“What I would love to have is a homeostatic, isometric, self-managing greenhouse that looks into my iris and my retina, takes a blood sample and looks at my breath, checks my toilet assay, and grows the stuff I need for me.”
So says David Gobel who, as co-founder of The Methuselah Foundation, hopes to increase the healthy human lifespan. He’s onto something, because in 2000 NASA asked him to create the very same thing―but for space colonies. Searching for a way to grow food that is ideally suited for consumption in space, the aerospace company partnered with the foundation to figure out how to do it.
If NASA hopes this will result in the ability to feed four astronauts living in outer space for three years, The Methuselah Foundation hopes that, as a byproduct of creating this garden of the future, we will also be able to biologically engineer food that will help human beings live longer, healthier lives.
And they might be right.
Smart gardens could grow medicine
Four years ago, Ritch Wood was looking for a better way to grow plants. As CEO for the global skincare company Nu Skin, he ran into ingredient shortages every winter when fields went dormant, and when he moved grow operations to the equator he ran into water and land shortages, along with a host of quality control issues.
Nu Skin needed reliable, quality ingredients for their skincare products, but farming was too unpredictable an industry. “If there was a way to grow indoors,” he thought, “and be able to do that 24 hours a day, 365 days a year―if we could guarantee that it was grown without any herbicides or pesticides and in a sustainable way that uses less water and land―that would be really helpful.”
At the time, controlled-environment agriculture (CEA) was in its infancy and grow-light technology had yet to take a turn for the affordable. When he learned of an agricultural system that promised to use a fraction of the land and water used by traditional agriculture methods and had the potential to make it more affordable, Wood made an investment.
Nu Skin paid $3 million for 70 percent of the company and rights to its IP―and Grōv Technologies was born.
The theory behind CEA is that, by controlling the environment in which a plant grows, we can control its full expression by micro-tweaking one of a thousand characteristics―including temperature, humidity, light duration, light wavelength, dissolved oxygen in the water, and carbon dioxide saturation in the air. By tweaking the growing cycle, we can control the caloric content as well as the nutrient content and density of the plant. Perhaps for the benefit of our health.
“What we’ve learned through controlled-environment agriculture,” Benjamin Swan, co-founder and CEO at Sustenir in Singapore, once told National Geographic, “[is] we can actually emphasize certain characteristics of the plants. So, without using GMO, we can make our kale softer, we can actually make it sweet.”
The theoretical use cases for this technology are endless―from being able to grow in places where water is scarce (like in much of Africa), or where water is overly abundant (like Hawaii), or in places where labor is scarce (like in parts of Asia), or even in places that have long winters (like Northern Europe). Theoretically, we could have grow towers in every town and feed the whole of it no matter its natural environment.
We could even grow those foods to those cities’ exact nutritional needs―more vitamin D-rich foods in wintery places, for example. Engineers and food scientists from Singapore’s Polytechnic want to take this one step further, aiming to predict and prevent illness in a given population by tracking their biometric data using Apple watch-like wearables, then 3D printing nutrient-specific foods that could mitigate imbalances.
Singapore leads much of the research and development in this area out of necessity. With limited land and water resources, the county is forced to import 90 percent of their food and 40 percent of their water from outside the country. As a result, they have no option but to grow vertically and desalinate water from the ocean.
By investing in Grōv Tech, Nu Skin hoped to do something similar, getting ahead of the supply chain that fuels their skincare products before the competition could beat them to it, or before climate change makes traditional methods more difficult, all while shoring up technology that could provide a farming model that is more sustainable. With this goal in mind, Wood decided to start by growing animal feed for Bateman’s Dairy farm in Utah. This would allow the company to scale the product while refining and automating the technology to the point that it could be replicated.
One year into feeding the 20,000 animals at Bateman, the company had learned a lot. For instance: cows need a lot of magnesium, but they don’t like eating it. Now, Grōv Tech puts magnesium in the water so it’s directly absorbed into the plant and then becomes bioavailable to the cow upon eating it. And because the growing process only takes seven days, data scientists can analyze the results in real-time and adjust the components to optimize production for the next batch of feed.
According to Grōv Tech president Steven Lindsley, it’s not far off that we’ll be looking at milk production (butter, fats, and proteins) and optimizing a herd’s diet for taste, quality, and nutritional value―not to mention the wellbeing of the animal. We’ll be able to look at how many trips from the veterinarian an animal gets when they’re fed certain nutrients in their diet, and whether they can have more calves and produce the same amount of dairy on less, better quality feed. (So far, the answer to this last question is yes, Lindsley tells me. When animals are fed better quality food they need less of it―just like humans.)
And if we hook all of the cows up to robotic milking equipment and connect everything to artificial intelligence, machine learning, and the Internet of Things―Lindsley’s far-flung goal―then we might be able to collect enough data to not only feed cows to their optimum health and performance ability, but humans too.
And that could have ramifications not just for feeding the world, but also nourishing it.
Biometric data could prevent disease
Diagnostic tools are on the rise. Our saliva can be tested for cancer and heart disease, our blood can be tested for food intolerances and vitamin deficiencies, our urine can be tested for heavy metals, our stools can be tested for microbiome and gut health, and many of us wear diagnostic tools on our wrists―Apple watches and FitBits track our steps, sleep, and heart rates, among other barometers.
I was fascinated when, during the pandemic, FitBit began exposing the data of its wearers. According to the fitness tracking device, when shutdowns first occurred the week of March 22nd, 2020, the US saw a 12 percent decline in the number of steps taken compared to the same week the year prior. Cities with the strictest shelter-in-place orders, such as San Francisco and New York, saw declines closer to 20 percent.
But then something interesting happened: In April, once we started working from home in earnest and shelter-in-place orders became less strict, we started getting more workouts per week than we did last year with walking, biking, and yoga surging in popularity. Forty-two percent of users increased their active minutes during that time with 31 percent maintaining their usual average.
And then, because we didn’t need to wake up as early to drive to work, we started sleeping longer and more consistently. Forty-five percent of Fitbit users increased their sleep duration in April and bedtimes normalized. We began going to bed earlier on weekends and later on weeknights, resulting in less “social jet lag,” a factor that can negatively impact heart health.
Thanks to this sudden increase in movement and sleep, Fitbit reported that the collective resting heart rate of their users had dropped by 1.26 beats per minute in users aged 18-29, a huge win for heart health!
Though the data is fascinating, right now it’s useless. I once wore an Apple watch for two years, tracked my every step and heartbeat and the amount of time I did yoga, and even gave my saliva to Ancestry hoping that, despite the long list of disclosures I was required to sign (may I never be cloned and sold for parts), I would learn something about my health.
I didn’t.
Though we have unfathomable diagnostic capabilities, they far surpass our curative abilities. “There are all sorts of diagnostic tests and there are lots of things being marketed to consumers directly, and some of those are things that are not linked to that type of action,” Wendy Kohlmann, the director of genetic counseling shared resource at the Huntsman Institute, once told me.
I can, for instance, discover (with limitations) whether there are differences in my BRCA1 and BRCA2 genes, and we do have an understanding that those differences can be linked to HBOC syndrome which increases the chances of hereditary breast and ovarian cancers, but it is still too soon to understand what can be done to reduce my risk of developing them apart from increasing regular screenings or removing body parts that are at risk.
“We can all benefit from maintaining a healthy weight, being physically active on a regular basis, and eating a balanced diet,” Kohlmann told me, “But the data is not to the point where, based on your genetic factors, we would have a different lifestyle recommendation. We wouldn’t be able to say, for instance, this person needs to eat more apples and that person needs to eat more broccoli… Maybe we’ll get there one day, but we’re not there yet.”
AI might be able to help. “The crux of diagnosis involves collecting data (symptoms, medical history, environmental factors) and predicting the phenomena correlated with them (an illness). This act of seeking out various correlations and making predictions is exactly what deep learning excels at,” says Kai-Fu Lee in his book AI Superpowers.
“This is what RXThinking is attempting to build. Founded by a Chinese AI researcher with deep experience in Silicon Valley and at Baidu, the startup is training medical AI algorithms to become super-diagnosticians that can be dispatched to all corners of China,” he says. “It draws on over 400 million existing medical records and continually scans the latest medical publications to make recommendations.”
This is far superior to the data available at a doctor’s fingertips. One day, AI might even be able to predict what diseases I am developing based on the items in my Amazon cart. After all, AI is already being used to determine how likely we are to pay back a loan, not by how much money we make, but by how much battery power is left on our phones.
“What does an applicant’s phone battery have to do with creditworthiness?” Lee asks in his book. “By training its algorithms on millions of loans—many that got paid back and some that didn’t—Smart Finance has discovered thousands of weak features that are correlated to creditworthiness, even if those correlations can’t be explained… In late 2017, the company was making more than 2 million loans per month with default rates in the low single digits, a track record that makes traditional brick-and-mortar banks extremely jealous.”
Smart gardens could replace doctors
Could we eventually make diagnoses the same way? Not by analyzing our symptoms (at which point it’s often too late), but by analyzing our collective data? Are the items in my Amazon cart similar to the items often purchased by people who eventually get pancreatic cancer? Do I live in a city that has high levels of estrogen in the water, and thus I am at a higher chance of developing breast cancer?
And could the same AI eventually make prescriptions, not in the form of pills, but in the form of things I should put in my Amazon carts instead (based on the things people who don’t develop the disease do) or ways I should treat my water to mitigate risk?
Could we see the cancerous trends toward which our bodies are trending and stop those malignant cells from ever developing? Better yet, could we each have our own personal garden that monitors our health based on our toilet assays, among other data, and grows food exactly to our specifications without us needing to engage with tech at all?
Well now we’re getting closer to Gobel’s dream.
Thank you for reading,
Elle
Related
The White House last month announced new guidelines requiring that all taxpayer-funded research, including data used for a study, be made public at no cost by the end of 2025, according to Vox.
I had no idea things like this existed. I’m hopeful that we will continue to trend in this direction if we normalize it and demand more transparency from the food industry. It’s going to take a lot of work but organizations like Methuselah Foundation will hopefully push the industry down a positive path. Great article, Elle. Very interesting read!