice, we consider the issue of the ethics gap and ask whether ethics oversight is something nontraditional researchers want, and if so, what forms it might take. Given that individuals within these communities sometimes vehemently disagree with each other, is consensus on these questions even possible?
We learned that there is no "one size fits all" solution for ethics oversight of nontraditional research. Rather, the appropriateness of any oversight model will depend on each initiative's objectives, needs, risks, and constraints.
We also learned that nontraditional researchers are generally willing (and in some cases eager) to engage with traditional scientific, legal, and bioethics experts on ethics, safety, and related questions.
We suggest that these experts make themselves available to help nontraditional researchers build infrastructure for ethics self-governance and identify when it might be necessary to seek outside assistance.
Independent biomedical research has promise, but like any emerging science, it poses novel ethical questions and challenges. Existing research ethics and oversight frameworks may not be well-suited to answer them in every context, so we need to think outside the box about what we can create for the future. That process should begin by talking to independent biomedical researchers about their activities, priorities, and concerns with an eye to understanding how best to support them.
Christi Guerrini, JD, MPH studies biomedical citizen science and is an Associate Professor at Baylor College of Medicine. Alex Pearlman, MA, is a science journalist and bioethicist who writes about emerging issues in biotechnology. They have recently launched outlawbio.org, a place for discussion about nontraditional research.
Sept. 13th Event: Delta, Vaccines, and Breakthrough Infections
This virtual event will convene leading scientific and medical experts to address the public's questions and concerns about COVID-19 vaccines, Delta, and breakthrough infections. Audience Q&A will follow the panel discussion. Your questions can be submitted in advance at the registration link.
DATE:
Monday, September 13th, 2021
12:30 p.m. - 1:45 p.m. EDT
REGISTER:
Dr. Amesh Adalja, M.D., FIDSA, Senior Scholar, Johns Hopkins Center for Health Security; Adjunct Assistant Professor, Johns Hopkins Bloomberg School of Public Health; Affiliate of the Johns Hopkins Center for Global Health. His work is focused on emerging infectious disease, pandemic preparedness, and biosecurity.
Dr. Nahid Bhadelia, M.D., MALD, Founding Director, Boston University Center for Emerging Infectious Diseases Policy and Research (CEID); Associate Director, National Emerging Infectious Diseases Laboratories (NEIDL), Boston University; Associate Professor, Section of Infectious Diseases, Boston University School of Medicine. She is an internationally recognized leader in highly communicable and emerging infectious diseases (EIDs) with clinical, field, academic, and policy experience in pandemic preparedness.
Dr. Akiko Iwasaki, Ph.D., Waldemar Von Zedtwitz Professor of Immunobiology and Molecular, Cellular and Developmental Biology and Professor of Epidemiology (Microbial Diseases), Yale School of Medicine; Investigator, Howard Hughes Medical Institute. Her laboratory researches how innate recognition of viral infections lead to the generation of adaptive immunity, and how adaptive immunity mediates protection against subsequent viral challenge.
Dr. Marion Pepper, Ph.D., Associate Professor, Department of Immunology, University of Washington. Her lab studies how cells of the adaptive immune system, called CD4+ T cells and B cells, form immunological memory by visualizing their differentiation, retention, and function.
This event is the third of a four-part series co-hosted by Leaps.org, the Aspen Institute Science & Society Program, and the Sabin–Aspen Vaccine Science & Policy Group, with generous support from the Gordon and Betty Moore Foundation and the Howard Hughes Medical Institute.
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.