Researchers are looking to engineer chocolate with less oil, which could reduce some of its detriments to health.
Creamy milk with velvety texture. Dark with sprinkles of sea salt. Crunchy hazelnut-studded chunks. Chocolate is a treat that appeals to billions of people worldwide, no matter the age. And it’s not only the taste, but the feel of a chocolate morsel slowly melting in our mouths—the smoothness and slipperiness—that’s part of the overwhelming satisfaction. Why is it so enjoyable?
That’s what an interdisciplinary research team of chocolate lovers from the University of Leeds School of Food Science and Nutrition and School of Mechanical Engineering in the U.K. resolved to study in 2021. They wanted to know, “What is making chocolate that desirable?” says Siavash Soltanahmadi, one of the lead authors of a new study about chocolates hedonistic quality.
Besides addressing the researchers’ general curiosity, their answers might help chocolate manufacturers make the delicacy even more enjoyable and potentially healthier. After all, chocolate is a billion-dollar industry. Revenue from chocolate sales, whether milk or dark, is forecasted to grow 13 percent by 2027 in the U.K. In the U.S., chocolate and candy sales increased by 11 percent from 2020 to 2021, on track to reach $44.9 billion by 2026. Figuring out how chocolate affects the human palate could up the ante even more.
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.”
Artificial Intelligence is already helping to grow some of the food we eat.
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 from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
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.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
