Sustainable Urban Farming Has a Rising Hot Star: Bugs
In Sydney, Australia, in the basement of an inner-city high-rise, lives a mass of unexpected inhabitants: millions of maggots. The insects are far from unwelcome. They are there to feast on the food waste generated by the building's human residents.
Goterra, the start-up that installed the maggots in the building in December, belongs to the rapidly expanding insect agriculture industry, which is experiencing a surge of investment worldwide.
The maggots – the larvae of the black soldier fly – are voracious, unfussy eaters. As adult flies, they don't eat, so the young fatten up swiftly on whatever they can get. Goterra's basement colony can munch through 5 metric tons of waste in a day.
"Maggots are nature's cleaners," says Bob Gordon, Head of Growth at Goterra. "They're a great tool to manage waste streams."
Their capacity to consume presents a neat response to the problem of food waste, which contributes up to 8% of global greenhouse gas emissions each year as it rots in landfill.
"The maggots eat the food fairly fresh," Gordon says. "So, there's minimal degradation and you don't get those methane emissions."
Alongside their ability to devour waste, the soldier fly larvae hold further agricultural promise: they yield an incredibly efficient protein. After the maggots have binged for about 12 days, Goterra harvests and processes them into a protein-rich livestock feed. Their excrement, known as frass, is also collected and turned into soil conditioner.
"We are producing protein in a basement," says Gordon. "It's urban farming – really sustainable, urban farming."
Goterra's module in the basement at Barangaroo, Sydney.
Supplied by Goterra
Goterra's founder Olympia Yarger started producing the insects in "buckets in her backyard" in 2016. Today, Goterra has a large-scale processing plant and has developed proprietary modules – in shipping containers – that use robotics to manage the larvae.
The modules have been installed on site at municipal buildings, hospitals, supermarkets, several McDonald's restaurants, and a range of smaller enterprises in Australia. Users pay a subscription fee and simply pour in the waste; Goterra visits once a fortnight to harvest the bugs.
Insect agriculture is well established outside of the West, and the practice is gaining traction around the world. China has mega-facilities that can process hundreds of tons of waste in a day. In Kenya, a program recently trained 2000 farmers in soldier fly farming to boost their economic security. French biotech company InnovaFeed, in partnership with US agricultural heavyweight ADM, plans to build "the world's largest insect protein facility" in Illinois this year.
"The [maggots] are science fiction on earth. Watching them work is awe-inspiring."
But the concept is still not to everyone's taste.
"This is still a topic that I say is a bit like black liquorice – people tend to either really like it or really don't," says Wendy Lu McGill, Communications Director at the North American Coalition of Insect Agriculture (NACIA).
Formed in 2016, NACIA now has over 100 members – including researchers and commercial producers of black soldier flies, meal worms and crickets.
McGill says there have been a few iterations of insect agriculture in the US – beginning with worms produced for bait after World War II then shifting to food for exotic pets. The current focus – "insects as food and feed" – took root about a decade ago, with the establishment of the first commercial farms for this purpose.
"We're starting to see more expansion in the U.S. and a lot of the larger investments have been for black soldier fly producers," McGill says. "They tend to have larger facilities and the animal feed market they're looking at is potentially quite large."
InnovaFeed's Illinois facility is set to produce 60,000 metric tons of animal feed protein per year.
"They'll be trying to employ many different circular principles," McGill says of the project. "For example, the heat from the feed factory – the excess heat that would normally just be vented – will be used to heat the other side that's raising the black soldier fly."
Although commercial applications have started to flourish recently, scientific knowledge of the black soldier fly's potential has existed for decades.
Dr. Jeffery Tomberlin, an entomologist at Texas A&M University, has been studying the insect for over 20 years, contributing to key technologies used in the industry. He also founded Evo, a black soldier fly company in Texas, which feeds its larvae the waste from a local bakery and distillery.
"They are science fiction on earth," he says of the maggots. "Watching them work is awe-inspiring."
Tomberlin says fly farms can work effectively at different scales, and present possibilities for non-Western countries to shift towards "commodity independence."
"You don't have to have millions of dollars invested to be successful in producing this insect," he says. "[A farm] can be as simple as an open barn along the equator to a 30,000 square-foot indoor facility in the Netherlands."
As the world's population balloons, food insecurity is an increasing concern. By 2050, the UN predicts that to feed our projected population we will need to ramp up food production by at least 60%. Insect agriculture, which uses very little land and water compared to traditional livestock farming, could play a key role.
Insects may become more common human food, but the current commercial focus is animal feed. Aquaculture is a key market, with insects presenting an alternative to fish meal derived from over-exploited stocks. Insect meal is also increasingly popular in pet food, particularly in Europe.
While recent investment has been strong – NACIA says 2020 was the best year yet – reaching a scale that can match existing agricultural industries and providing a competitive price point are still hurdles for insect agriculture.
But COVID-19 has strengthened the argument for new agricultural approaches, such as the decentralized, indoor systems and circular principles employed by insect farms.
"This has given the world a preview – which no one wanted – of [future] supply chain disruptions," says McGill.
As the industry works to meet demand, Tomberlin predicts diversification and product innovation: "I think food science is going to play a big part in that. They can take an insect and create ice cream." (Dried soldier fly larvae "taste kind of like popcorn," if you were wondering.)
Tomberlin says the insects could even become an interplanetary protein source: "I do believe in that. I mean, if we're going to colonize other planets, we need to be sustainable."
But he issues a word of caution about the industry growing too big, too fast: "I think we as an industry need to be very careful of how we harness and apply [our knowledge]. The black soldier fly is considered the crown jewel today, but if it's mismanaged, it can be relegated back to a past."
Goterra's Gordon also warns against rushing into mass production: "If you're just replacing big intensive animal agriculture with big intensive animal agriculture with more efficient animals, then what's the change you're really effecting?"
But he expects the industry will continue its rise though the next decade, and Goterra – fuelled by recent $8 million Series A funding – plans to expand internationally this year.
"Within 10 years' time, I would like to see the vast majority of our unavoidable food waste being used to produce maggots to go into a protein application," Gordon says.
"There's no lack of demand. And there's no lack of food waste."
Podcast: The Friday Five weekly roundup in health research
The Friday Five covers five stories in health research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Covered in this week's Friday Five:
- Sex differences in cancer
- Promising research on a vaccine for Lyme disease
- Using a super material for brain-like devices
- Measuring your immunity to Covid
- Reducing dementia risk with leisure activities
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.