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    MIT School of Science launches Center for Sustainability Science and Strategy

    The MIT School of Science is launching a center to advance knowledge and computational capabilities in the field of sustainability science, and support decision-makers in government, industry, and civil society to achieve sustainable development goals. Aligned with the Climate Project at MIT, researchers at the MIT Center for Sustainability Science and Strategy will develop and apply expertise from across the Institute to improve understanding of sustainability challenges, and thereby provide actionable knowledge and insight to inform strategies for improving human well-being for current and future generations.Noelle Selin, professor at MIT’s Institute for Data, Systems and Society and the Department of Earth, Atmospheric and Planetary Sciences, will serve as the center’s inaugural faculty director. C. Adam Schlosser and Sergey Paltsev, senior research scientists at MIT, will serve as deputy directors, with Anne Slinn as executive director.Incorporating and succeeding both the Center for Global Change Science and Joint Program on the Science and Policy of Global Change while adding new capabilities, the center aims to produce leading-edge research to help guide societal transitions toward a more sustainable future. Drawing on the long history of MIT’s efforts to address global change and its integrated environmental and human dimensions, the center is well-positioned to lead burgeoning global efforts to advance the field of sustainability science, which seeks to understand nature-society systems in their full complexity. This understanding is designed to be relevant and actionable for decision-makers in government, industry, and civil society in their efforts to develop viable pathways to improve quality of life for multiple stakeholders.“As critical challenges such as climate, health, energy, and food security increasingly affect people’s lives around the world, decision-makers need a better understanding of the earth in its full complexity — and that includes people, technologies, and institutions as well as environmental processes,” says Selin. “Better knowledge of these systems and how they interact can lead to more effective strategies that avoid unintended consequences and ensure an improved quality of life for all.”    Advancing knowledge, computational capability, and decision supportTo produce more precise and comprehensive knowledge of sustainability challenges and guide decision-makers to formulate more effective strategies, the center has set the following goals:Advance fundamental understanding of the complex interconnected physical and socio-economic systems that affect human well-being. As new policies and technologies are developed amid climate and other global changes, they interact with environmental processes and institutions in ways that can alter the earth’s critical life-support systems. Fundamental mechanisms that determine many of these systems’ behaviors, including those related to interacting climate, water, food, and socio-economic systems, remain largely unknown and poorly quantified. Better understanding can help society mitigate the risks of abrupt changes and “tipping points” in these systems.Develop, establish and disseminate new computational tools toward better understanding earth systems, including both environmental and human dimensions. The center’s work will integrate modeling and data analysis across disciplines in an era of increasing volumes of observational data. MIT multi-system models and data products will provide robust information to inform decision-making and shape the next generation of sustainability science and strategy.Produce actionable science that supports equity and justice within and across generations. The center’s research will be designed to inform action associated with measurable outcomes aligned with supporting human well-being across generations. This requires engaging a broad range of stakeholders, including not only nations and companies, but also nongovernmental organizations and communities that take action to promote sustainable development — with special attention to those who have historically borne the brunt of environmental injustice.“The center’s work will advance fundamental understanding in sustainability science, leverage leading-edge computing and data, and promote engagement and impact,” says Selin. “Our researchers will help lead scientists and strategists across the globe who share MIT’s commitment to mobilizing knowledge to inform action toward a more sustainable world.”Building a better world at MITBuilding on existing MIT capabilities in sustainability, science, and strategy, the center aims to: focus research, education, and outreach under a theme that reflects a comprehensive state of the field and international research directions, fostering a dynamic community of students, researchers, and faculty;raise the visibility of sustainability science at MIT, emphasizing links between science and action, in the context of existing Institute goals and other efforts on climate and sustainability, and in a way that reflects the vital contributions of a range of natural and social science disciplines to understanding human-environment systems; andre-emphasize MIT’s long-standing expertise in integrated systems modeling while leveraging the Institute’s concurrent leading-edge strengths in data and computing, establishing leadership that harnesses recent innovations, including those in machine learning and artificial intelligence, toward addressing the science challenges of global change and sustainability.“The Center for Sustainability Science and Strategy will provide the necessary synergy for our MIT researchers to develop, deploy, and scale up serious solutions to climate change and other critical sustainability challenges,” says Nergis Mavalvala, the Curtis and Kathleen Marble Professor of Astrophysics and dean of the MIT School of Science. “With Professor Selin at its helm, the center will also ensure that these solutions are created in concert with the people who are directly affected now and in the future.”The center builds on more than three decades of achievements by the Center for Global Change Science and the Joint Program on the Science and Policy of Global Change, both of which were directed or co-directed by professor of atmospheric science Ronald Prinn. 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    Advancing technology for aquaculture

    According to the National Oceanic and Atmospheric Administration, aquaculture in the United States represents a $1.5 billion industry annually. Like land-based farming, shellfish aquaculture requires healthy seed production in order to maintain a sustainable industry. Aquaculture hatchery production of shellfish larvae — seeds — requires close monitoring to track mortality rates and assess health from the earliest stages of life. 

    Careful observation is necessary to inform production scheduling, determine effects of naturally occurring harmful bacteria, and ensure sustainable seed production. This is an essential step for shellfish hatcheries but is currently a time-consuming manual process prone to human error. 

    With funding from MIT’s Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), MIT Sea Grant is working with Associate Professor Otto Cordero of the MIT Department of Civil and Environmental Engineering, Professor Taskin Padir and Research Scientist Mark Zolotas at the Northeastern University Institute for Experiential Robotics, and others at the Aquaculture Research Corporation (ARC), and the Cape Cod Commercial Fishermen’s Alliance, to advance technology for the aquaculture industry. Located on Cape Cod, ARC is a leading shellfish hatchery, farm, and wholesaler that plays a vital role in providing high-quality shellfish seed to local and regional growers.

    Two MIT students have joined the effort this semester, working with Robert Vincent, MIT Sea Grant’s assistant director of advisory services, through the Undergraduate Research Opportunities Program (UROP). 

    First-year student Unyime Usua and sophomore Santiago Borrego are using microscopy images of shellfish seed from ARC to train machine learning algorithms that will help automate the identification and counting process. The resulting user-friendly image recognition tool aims to aid aquaculturists in differentiating and counting healthy, unhealthy, and dead shellfish larvae, improving accuracy and reducing time and effort.

    Vincent explains that AI is a powerful tool for environmental science that enables researchers, industry, and resource managers to address challenges that have long been pinch points for accurate data collection, analysis, predictions, and streamlining processes. “Funding support from programs like J-WAFS enable us to tackle these problems head-on,” he says. 

    ARC faces challenges with manually quantifying larvae classes, an important step in their seed production process. “When larvae are in their growing stages they are constantly being sized and counted,” explains Cheryl James, ARC larval/juvenile production manager. “This process is critical to encourage optimal growth and strengthen the population.” 

    Developing an automated identification and counting system will help to improve this step in the production process with time and cost benefits. “This is not an easy task,” says Vincent, “but with the guidance of Dr. Zolotas at the Northeastern University Institute for Experiential Robotics and the work of the UROP students, we have made solid progress.” 

    The UROP program benefits both researchers and students. Involving MIT UROP students in developing these types of systems provides insights into AI applications that they might not have considered, providing opportunities to explore, learn, and apply themselves while contributing to solving real challenges.

    Borrego saw this project as an opportunity to apply what he’d learned in class 6.390 (Introduction to Machine Learning) to a real-world issue. “I was starting to form an idea of how computers can see images and extract information from them,” he says. “I wanted to keep exploring that.”

    Usua decided to pursue the project because of the direct industry impacts it could have. “I’m pretty interested in seeing how we can utilize machine learning to make people’s lives easier. We are using AI to help biologists make this counting and identification process easier.” While Usua wasn’t familiar with aquaculture before starting this project, she explains, “Just hearing about the hatcheries that Dr. Vincent was telling us about, it was unfortunate that not a lot of people know what’s going on and the problems that they’re facing.”

    On Cape Cod alone, aquaculture is an $18 million per year industry. But the Massachusetts Division of Marine Fisheries estimates that hatcheries are only able to meet 70–80 percent of seed demand annually, which impacts local growers and economies. Through this project, the partners aim to develop technology that will increase seed production, advance industry capabilities, and help understand and improve the hatchery microbiome.

    Borrego explains the initial challenge of having limited data to work with. “Starting out, we had to go through and label all of the data, but going through that process helped me learn a lot.” In true MIT fashion, he shares his takeaway from the project: “Try to get the best out of what you’re given with the data you have to work with. You’re going to have to adapt and change your strategies depending on what you have.”

    Usua describes her experience going through the research process, communicating in a team, and deciding what approaches to take. “Research is a difficult and long process, but there is a lot to gain from it because it teaches you to look for things on your own and find your own solutions to problems.”

    In addition to increasing seed production and reducing the human labor required in the hatchery process, the collaborators expect this project to contribute to cost savings and technology integration to support one of the most underserved industries in the United States. 

    Borrego and Usua both plan to continue their work for a second semester with MIT Sea Grant. Borrego is interested in learning more about how technology can be used to protect the environment and wildlife. Usua says she hopes to explore more projects related to aquaculture. “It seems like there’s an infinite amount of ways to tackle these issues.” More

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    Study finds lands used for grazing can worsen or help climate change

    When it comes to global climate change, livestock grazing can be either a blessing or a curse, according to a new study, which offers clues on how to tell the difference.

    If managed properly, the study shows, grazing can actually increase the amount of carbon from the air that gets stored in the ground and sequestered for the long run. But if there is too much grazing, soil erosion can result, and the net effect is to cause more carbon losses, so that the land becomes a net carbon source, instead of a carbon sink. And the study found that the latter is far more common around the world today.

    The new work, published today in the journal Nature Climate Change, provides ways to determine the tipping point between the two, for grazing lands in a given climate zone and soil type. It also provides an estimate of the total amount of carbon that has been lost over past decades due to livestock grazing, and how much could be removed from the atmosphere if grazing optimization management implemented. The study was carried out by Cesar Terrer, an assistant professor of civil and environmental engineering at MIT; Shuai Ren, a PhD student at the Chinese Academy of Sciences whose thesis is co-supervised by Terrer; and four others.

    “This has been a matter of debate in the scientific literature for a long time,” Terrer says. “In general experiments, grazing decreases soil carbon stocks, but surprisingly, sometimes grazing increases soil carbon stocks, which is why it’s been puzzling.”

    What happens, he explains, is that “grazing could stimulate vegetation growth through easing resource constraints such as light and nutrients, thereby increasing root carbon inputs to soils, where carbon can stay there for centuries or millennia.”

    But that only works up to a certain point, the team found after a careful analysis of 1,473 soil carbon observations from different grazing studies from many locations around the world. “When you cross a threshold in grazing intensity, or the amount of animals grazing there, that is when you start to see sort of a tipping point — a strong decrease in the amount of carbon in the soil,” Terrer explains.

    That loss is thought to be primarily from increased soil erosion on the denuded land. And with that erosion, Terrer says, “basically you lose a lot of the carbon that you have been locking in for centuries.”

    The various studies the team compiled, although they differed somewhat, essentially used similar methodology, which is to fence off a portion of land so that livestock can’t access it, and then after some time take soil samples from within the enclosure area, and from comparable nearby areas that have been grazed, and compare the content of carbon compounds.

    “Along with the data on soil carbon for the control and grazed plots,” he says, “we also collected a bunch of other information, such as the mean annual temperature of the site, mean annual precipitation, plant biomass, and properties of the soil, like pH and nitrogen content. And then, of course, we estimate the grazing intensity — aboveground biomass consumed, because that turns out to be the key parameter.”  

    With artificial intelligence models, the authors quantified the importance of each of these parameters, those drivers of intensity — temperature, precipitation, soil properties — in modulating the sign (positive or negative) and magnitude of the impact of grazing on soil carbon stocks. “Interestingly, we found soil carbon stocks increase and then decrease with grazing intensity, rather than the expected linear response,” says Ren.

    Having developed the model through AI methods and validated it, including by comparing its predictions with those based on underlying physical principles, they can then apply the model to estimating both past and future effects. “In this case,” Terrer says, “we use the model to quantify the historical loses in soil carbon stocks from grazing. And we found that 46 petagrams [billion metric tons] of soil carbon, down to a depth of one meter, have been lost in the last few decades due to grazing.”

    By way of comparison, the total amount of greenhouse gas emissions per year from all fossil fuels is about 10 petagrams, so the loss from grazing equals more than four years’ worth of all the world’s fossil emissions combined.

    What they found was “an overall decline in soil carbon stocks, but with a lot of variability.” Terrer says. The analysis showed that the interplay between grazing intensity and environmental conditions such as temperature could explain the variability, with higher grazing intensity and hotter climates resulting in greater carbon loss. “This means that policy-makers should take into account local abiotic and biotic factors to manage rangelands efficiently,” Ren notes. “By ignoring such complex interactions, we found that using IPCC [Intergovernmental Panel on Climate Change] guidelines would underestimate grazing-induced soil carbon loss by a factor of three globally.”

    Using an approach that incorporates local environmental conditions, the team produced global, high-resolution maps of optimal grazing intensity and the threshold of intensity at which carbon starts to decrease very rapidly. These maps are expected to serve as important benchmarks for evaluating existing grazing practices and provide guidance to local farmers on how to effectively manage their grazing lands.

    Then, using that map, the team estimated how much carbon could be captured if all grazing lands were limited to their optimum grazing intensity. Currently, the authors found, about 20 percent of all pasturelands have crossed the thresholds, leading to severe carbon losses. However, they found that under the optimal levels, global grazing lands would sequester 63 petagrams of carbon. “It is amazing,” Ren says. “This value is roughly equivalent to a 30-year carbon accumulation from global natural forest regrowth.”

    That would be no simple task, of course. To achieve optimal levels, the team found that approximately 75 percent of all grazing areas need to reduce grazing intensity. Overall, if the world seriously reduces the amount of grazing, “you have to reduce the amount of meat that’s available for people,” Terrer says.

    “Another option is to move cattle around,” he says, “from areas that are more severely affected by grazing intensity, to areas that are less affected. Those rotations have been suggested as an opportunity to avoid the more drastic declines in carbon stocks without necessarily reducing the availability of meat.”

    This study didn’t delve into these social and economic implications, Terrer says. “Our role is to just point out what would be the opportunity here. It shows that shifts in diets can be a powerful way to mitigate climate change.”

    “This is a rigorous and careful analysis that provides our best look to date at soil carbon changes due to livestock grazing practiced worldwide,” say Ben Bond-Lamberty, a terrestrial ecosystem research scientist at Pacific Northwest National Laboratory, who was not associated with this work. “The authors’ analysis gives us a unique estimate of soil carbon losses due to grazing and, intriguingly, where and how the process might be reversed.”

    He adds: “One intriguing aspect to this work is the discrepancies between its results and the guidelines currently used by the IPCC — guidelines that affect countries’ commitments, carbon-market pricing, and policies.” However, he says, “As the authors note, the amount of carbon historically grazed soils might be able to take up is small relative to ongoing human emissions. But every little bit helps!”

    “Improved management of working lands can be a powerful tool to combat climate change,” says Jonathan Sanderman, carbon program director of the Woodwell Climate Research Center in Falmouth, Massachusetts, who was not associated with this work. He adds, “This work demonstrates that while, historically, grazing has been a large contributor to climate change, there is significant potential to decrease the climate impact of livestock by optimizing grazing intensity to rebuild lost soil carbon.”

    Terrer states that for now, “we have started a new study, to evaluate the consequences of shifts in diets for carbon stocks. I think that’s the million-dollar question: How much carbon could you sequester, compared to business as usual, if diets shift to more vegan or vegetarian?” The answers will not be simple, because a shift to more vegetable-based diets would require more cropland, which can also have different environmental impacts. Pastures take more land than crops, but produce different kinds of emissions. “What’s the overall impact for climate change? That is the question we’re interested in,” he says.

    The research team included Juan Li, Yingfao Cao, Sheshan Yang, and Dan Liu, all with the  Chinese Academy of Sciences. The work was supported by the Second Tibetan Plateau Scientific Expedition and Research Program, and the Science and Technology Major Project of Tibetan Autonomous Region of China. More

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    Letting the Earth answer back: Designing better planetary conversations

    For Chen Chu MArch ’21, the invitation to join the 2023-24 cohort of Morningside Academy for Design Design Fellows has been an unparalleled opportunity to investigate the potential of design as an alternative method of problem-solving.

    After earning a master’s degree in architecture at MIT and gaining professional experience as a researcher at an environmental nongovernmental organization, Chu decided to pursue a PhD in the Department of Urban Studies and Planning. “I discovered that I needed to engage in a deeper way with the most difficult ethical challenges of our time, especially those arising from the fact of climate change,” he explains. “For me, MIT has always represented this wonderful place where people are inherently intellectually curious — it’s a very rewarding community to be part of.”

    Chu’s PhD research, guided by his doctoral advisor Delia Wendel, assistant professor of urban studies and international development, focuses on how traditional practices of floodplain agriculture can inform local and global strategies for sustainable food production and distribution in response to climate change. 

    Typically located alongside a river or stream, floodplains arise from seasonal flooding patterns that distribute nutrient-rich silt and create connectivity between species. This results in exceptionally high levels of biodiversity and microbial richness, generating the ideal conditions for agriculture. It’s no accident that the first human civilizations were founded on floodplains, including Mesopotamia (named for its location poised between two rivers, the Euphrates and Tigris), the Indus River Civilization, and the cultures of Ancient Egypt based around the Nile. Riverine transportation networks and predictable flooding rhythms provide a framework for trade and cultivation; nonetheless, floodplain communities must learn to live with risk, subject to the sudden disruptions of high waters, drought, and ecological disequilibrium. 

    For Chu, the “unstable and ungovernable” status of floodplains makes them fertile ground for thinking about. “I’m drawn to these so-called ‘wet landscapes’ — edge conditions that act as transitional spaces between land and water, between humans and nature, between city and river,” he reflects. “The development of extensively irrigated agricultural sites is typically a collective effort, which raises intriguing questions about how communities establish social organizations that simultaneously negotiate top-down state control and adapt to the uncertainty of nature.”

    Chu is in the process of honing the focus of his dissertation and refining his data collection methods, which will include archival research and fieldwork, as well as interviews with floodplain inhabitants to gain an understanding of sociopolitical nuances. Meanwhile, his role as a design fellow gives him the space to address the big questions that fire his imagination. How can we live well on shared land? How can we take responsibility for the lives of future generations? What types of political structures are required to get everyone on board? 

    These are just a few of the questions that Chu recently put to his cohort in a presentation. During the weekly seminars for the fellowship, he has the chance to converse with peers and mentors of multiple disciplines — from researchers rethinking the pedagogy of design to entrepreneurs applying design thinking to new business models to architects and engineers developing new habitats to heal our relationship with the natural world. 

    “I’ll admit — I’m wary of the human instinct to problem-solve,” says Chu. “When it comes to the material conditions and lived experience of people and planet, there’s a limit to our economic and political reasoning, and to conventional architectural practice. That said, I do believe that the mindset of a designer can open up new ways of thinking. At its core, design is an interdisciplinary practice based on the understanding that a problem can’t be solved from a narrow, singular perspective.” 

    The stimulating structure of a MAD Fellowship — free from immediate obligations to publish or produce, fellows learn from one another and engage with visiting speakers via regular seminars and events — has prompted Chu to consider what truly makes for generative conversation in the contexts of academia and the private and public sectors. In his opinion, discussions around climate change often fail to take account of one important voice; an absence he describes as “that silent being, the Earth.”

    “You can’t ask the Earth, ‘What does justice mean to you?’ Nature will not respond,” he reflects. To bridge the gap, Chu believes it’s important to combine the study of specific political and social conditions with broader existential questions raised by the environmental humanities. His own research draws upon the perspectives of thinkers including Dipesh Chakrabarty, Donna Haraway, Peter Singer,  Anna Tsing, and Michael Watts, among others. He cites James C. Scott’s lecture “In Praise of Floods” as one of his most important influences.

    In addition to his instinctive appreciation for theory, Chu’s outlook is grounded by an attention to innovation at the local level. He is currently establishing the parameters of his research, examining case studies of agricultural systems and flood mitigation strategies that have been sustained for centuries. 

    “One example is the polder system that is practiced in the Netherlands, China, Bangladesh, and many parts of the world: small, low-lying tracts of land submerged in water and surrounded by dykes and canals,” he explains. “You’ll find a different but comparable strategy in the colder regions of Japan. Crops are protected from the winter winds by constructing a spatial unit with the house at the center; trees behind the house serve as windbreakers and paddy fields for rice are located in front of the house, providing an integrated system of food and livelihood security.”

    Chu observes that there is a tendency for international policymakers to overlook local solutions in favor of grander visions and ambitious climate pledges — but he is equally keen not to romanticize vernacular practices. “Realistically, it’s always a two-way interaction. Unless you already have a workable local system in place, it’s difficult to implement a solution without top-down support. On the other hand, the large-scale technocratic dreams are empty if ignorant of local traditions and histories.” 

    By navigating between the global and the local, the theoretical and the practical, the visionary and the cautionary, Chu has hope in the possibility of gradually finding a way toward long-term solutions that adapt to specific conditions over time. It’s a model of ambition and criticality that Chu sees played out during dialogue at MAD and within his department; at root, he’s aware that the outcome of these conversations depends on the ethical context that shapes them.

    “I’ve been fortunate to have many mentors who have taught me the power of humility; a respect for the finitude, fragility,  and uncertainty of life,” he recalls. “It’s a mindset that’s barely apparent in today’s push for economic growth.” The flip-side of hubristic growth is an assumption that technological ingenuity will be enough to solve the climate crisis, but Chu’s optimism arises from a different source: “When I feel overwhelmed by the weight of the problems we’re facing, I just need to look around me,” he says. “Here on campus — at MAD, in my home department, and increasingly among the new generations of students — there’s a powerful ethos of political sensitivity, ethical compassion, and an attention to clear and critical judgment. That always gives me hope for the planet.” More

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    Reducing pesticide use while increasing effectiveness

    Farming can be a low-margin, high-risk business, subject to weather and climate patterns, insect population cycles, and other unpredictable factors. Farmers need to be savvy managers of the many resources they deal, and chemical fertilizers and pesticides are among their major recurring expenses.

    Despite the importance of these chemicals, a lack of technology that monitors and optimizes sprays has forced farmers to rely on personal experience and rules of thumb to decide how to apply these chemicals. As a result, these chemicals tend to be over-sprayed, leading to their runoff into waterways and buildup up in the soil.

    That could change, thanks to a new approach of feedback-optimized spraying, invented by AgZen, an MIT spinout founded in 2020 by Professor Kripa Varanasi and Vishnu Jayaprakash SM ’19, PhD ’22.

    Play video

    AgZen has developed a system for farming that can monitor exactly how much of the sprayed chemicals adheres to plants, in real time, as the sprayer drives through a field. Built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray.

    Over the past decade, AgZen’s founders have developed products and technologies to control the interactions of droplets and sprays with plant surfaces. The Boston-based venture-backed company launched a new commercial product in 2024 and is currently piloting another related product. Field tests of both have shown the products can help farmers spray more efficiently and effectively, using fewer chemicals overall.

    “Worldwide, farms spend approximately $60 billion a year on pesticides. Our objective is to reduce the number of pesticides sprayed and lighten the financial burden on farms without sacrificing effective pest management,” Varanasi says.

    Getting droplets to stick

    While the world pesticide market is growing rapidly, a lot of the pesticides sprayed don’t reach their target. A significant portion bounces off the plant surfaces, lands on the ground, and becomes part of the runoff that flows to streams and rivers, often causing serious pollution. Some of these pesticides can be carried away by wind over very long distances.

    “Drift, runoff, and poor application efficiency are well-known, longstanding problems in agriculture, but we can fix this by controlling and monitoring how sprayed droplets interact with leaves,” Varanasi says.

    With support from MIT Tata Center and the Abdul Latif Jameel Water and Food Systems Lab, Varanasi and his team analyzed how droplets strike plant surfaces, and explored ways to increase application efficiency. This research led them to develop a novel system of nozzles that cloak droplets with compounds that enhance the retention of droplets on the leaves, a product they call EnhanceCoverage.

    Field studies across regions — from Massachusetts to California to Italy and France —showed that this droplet-optimization system could allow farmers to cut the amount of chemicals needed by more than half because more of the sprayed substances would stick to the leaves.

    Measuring coverage

    However, in trying to bring this technology to market, the researchers faced a sticky problem: Nobody knew how well pesticide sprays were adhering to the plants in the first place, so how could AgZen say that the coverage was better with its new EnhanceCoverage system?

    “I had grown up spraying with a backpack on a small farm in India, so I knew this was an issue,” Jayaprakash says. “When we spoke to growers, they told me how complicated spraying is when you’re on a large machine. Whenever you spray, there are so many things that can influence how effective your spray is. How fast do you drive the sprayer? What flow rate are you using for the chemicals? What chemical are you using? What’s the age of the plants, what’s the nozzle you’re using, what is the weather at the time? All these things influence agrochemical efficiency.”

    Agricultural spraying essentially comes down to dissolving a chemical in water and then spraying droplets onto the plants. “But the interaction between a droplet and the leaf is complex,” Varanasi says. “We were coming in with ways to optimize that, but what the growers told us is, hey, we’ve never even really looked at that in the first place.”

    Although farmers have been spraying agricultural chemicals on a large scale for about 80 years, they’ve “been forced to rely on general rules of thumb and pick all these interlinked parameters, based on what’s worked for them in the past. You pick a set of these parameters, you go spray, and you’re basically praying for outcomes in terms of how effective your pest control is,” Varanasi says.

    Before AgZen could sell farmers on the new system to improve droplet coverage, the company had to invent a way to measure precisely how much spray was adhering to plants in real-time.

    Comparing before and after

    The system they came up with, which they tested extensively on farms across the country last year, involves a unit that can be bolted onto the spraying arm of virtually any sprayer. It carries two sensor stacks, one just ahead of the sprayer nozzles and one behind. Then, built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray. It also computes how much those droplets will spread out or evaporate, leading to a precise estimate of the final coverage.

    “There’s a lot of physics that governs how droplets spread and evaporate, and this has been incorporated into software that a farmer can use,” Varanasi says. “We bring a lot of our expertise into understanding droplets on leaves. All these factors, like how temperature and humidity influence coverage, have always been nebulous in the spraying world. But now you have something that can be exact in determining how well your sprays are doing.”

    “We’re not only measuring coverage, but then we recommend how to act,” says Jayaprakash, who is AgZen’s CEO. “With the information we collect in real-time and by using AI, RealCoverage tells operators how to optimize everything on their sprayer, from which nozzle to use, to how fast to drive, to how many gallons of spray is best for a particular chemical mix on a particular acre of a crop.”

    The tool was developed to prove how much AgZen’s EnhanceCoverage nozzle system (which will be launched in 2025) improves coverage. But it turns out that monitoring and optimizing droplet coverage on leaves in real-time with this system can itself yield major improvements.

    “We worked with large commercial farms last year in specialty and row crops,” Jayaprakash says. “When we saved our pilot customers up to 50 percent of their chemical cost at a large scale, they were very surprised.” He says the tool has reduced chemical costs and volume in fallow field burndowns, weed control in soybeans, defoliation in cotton, and fungicide and insecticide sprays in vegetables and fruits. Along with data from commercial farms, field trials conducted by three leading agricultural universities have also validated these results.

    “Across the board, we were able to save between 30 and 50 percent on chemical costs and increase crop yields by enabling better pest control,” Jayaprakash says. “By focusing on the droplet-leaf interface, our product can help any foliage spray throughout the year, whereas most technological advancements in this space recently have been focused on reducing herbicide use alone.” The company now intends to lease the system across thousands of acres this year.

    And these efficiency gains can lead to significant returns at scale, he emphasizes: In the U.S., farmers currently spend $16 billion a year on chemicals, to protect about $200 billion of crop yields.

    The company launched its first product, the coverage optimization system called RealCoverage, this year, reaching a wide variety of farms with different crops and in different climates. “We’re going from proof-of-concept with pilots in large farms to a truly massive scale on a commercial basis with our lease-to-own program,” Jayaprakash says.

    “We’ve also been tapped by the USDA to help them evaluate practices to minimize pesticides in watersheds,” Varanasi says, noting that RealCoverage can also be useful for regulators, chemical companies, and agricultural equipment manufacturers.

    Once AgZen has proven the effectiveness of using coverage as a decision metric, and after the RealCoverage optimization system is widely in practice, the company will next roll out its second product, EnhanceCoverage, designed to maximize droplet adhesion. Because that system will require replacing all the nozzles on a sprayer, the researchers are doing pilots this year but will wait for a full rollout in 2025, after farmers have gained experience and confidence with their initial product.

    “There is so much wastage,” Varanasi says. “Yet farmers must spray to protect crops, and there is a lot of environmental impact from this. So, after all this work over the years, learning about how droplets stick to surfaces and so on, now the culmination of it in all these products for me is amazing, to see all this come alive, to see that we’ll finally be able to solve the problem we set out to solve and help farmers.” More

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    MIT researchers remotely map crops, field by field

    Crop maps help scientists and policymakers track global food supplies and estimate how they might shift with climate change and growing populations. But getting accurate maps of the types of crops that are grown from farm to farm often requires on-the-ground surveys that only a handful of countries have the resources to maintain.

    Now, MIT engineers have developed a method to quickly and accurately label and map crop types without requiring in-person assessments of every single farm. The team’s method uses a combination of Google Street View images, machine learning, and satellite data to automatically determine the crops grown throughout a region, from one fraction of an acre to the next. 

    The researchers used the technique to automatically generate the first nationwide crop map of Thailand — a smallholder country where small, independent farms make up the predominant form of agriculture. The team created a border-to-border map of Thailand’s four major crops — rice, cassava, sugarcane, and maize — and determined which of the four types was grown, at every 10 meters, and without gaps, across the entire country. The resulting map achieved an accuracy of 93 percent, which the researchers say is comparable to on-the-ground mapping efforts in high-income, big-farm countries.

    The team is applying their mapping technique to other countries such as India, where small farms sustain most of the population but the type of crops grown from farm to farm has historically been poorly recorded.

    “It’s a longstanding gap in knowledge about what is grown around the world,” says Sherrie Wang, the d’Arbeloff Career Development Assistant Professor in MIT’s Department of Mechanical Engineering, and the Institute for Data, Systems, and Society (IDSS). “The final goal is to understand agricultural outcomes like yield, and how to farm more sustainably. One of the key preliminary steps is to map what is even being grown — the more granularly you can map, the more questions you can answer.”

    Wang, along with MIT graduate student Jordi Laguarta Soler and Thomas Friedel of the agtech company PEAT GmbH, will present a paper detailing their mapping method later this month at the AAAI Conference on Artificial Intelligence.

    Ground truth

    Smallholder farms are often run by a single family or farmer, who subsist on the crops and livestock that they raise. It’s estimated that smallholder farms support two-thirds of the world’s rural population and produce 80 percent of the world’s food. Keeping tabs on what is grown and where is essential to tracking and forecasting food supplies around the world. But the majority of these small farms are in low to middle-income countries, where few resources are devoted to keeping track of individual farms’ crop types and yields.

    Crop mapping efforts are mainly carried out in high-income regions such as the United States and Europe, where government agricultural agencies oversee crop surveys and send assessors to farms to label crops from field to field. These “ground truth” labels are then fed into machine-learning models that make connections between the ground labels of actual crops and satellite signals of the same fields. They then label and map wider swaths of farmland that assessors don’t cover but that satellites automatically do.

    “What’s lacking in low- and middle-income countries is this ground label that we can associate with satellite signals,” Laguarta Soler says. “Getting these ground truths to train a model in the first place has been limited in most of the world.”

    The team realized that, while many developing countries do not have the resources to maintain crop surveys, they could potentially use another source of ground data: roadside imagery, captured by services such as Google Street View and Mapillary, which send cars throughout a region to take continuous 360-degree images with dashcams and rooftop cameras.

    In recent years, such services have been able to access low- and middle-income countries. While the goal of these services is not specifically to capture images of crops, the MIT team saw that they could search the roadside images to identify crops.

    Cropped image

    In their new study, the researchers worked with Google Street View (GSV) images taken throughout Thailand — a country that the service has recently imaged fairly thoroughly, and which consists predominantly of smallholder farms.

    Starting with over 200,000 GSV images randomly sampled across Thailand, the team filtered out images that depicted buildings, trees, and general vegetation. About 81,000 images were crop-related. They set aside 2,000 of these, which they sent to an agronomist, who determined and labeled each crop type by eye. They then trained a convolutional neural network to automatically generate crop labels for the other 79,000 images, using various training methods, including iNaturalist — a web-based crowdsourced  biodiversity database, and GPT-4V, a “multimodal large language model” that enables a user to input an image and ask the model to identify what the image is depicting. For each of the 81,000 images, the model generated a label of one of four crops that the image was likely depicting — rice, maize, sugarcane, or cassava.

    The researchers then paired each labeled image with the corresponding satellite data taken of the same location throughout a single growing season. These satellite data include measurements across multiple wavelengths, such as a location’s greenness and its reflectivity (which can be a sign of water). 

    “Each type of crop has a certain signature across these different bands, which changes throughout a growing season,” Laguarta Soler notes.

    The team trained a second model to make associations between a location’s satellite data and its corresponding crop label. They then used this model to process satellite data taken of the rest of the country, where crop labels were not generated or available. From the associations that the model learned, it then assigned crop labels across Thailand, generating a country-wide map of crop types, at a resolution of 10 square meters.

    This first-of-its-kind crop map included locations corresponding to the 2,000 GSV images that the researchers originally set aside, that were labeled by arborists. These human-labeled images were used to validate the map’s labels, and when the team looked to see whether the map’s labels matched the expert, “gold standard” labels, it did so 93 percent of the time.

    “In the U.S., we’re also looking at over 90 percent accuracy, whereas with previous work in India, we’ve only seen 75 percent because ground labels are limited,” Wang says. “Now we can create these labels in a cheap and automated way.”

    The researchers are moving to map crops across India, where roadside images via Google Street View and other services have recently become available.

    “There are over 150 million smallholder farmers in India,” Wang says. “India is covered in agriculture, almost wall-to-wall farms, but very small farms, and historically it’s been very difficult to create maps of India because there are very sparse ground labels.”

    The team is working to generate crop maps in India, which could be used to inform policies having to do with assessing and bolstering yields, as global temperatures and populations rise.

    “What would be interesting would be to create these maps over time,” Wang says. “Then you could start to see trends, and we can try to relate those things to anything like changes in climate and policies.” More

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    K. Lisa Yang Global Engineering and Research Center will prioritize innovations for resource-constrained communities

    Billions of people worldwide face threats to their livelihood, health, and well-being due to poverty. These problems persist because solutions offered in developed countries often do not meet the requirements — related to factors like price, performance, usability, robustness, and culture — of poor or developing countries. Academic labs frequently try to tackle these challenges, but often to no avail because they lack real-world, on-the-ground knowledge from key stakeholders, and because they do not have an efficient, reliable means of converting breakthroughs to real-world impact.

    The new K. Lisa Yang Global Engineering and Research (GEAR) Center at MIT, founded with a $28 million gift from philanthropist and investor Lisa Yang, aims to rethink how products and technologies for resource-constrained communities are conceived, designed, and commercialized. A collaboration between MIT’s School of Engineering and School of Science, the Yang GEAR Center will bring together a multidisciplinary team of MIT researchers to assess today’s most pressing global challenges in three critical areas: global health, climate change mitigation and adaptation, and the water-energy-food nexus.

    “As she has shown over and over through her philanthropy, Lisa Yang shares MIT’s passion for connecting fundamental research and real-world data to create positive impact,” says MIT president Sally Kornbluth. “I’m grateful for her powerful vision and incredible generosity in founding the K. Lisa Yang GEAR Center. I can’t imagine a better use of MIT’s talents than working to improve the lives and health of people around the world.”

    Yang’s gift expands her exceptional philanthropic support of human health and basic science research at MIT over the past six years. Yang GEAR Center will join MIT’s Yang Tan Collective, an assemblage of six major research centers focused on accelerating collaboration in basic science, research, and engineering to realize translational strategies that improve human health and well-being at a global scale.

    “Billions of people face daily life-or-death challenges that could be improved with elegant technologies,” says Yang. “And yet I’ve learned how many products and tools created by top engineers don’t make it out of the lab. They may look like clever ideas during the prototype phase, but they are entirely ill-suited to the communities they were designed for. I am very excited about the potential of a deliberate and thoughtful engineering effort that will prioritize the design of technologies for use in impoverished communities.”

    Cost, material availability, cultural suitability, and other market mismatches hinder many major innovations in global health, food, and water from being translated to use in resource-constrained communities. Yang GEAR Center will support a major research and design program with its mission to strategically identify compelling challenges and associated scientific knowledge gaps in resource-constrained communities then address them through academic innovation to create and translate transformative technologies.

    The center will be led by Amos Winter, associate professor of mechanical engineering, whose lab focuses on creating technologies that marry innovative, low-cost design with an in-depth understanding of the unique socioeconomic constraints of emerging markets.

    “Academia has a key role to play in solving the historically unsolvable challenges in resource-constrained communities,” says Winter. “However, academic research is often disconnected from the real-world requirements that must be satisfied to make meaningful change. Yang GEAR Center will be a catalyst for innovation to impact by helping colleagues identify compelling problems and focus their talents on realizing real-world solutions, and by providing mechanisms for commercial dissemination. I am extremely grateful to find in Lisa a partner who shares a vision for how academic research can play a more efficient and targeted role in addressing the needs of the world’s most disadvantaged populations.”

    The backbone of the Yang GEAR Center will be a team of seasoned research scientists and engineers. These individuals will scout real-world problems and distill the relevant research questions then help assemble collaborative teams. As projects develop, center staff will mentor students, build and conduct field pilots, and foster relationships with stakeholders around the world. They will be strategically positioned to translate technology at the end of projects through licensing and startups. Center staff and collaborators will focus on creating products and services for climate-driven migrants, such as solar-powered energy and water networks; technologies for reducing atmospheric carbon and promoting the hydrogen economy; brackish water desalination and irrigation solutions; and high-performance, global health diagnostics and devices.

    For instance, a Yang GEAR Center team focused on creating water-saving and solar-powered irrigation solutions for farmers in the Middle East and North Africa will continue its work in the region. They will conduct exploratory research; build a team of stakeholders, including farmers, agricultural outreach organizations, irrigation hardware manufacturers, retailers, water and agriculture scientists, and local government officials; design, rigorously test, and iterate prototypes both in the lab and in the field; and conduct large-scale field trials to garner user feedback and pave the way to product commercialization.

    “Grounded in foundational scientific research and blended with excellence in the humanities, MIT provides a framework that integrates people, economics, research, and innovation. By incorporating multiple perspectives — and being attentive to the needs and cultures of the people who will ultimately rely on research outcomes — MIT can have the greatest impact in areas of health, climate science, and resource security,” says Nergis Mavalvala, dean of the School of Science and the Curtis and Kathleen Marble Professor of Astrophysics.

    An overarching aim for the center will be to educate graduates who are global engineers, designers, and researchers positioned for a career of addressing compelling, high-impact challenges. The center includes four endowed Hock E. Tan GEAR Center Fellowships that will support graduate students and/or postdoctoral fellows eager to enter the field of global engineering. The fellowships are named for MIT alumnus and Broadcom CEO Hock E. Tan ’75 SM ’75.

    “I am thrilled that the Yang GEAR Center is taking a leading role in training problem-solvers who will rethink how products and inventions can help communities facing the most pressing challenges of our time,” adds Anantha Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “These talented young students,  postdocs, and staff have the potential to reach across disciplines — and across the globe — to truly transform the impact engineering can have in the future.” More

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    Food for thought

    MIT graduate student Juana De La O describes herself as a food-motivated organism, so it’s no surprise that she reaches for food and baking analogies when she’s discussing her thesis work in the lab of undergraduate officer and professor of biology Adam Martin. 

    Consider the formative stages of a croissant, she offers, occasionally providing homemade croissants to accompany the presentation: When one is forming the puff pastry, the dough is folded over the butter again and again. Tissues in a developing mouse embryo must similarly fold and bend, creating layers and structures that become the spine, head, and organs — but these tissues have no hands to induce those formative movements. 

    De La O is studying neural tube closure, the formation of the structure that becomes the spinal cord and the brain. Disorders like anencephaly and craniorachischisis occur when the head region fails to close in a developing fetus. It’s a heartbreaking defect, De La O says, because it’s 100 percent lethal — but the fetus fully develops otherwise. 

    “Your entire central nervous system hinges on this one event happening successfully,” she says. “On the fundamental level, we have a very limited understanding of the mechanisms required for neural closure to happen at all, much less an understanding of what goes wrong that leads to those defects.” 

    Hypothetically speaking

    De La O hails from Chicago, where she received an undergraduate degree from the University of Chicago and worked in the lab of Ilaria Rebay. De La O’s sister was the first person in her family to go to and graduate from college — De La O, in turn, is the first person in her family to pursue a PhD. 

    From her first time visiting campus, De La O could see MIT would provide a thrilling environment in which to study.

    “MIT was one of the few places where the students weren’t constantly complaining about how hard their life was,” she says. “At lunch with prospective students, they’d be talking to each other and then just organically slip into conversations about science.”

    The department emails acceptance letters and sends a physical copy via snail mail. De La O’s letter included a handwritten note from department head Amy Keating, then a graduate officer, who had interviewed De La O during her campus visit. 

    “That’s what really sold it for me,” she recalls. “I went to my PI [principal investigator]’s office and said, ‘I have new data’” and I showed her the letter, and there was lots of unintelligible crying.” 

    To prepare her for graduate school, her parents, both immigrants from Mexico, spent the summer teaching De La O to make all her favorite dishes because “comfort food feels like home.”   

    When she reached MIT, however, the Covid-19 pandemic ground the world to a halt and severely limited what students could experience during rotations. Far from home and living alone, De La O taught herself to bake, creating the confections she craved but couldn’t leave her apartment to purchase. De La O didn’t get to work as extensively as she would have liked during her rotation in the Martin lab. 

    Martin had recently returned from a sabbatical that was spent learning a new research model; historically a fly lab, Martin was planning to delve into mouse research. 

    “My final presentation was, ‘Here’s a hypothetical project I would hypothetically do if I were hypothetically going to work with mice in a fly lab,’” De La O says. 

    Martin recalls being impressed. De La O is skilled at talking about science in an earnest and engaging way, and she dug deep into the literature and identified points Martin hadn’t considered. 

    “This is a level of independence that I look for in a student because it is important to the science to have someone who is contributing their ideas and independent reading and research to a project,” Martin says. 

    After agreeing to join the lab — news she shared with Martin via a meme — she got to work. 

    Charting mouse development

    The neural tube forms from a flat sheet whose sides rise and meet to create a hollow cylinder. De La O has observed patterns of actin and myosin changing in space and time as the embryo develops. Actin and myosin are fibrous proteins that provide structure in eukaryotic cells. They are responsible for some cell movement, like muscle contraction or cell division. Fibers of actin and myosin can also connect across cells, forming vast networks that coordinate the movements of whole tissues. By looking at the structure of these networks, researchers can make predictions about how force is affecting those tissues.

    De La O has found indications of a difference in the tension across the tissue during the critical stages of neural tube closure, which contributes to the tissue’s ability to fold and form a tube. They are not the first research group to propose this, she notes, but they’re suggesting that the patterns of tension are not uniform during a single stage of development.

    “My project, on a really fundamental level, is an atlas for a really early stage of mouse development for actin and myosin,” De La O says. “This dataset doesn’t exist in the field yet.” 

    However, De La O has been performing analyses exclusively in fixed samples, so she may be quantifying phenomena that are not actually how tissues behave. To determine whether that’s the case, De La O plans to analyze live samples.

    The idea is that if one could carefully cut tissue and observe how quickly it recoils, like slicing through a taught rubber band, those measurements could be used to approximate force across the tissue. However, the techniques required are still being developed, and the greater Boston area currently lacks the equipment and expertise needed to attempt those experiments. 

    A big part of her work in the lab has been figuring out how to collect and analyze relevant data. This research has already taken her far and wide, both literally and virtually. 

    “We’ve found that people have been very generous with their time and expertise,” De La O says. “One of the benefits we, as fly people, brought into this field is we don’t know anything — so we’re going to question everything.”

    De La O traveled to the University of Virginia to learn live imaging techniques from associate professor of cell biology Ann Sutherland, and she’s also been in contact with Gabriel Galea at University College London, where Martin and De La O are considering a visit for further training. 

    “There are a lot of reasons why these experiments could go wrong, and one of them is that I’m not trained yet,” she says. “Once you know how to do things on an optimal setup, you can figure out how to make it work on a less-optimal setup.”

    Collaboration and community

    De La O has now expanded her cooking repertoire far beyond her family’s recipes and shares her new creations when she visits home. At MIT, she hosts dinner parties, including one where everything from the savory appetizers to the sweet desserts contained honey, thanks to an Independent Activities Period course about the producers of the sticky substance, and she made and tried apple pie for the first time with her fellow graduate students after an afternoon of apple picking. 

    De La O says she’s still learning how to say no to taking on additional work outside of her regular obligations as a PhD student; she’s found there’s a lot of pressure for underrepresented students to be at the forefront of diversity efforts, and although she finds that work extremely fulfilling, she can, and has, stretched herself too thin in the past. 

    “Every time I see an application that asks ‘How will you work to increase diversity,’ my strongest instinct is just to write ‘I’m brown and around — you’re welcome,’” she jokes. “The greatest amount of diversity work I will do is to get where I’m going. Me achieving my goals increases diversity inherently, but I also want to do well because I know if I do, I will make everything better for people coming after me.”

    De La O is confident her path will be in academia, and troubleshooting, building up protocols, and setting up standards for her work in the Martin Lab has been “an excellent part of my training program.” 

    De La O and Martin embarked on a new project in a new model for the lab for De La O’s thesis, so much of her graduate studies will be spent laying the groundwork for future research. 

    “I hope her travels open Juana’s eyes to science being a larger community and to teach her about how to lead a collaboration,” Martin says. “Overall, I think this project is excellent for a student with aspirations to be a PI. I benefited from extremely open-ended projects as a student and see, in retrospect, how they prepared me for my work today.” More