More stories

  • in

    Reducing food waste to increase access to affordable foods

    About a third of the world’s food supply never gets eaten. That means the water, labor, energy, and fertilizer that went into growing, processing, and distributing the food is wasted.

    On the other end of the supply chain are cash-strapped consumers, who have been further distressed in recent years by factors like the Covid-19 pandemic and inflation.

    Spoiler Alert, a company founded by two MIT alumni, is helping companies bridge the gap between food waste and food insecurity with a platform connecting major food and beverage brands with discount grocers, retailers, and nonprofits. The platform helps brands discount or donate excess and short-dated inventory days, weeks, and months before it expires.

    “There is a tremendous amount of underutilized data that exists in the manufacturing and distribution space that results in good food going to waste,” says Ricky Ashenfelter MBA ’15, who co-founded the company with Emily Malina MBA ’15.

    Spoiler Alert helps brands manage distressed inventory data, create offers for potential buyers, and review and accept bids. The platform is designed to work with companies’ existing inventory and fulfillment systems, using automation and pricing intelligence to further streamline sales.

    “At a high level, we’re a waste-prevention software built for sales and supply-chain teams,” Ashenfelter says. “You can think of it as a private [business-to-business] eBay of sorts.”

    Spoiler Alert is working with global companies like Nestle, Kraft Heinz, and Danone, as well as discount grocers like the United Grocery Outlet and Misfits Market. Those brands are already using the platform to reduce food waste and get more food on people’s tables.

    “Project Drawdown [a nonprofit working on climate solutions] has identified food waste as the number one priority to address the global climate crisis, so these types of corporate initiatives can be really powerful from an environmental standpoint,” Ashenfelter says, noting the nonprofit estimates food waste accounts for 8 percent of global greenhouse gas emissions. “Contrast that with growing levels of food insecurity and folks not being able to access affordable nutrition, and you start to see how tackling supply-chain inefficiency can have a dramatic impact from both an environmental and a social lens. That’s what motivates us.”

    Untapped data for change

    Ashenfelter came to MIT’s Sloan School of Management after several years in sustainability software and management consulting within the retail and consumer products industries.

    “I was really attracted to transitioning into something much more entrepreneurial, and to leverage not only Sloan’s focus on entrepreneurship, but also the broader MIT ecosystem’s focus on technology, entrepreneurship, clean tech innovation, and other themes along that front,” he says.

    Ashenfelter met Malina at one of Sloan’s admitted students events in 2013, and the founders soon set out to use data to decrease food waste.

    “For us, the idea was clear: How do we better leverage data to manage excess and short-dated inventory?” Ashenfelter says. “How we go about that has evolved over the last six years, but it’s all rooted in solving an enormous climate problem, solving a major food insecurity problem, and from a capitalistic standpoint, helping businesses cut costs and generate revenue from otherwise wasted products.”

    The founders spent many hours in the Martin Trust Center for MIT Entrepreneurship with support from the Sloan Sustainability Initiative, and used Spoiler Alert as a case study in nearly every class they took, thinking through product development, sales, marketing, pricing, and more through their coursework.

    “We brought our idea into just about every action learning class that we could at Sloan and MIT,” Ashenfelter says.

    They also participated in the MIT $100K Entrepreneurship Competition and received support from the Venture Mentoring Service and the IDEAS Global Challenge program.

    Upon graduation, the founders initially began building a platform to facilitate donations of excess inventory, but soon learned big companies’ processes for discounting that inventory were also highly manual. Today, more than 90 percent of Spoiler Alert’s transaction volume is discounted, with the remainder donated.

    Different teams within an organization can upload excess inventory reports to Spoiler Alert’s system, eliminating the need to manually aggregate datasets and preparing what the industry refers to as “blowout lists” to sell. Spoiler Alert uses machine-learning-based tools to help both parties with pricing and negotiations to close deals more quickly.

    “Companies are taking pretty manual and slow approaches to deciding [what to do with excess inventory],” Ashenfelter says. “And when you have slow decision-making, you’re losing days or even weeks of shelf life on that product. That can be the difference between selling product versus donating, and donating versus dumping.”

    Once a deal has been made, Spoiler Alert automatically generates the forms and workflows needed by fulfillment teams to get the product out the door. The relationships companies build on the platform are also a major driver for cutting down waste.

    “We’re providing suppliers with the ability to control where their discounted and donated product ends up,” Ashenfelter says. “That’s really powerful because it allows these CPG brands to ensure that this product is, in many cases, getting to affordable nutrition outlets in underserved communities.”

    Ashenfelter says the majority of inventory goes to regional and national discount grocers, supplemented with extensive purchasing from local and nonprofit grocery chains.

    “Everything we do is oriented around helping sell as much product as possible to a reputable set of buyers at the most fair, equitable prices possible,” Ashenfelter says.

    Scaling for impact

    The pandemic has disrupted many aspects of the food supply chains. But Ashenfelter says it has also accelerated the adoption of digital solutions that can better manage such volatility.

    When Campbell began using Spoiler Alert’s system in 2019, for instance, it achieved a 36 percent increase in discount sales and a 27 percent increase in donations over the first five months.

    Ashenfelter says the results have proven that companies’ sustainability targets can go hand in hand with initiatives that boost their bottom lines. In fact, because Spoiler Alert focuses so much on the untapped revenue associated with food waste, many customers don’t even realize Spoiler Alert is a sustainability company until after they’ve signed on.

    “What’s neat about this program is that it becomes an incredibly powerful case study internally for how sustainability and operational outcomes aren’t in conflict and can drive both business results as well as overall environmental impact,” Ashenfelter says.

    Going forward, Spoiler Alert will continue building out algorithmic solutions that could further cut down on waste internationally and across a wider array of products.

    “At every step in our process, we’re collecting a tremendous amount of data in terms of what is and isn’t selling, at what price point, to which buyers, out of which geographies, and with how much remaining shelf life,” Ashenfelter explains. “We are only starting to scratch the surface in terms of bringing our recommendations engine to life for our suppliers and buyers. Ultimately our goal is to power the waste-free economy, and rooted in that is making better decisions faster, in collaboration with a growing ecosystem of supply chain partners, and with as little manual intervention as possible.” More

  • in

    SMART researchers develop method for early detection of bacterial infection in crops

    Researchers from the Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP) Interdisciplinary Research Group (IRG) ofSingapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, and their local collaborators from Temasek Life Sciences Laboratory (TLL), have developed a rapid Raman spectroscopy-based method for detecting and quantifying early bacterial infection in crops. The Raman spectral biomarkers and diagnostic algorithm enable the noninvasive and early diagnosis of bacterial infections in crop plants, which can be critical for the progress of plant disease management and agricultural productivity.

    Due to the increasing demand for global food supply and security, there is a growing need to improve agricultural production systems and increase crop productivity. Globally, bacterial pathogen infection in crop plants is one of the major contributors to agricultural yield losses. Climate change also adds to the problem by accelerating the spread of plant diseases. Hence, developing methods for rapid and early detection of pathogen-infected crops is important to improve plant disease management and reduce crop loss.

    The breakthrough by SMART and TLL researchers offers a faster and more accurate method to detect bacterial infection in crop plants at an earlier stage, as compared to existing techniques. The new results appear in a paper titled “Rapid detection and quantification of plant innate immunity response using Raman spectroscopy” published in the journal Frontiers in Plant Science.

    “The early detection of pathogen-infected crop plants is a significant step to improve plant disease management,” says Chua Nam Hai, DiSTAP co-lead principal investigator, professor, TLL deputy chair, and co-corresponding author. “It will allow the fast and selective removal of pathogen load and curb the further spread of disease to other neighboring crops.”

    Traditionally, plant disease diagnosis involves a simple visual inspection of plants for disease symptoms and severity. “Visual inspection methods are often ineffective, as disease symptoms usually manifest only at relatively later stages of infection, when the pathogen load is already high and reparative measures are limited. Hence, new methods are required for rapid and early detection of bacterial infection. The idea would be akin to having medical tests to identify human diseases at an early stage, instead of waiting for visual symptoms to show, so that early intervention or treatment can be applied,” says MIT Professor Rajeev Ram, who is a DiSTAP principal investigator and co-corresponding author on the paper.

    While existing techniques, such as current molecular detection methods, can detect bacterial infection in plants, they are often limited in their use. Molecular detection methods largely depend on the availability of pathogen-specific gene sequences or antibodies to identify bacterial infection in crops; the implementation is also time-consuming and nonadaptable for on-site field application due to the high cost and bulky equipment required, making it impractical for use in agricultural farms.

    “At DiSTAP, we have developed a quantitative Raman spectroscopy-based algorithm that can help farmers to identify bacterial infection rapidly. The developed diagnostic algorithm makes use of Raman spectral biomarkers and can be easily implemented in cloud-based computing and prediction platforms. It is more effective than existing techniques as it enables accurate identification and early detection of bacterial infection, both of which are crucial to saving crop plants that would otherwise be destroyed,” explains Gajendra Pratap Singh, scientific director and principal investigator at DiSTAP and co-lead author.

    A portable Raman system can be used on farms and provides farmers with an accurate and simple yes-or-no response when used to test for the presence of bacterial infections in crops. The development of this rapid and noninvasive method could improve plant disease management and have a transformative impact on agricultural farms by efficiently reducing agricultural yield loss and increasing productivity.

    “Using the diagnostic algorithm method, we experimented on several edible plants such as choy sum,” says DiSTAP and TLL principal investigator and co-corresponding author Rajani Sarojam. “The results showed that the Raman spectroscopy-based method can swiftly detect and quantify innate immunity response in plants infected with bacterial pathogens. We believe that this technology will be beneficial for agricultural farms to increase their productivity by reducing their yield loss due to plant diseases.”

    The researchers are currently working on the development of high-throughput, custom-made portable or hand-held Raman spectrometers that will allow Raman spectral analysis to be quickly and easily performed on field-grown crops.

    SMART and TLL developed and discovered the diagnostic algorithm and Raman spectral biomarkers. TLL also confirmed and validated the detection method through mutant plants. The research is carried out by SMART and supported by the National Research Foundation of Singapore under its Campus for Research Excellence And Technological Enterprise (CREATE) program.

    SMART was established by MIT and the NRF in 2007. The first entity in CREATE developed by NRF, SMART serves as an intellectual and innovation hub for research interactions between MIT and Singapore, undertaking cutting-edge research projects in areas of interest to both Singapore and MIT. SMART currently comprises an Innovation Center and five IRGs: Antimicrobial Resistance, Critical Analytics for Manufacturing Personalized-Medicine, DiSTAP, Future Urban Mobility, and Low Energy Electronic Systems. SMART research is funded by the NRF under the CREATE program.

    Led by Professor Michael Strano of MIT and Professor Chua Nam Hai of Temasek Lifesciences Laboratory, the DiSTAP program addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical, genetic, and biomaterial technologies. The goal is to fundamentally change how plant biosynthetic pathways are discovered, monitored, engineered, and ultimately translated to meet the global demand for food and nutrients. Scientists from MIT, TTL, Nanyang Technological University, and National University of Singapore are collaboratively developing new tools for the continuous measurement of important plant metabolites and hormones for novel discovery, deeper understanding and control of plant biosynthetic pathways in ways not yet possible, especially in the context of green leafy vegetables; leveraging these new techniques to engineer plants with highly desirable properties for global food security, including high-yield density production, and drought and pathogen resistance; and applying these technologies to improve urban farming. More

  • in

    J-WAFS launches Food and Climate Systems Transformation Alliance

    Food systems around the world are increasingly at risk from the impacts of climate change. At the same time, these systems, which include all activities from food production to consumption and food waste, are responsible for about one-third of the human-caused greenhouse gas emissions warming the planet. 

    To drive research-based innovation that will make food systems more resilient and sustainable, MIT’s Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) announced the launch of a new initiative at an event during the UN Climate Change Conference in Glasgow, Scotland, last week. The initiative, called the Food and Climate Systems Transformation (FACT) Alliance, will better connect researchers to farmers, food businesses, policymakers, and other food systems stakeholders around the world. 

    “Time is not on our side,” says Greg Sixt, the director of the FACT Alliance and research manager for food and climate systems at J-WAFS. “To date, the research community hasn’t delivered actionable solutions quickly enough or in the policy-relevant form needed if time-critical changes are to be made to our food systems. The FACT Alliance aims to change this.”

    Why, in fact, do our food systems need transformation?

    At COP26 (which stands for “conference of the parties” to the UN Framework Convention on Climate Change, being held for the 26th time this year), a number of countries have pledged to end deforestation, reduce methane emissions, and cease public financing of coal power. In his keynote address at the FACT Alliance event, Professor Pete Smith of the University of Aberdeen, an alliance member institution, noted that food and agriculture also need to be addressed because “there’s an interaction between climate change and the food system.” 

    The UN Intergovernmental Panel on Climate Change warns that a two-degree Celsius increase in average global temperature over preindustrial levels could trigger a worldwide food crisis, and emissions from food systems alone could push us past the two-degree mark even if energy-related emissions could be zeroed out. 

    Smith said dramatic and rapid transformations are needed to deliver safe, nutritious food for all, with reduced environmental impact and increased resilience to climate change. With a global network of leading research institutions and collaborating stakeholder organizations, the FACT Alliance aims to facilitate new, solutions-oriented research for addressing the most challenging aspects of food systems in the era of climate change. 

    How the FACT Alliance works

    Central to the work of the FACT Alliance is the development of new methodologies for aligning data across scales and food systems components, improving data access, integrating research across the diverse disciplines that address aspects of food systems, making stakeholders partners in the research process, and assessing impact in the context of complex and interconnected food and climate systems. 

    The FACT Alliance will conduct what’s known as “convergence research,” which meets complex problems with approaches that embody deep integration across disciplines. This kind of research calls for close association with the stakeholders who both make decisions and are directly affected by how food systems work, be they farmers, extension services (i.e., agricultural advisories), policymakers, international aid organizations, consumers, or others. By inviting stakeholders and collaborators to be part of the research process, the FACT Alliance allows for engagement at the scale, geography, and scope that is most relevant to the needs of each, integrating global and local teams to achieve better outcomes. 

    “Doing research in isolation of all the stakeholders and in isolation of the goals that we want to achieve will not deliver the transformation that we need,” said Smith. “The problem is too big for us to solve in isolation, and we need broad alliances to tackle the issue, and that’s why we developed the FACT Alliance.” 

    Members and collaborators

    Led by MIT’s J-WAFS, the FACT Alliance is currently made up of 16 core members and an associated network of collaborating stakeholder organizations. 

    “As the central convener of MIT research on food systems, J-WAFS catalyzes collaboration across disciplines,” says Maria Zuber, vice president for research at MIT. “Now, by bringing together a world-class group of research institutions and stakeholders from key sectors, the FACT Alliance aims to advance research that will help alleviate climate impacts on food systems and mitigate food system impacts on climate.”

    J-WAFS co-hosted the COP26 event “Bridging the Science-Policy Gap for Impactful, Demand-Driven Food Systems Innovation” with Columbia University, the American University of Beirut, and the CGIAR research program Climate Change, Agriculture and Food Security (CCAFS). The event featured a panel discussion with several FACT Alliance members and the UK Foreign, Commonwealth and Development Office (FCDO). More

  • in

    Saving seaweed with machine learning

    Last year, Charlene Xia ’17, SM ’20 found herself at a crossroads. She was finishing up her master’s degree in media arts and sciences from the MIT Media Lab and had just submitted applications to doctoral degree programs. All Xia could do was sit and wait. In the meantime, she narrowed down her career options, regardless of whether she was accepted to any program.

    “I had two thoughts: I’m either going to get a PhD to work on a project that protects our planet, or I’m going to start a restaurant,” recalls Xia.

    Xia poured over her extensive cookbook collection, researching international cuisines as she anxiously awaited word about her graduate school applications. She even looked into the cost of a food truck permit in the Boston area. Just as she started hatching plans to open a plant-based skewer restaurant, Xia received word that she had been accepted into the mechanical engineering graduate program at MIT.

    Shortly after starting her doctoral studies, Xia’s advisor, Professor David Wallace, approached her with an interesting opportunity. MathWorks, a software company known for developing the MATLAB computing platform, had announced a new seed funding program in MIT’s Department of Mechanical Engineering. The program encouraged collaborative research projects focused on the health of the planet.

    “I saw this as a super-fun opportunity to combine my passion for food, my technical expertise in ocean engineering, and my interest in sustainably helping our planet,” says Xia.

    Play video

    From MIT Mechanical Engineering: “Saving Seaweed with Machine Learning”

    Wallace knew Xia would be up to the task of taking an interdisciplinary approach to solve an issue related to the health of the planet. “Charlene is a remarkable student with extraordinary talent and deep thoughtfulness. She is pretty much fearless, embracing challenges in almost any domain with the well-founded belief that, with effort, she will become a master,” says Wallace.

    Alongside Wallace and Associate Professor Stefanie Mueller, Xia proposed a project to predict and prevent the spread of diseases in aquaculture. The team focused on seaweed farms in particular.

    Already popular in East Asian cuisines, seaweed holds tremendous potential as a sustainable food source for the world’s ever-growing population. In addition to its nutritive value, seaweed combats various environmental threats. It helps fight climate change by absorbing excess carbon dioxide in the atmosphere, and can also absorb fertilizer run-off, keeping coasts cleaner.

    As with so much of marine life, seaweed is threatened by the very thing it helps mitigate against: climate change. Climate stressors like warm temperatures or minimal sunlight encourage the growth of harmful bacteria such as ice-ice disease. Within days, entire seaweed farms are decimated by unchecked bacterial growth.

    To solve this problem, Xia turned to the microbiota present in these seaweed farms as a predictive indicator of any threat to the seaweed or livestock. “Our project is to develop a low-cost device that can detect and prevent diseases before they affect seaweed or livestock by monitoring the microbiome of the environment,” says Xia.

    The team pairs old technology with the latest in computing. Using a submersible digital holographic microscope, they take a 2D image. They then use a machine learning system known as a neural network to convert the 2D image into a representation of the microbiome present in the 3D environment.

    “Using a machine learning network, you can take a 2D image and reconstruct it almost in real time to get an idea of what the microbiome looks like in a 3D space,” says Xia.

    The software can be run in a small Raspberry Pi that could be attached to the holographic microscope. To figure out how to communicate these data back to the research team, Xia drew upon her master’s degree research.

    In that work, under the guidance of Professor Allan Adams and Professor Joseph Paradiso in the Media Lab, Xia focused on developing small underwater communication devices that can relay data about the ocean back to researchers. Rather than the usual $4,000, these devices were designed to cost less than $100, helping lower the cost barrier for those interested in uncovering the many mysteries of our oceans. The communication devices can be used to relay data about the ocean environment from the machine learning algorithms.

    By combining these low-cost communication devices along with microscopic images and machine learning, Xia hopes to design a low-cost, real-time monitoring system that can be scaled to cover entire seaweed farms.

    “It’s almost like having the ‘internet of things’ underwater,” adds Xia. “I’m developing this whole underwater camera system alongside the wireless communication I developed that can give me the data while I’m sitting on dry land.”

    Armed with these data about the microbiome, Xia and her team can detect whether or not a disease is about to strike and jeopardize seaweed or livestock before it is too late.

    While Xia still daydreams about opening a restaurant, she hopes the seaweed project will prompt people to rethink how they consider food production in general.

    “We should think about farming and food production in terms of the entire ecosystem,” she says. “My meta-goal for this project would be to get people to think about food production in a more holistic and natural way.” More

  • in

    New “risk triage” platform pinpoints compounding threats to US infrastructure

    Over a 36-hour period in August, Hurricane Henri delivered record rainfall in New York City, where an aging storm-sewer system was not built to handle the deluge, resulting in street flooding. Meanwhile, an ongoing drought in California continued to overburden aquifers and extend statewide water restrictions. As climate change amplifies the frequency and intensity of extreme events in the United States and around the world, and the populations and economies they threaten grow and change, there is a critical need to make infrastructure more resilient. But how can this be done in a timely, cost-effective way?

    An emerging discipline called multi-sector dynamics (MSD) offers a promising solution. MSD homes in on compounding risks and potential tipping points across interconnected natural and human systems. Tipping points occur when these systems can no longer sustain multiple, co-evolving stresses, such as extreme events, population growth, land degradation, drinkable water shortages, air pollution, aging infrastructure, and increased human demands. MSD researchers use observations and computer models to identify key precursory indicators of such tipping points, providing decision-makers with critical information that can be applied to mitigate risks and boost resilience in infrastructure and managed resources.

    At MIT, the Joint Program on the Science and Policy of Global Change has since 2018 been developing MSD expertise and modeling tools and using them to explore compounding risks and potential tipping points in selected regions of the United States. In a two-hour webinar on Sept. 15, MIT Joint Program researchers presented an overview of the program’s MSD research tool set and its applications.  

    MSD and the risk triage platform

    “Multi-sector dynamics explores interactions and interdependencies among human and natural systems, and how these systems may adapt, interact, and co-evolve in response to short-term shocks and long-term influences and stresses,” says MIT Joint Program Deputy Director C. Adam Schlosser, noting that such analysis can reveal and quantify potential risks that would likely evade detection in siloed investigations. “These systems can experience cascading effects or failures after crossing tipping points. The real question is not just where these tipping points are in each system, but how they manifest and interact across all systems.”

    To address that question, the program’s MSD researchers have developed the MIT Socio-Environmental Triage (MST) platform, now publicly available for the first time. Focused on the continental United States, the first version of the platform analyzes present-day risks related to water, land, climate, the economy, energy, demographics, health, and infrastructure, and where these compound to create risk hot spots. It’s essentially a screening-level visualization tool that allows users to examine risks, identify hot spots when combining risks, and make decisions about how to deploy more in-depth analysis to solve complex problems at regional and local levels. For example, MST can identify hot spots for combined flood and poverty risks in the lower Mississippi River basin, and thereby alert decision-makers as to where more concentrated flood-control resources are needed.

    Successive versions of the platform will incorporate projections based on the MIT Joint Program’s Integrated Global System Modeling (IGSM) framework of how different systems and stressors may co-evolve into the future and thereby change the risk landscape. This enhanced capability could help uncover cost-effective pathways for mitigating and adapting to a wide range of environmental and economic risks.  

    MSD applications

    Five webinar presentations explored how MIT Joint Program researchers are applying the program’s risk triage platform and other MSD modeling tools to identify potential tipping points and risks in five key domains: water quality, land use, economics and energy, health, and infrastructure. 

    Joint Program Principal Research Scientist Xiang Gao described her efforts to apply a high-resolution U.S. water-quality model to calculate a location-specific, water-quality index over more than 2,000 river basins in the country. By accounting for interactions among climate, agriculture, and socioeconomic systems, various water-quality measures can be obtained ranging from nitrate and phosphate levels to phytoplankton concentrations. This modeling approach advances a unique capability to identify potential water-quality risk hot spots for freshwater resources.

    Joint Program Research Scientist Angelo Gurgel discussed his MSD-based analysis of how climate change, population growth, changing diets, crop-yield improvements and other forces that drive land-use change at the global level may ultimately impact how land is used in the United States. Drawing upon national observational data and the IGSM framework, the analysis shows that while current U.S. land-use trends are projected to persist or intensify between now and 2050, there is no evidence of any concerning tipping points arising throughout this period.  

    MIT Joint Program Research Scientist Jennifer Morris presented several examples of how the risk triage platform can be used to combine existing U.S. datasets and the IGSM framework to assess energy and economic risks at the regional level. For example, by aggregating separate data streams on fossil-fuel employment and poverty, one can target selected counties for clean energy job training programs as the nation moves toward a low-carbon future. 

    “Our modeling and risk triage frameworks can provide pictures of current and projected future economic and energy landscapes,” says Morris. “They can also highlight interactions among different human, built, and natural systems, including compounding risks that occur in the same location.”  

    MIT Joint Program research affiliate Sebastian Eastham, a research scientist at the MIT Laboratory for Aviation and the Environment, described an MSD approach to the study of air pollution and public health. Linking the IGSM with an atmospheric chemistry model, Eastham ultimately aims to better understand where the greatest health risks are in the United States and how they may compound throughout this century under different policy scenarios. Using the risk triage tool to combine current risk metrics for air quality and poverty in a selected county based on current population and air-quality data, he showed how one can rapidly identify cardiovascular and other air-pollution-induced disease risk hot spots.

    Finally, MIT Joint Program research affiliate Alyssa McCluskey, a lecturer at the University of Colorado at Boulder, showed how the risk triage tool can be used to pinpoint potential risks to roadways, waterways, and power distribution lines from flooding, extreme temperatures, population growth, and other stressors. In addition, McCluskey described how transportation and energy infrastructure development and expansion can threaten critical wildlife habitats.

    Enabling comprehensive, location-specific analyses of risks and hot spots within and among multiple domains, the Joint Program’s MSD modeling tools can be used to inform policymaking and investment from the municipal to the global level.

    “MSD takes on the challenge of linking human, natural, and infrastructure systems in order to inform risk analysis and decision-making,” says Schlosser. “Through our risk triage platform and other MSD models, we plan to assess important interactions and tipping points, and to provide foresight that supports action toward a sustainable, resilient, and prosperous world.”

    This research is funded by the U.S. Department of Energy’s Office of Science as an ongoing project. More

  • in

    Research collaboration puts climate-resilient crops in sight

    Any houseplant owner knows that changes in the amount of water or sunlight a plant receives can put it under immense stress. A dying plant brings certain disappointment to anyone with a green thumb. 

    But for farmers who make their living by successfully growing plants, and whose crops may nourish hundreds or thousands of people, the devastation of failing flora is that much greater. As climate change is poised to cause increasingly unpredictable weather patterns globally, crops may be subject to more extreme environmental conditions like droughts, fluctuating temperatures, floods, and wildfire. 

    Climate scientists and food systems researchers worry about the stress climate change may put on crops, and on global food security. In an ambitious interdisciplinary project funded by the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), David Des Marais, the Gale Assistant Professor in the Department of Civil and Environmental Engineering at MIT, and Caroline Uhler, an associate professor in the MIT Department of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society, are investigating how plant genes communicate with one another under stress. Their research results can be used to breed plants more resilient to climate change.

    Crops in trouble

    Governing plants’ responses to environmental stress are gene regulatory networks, or GRNs, which guide the development and behaviors of living things. A GRN may be comprised of thousands of genes and proteins that all communicate with one another. GRNs help a particular cell, tissue, or organism respond to environmental changes by signaling certain genes to turn their expression on or off.

    Even seemingly minor or short-term changes in weather patterns can have large effects on crop yield and food security. An environmental trigger, like a lack of water during a crucial phase of plant development, can turn a gene on or off, and is likely to affect many others in the GRN. For example, without water, a gene enabling photosynthesis may switch off. This can create a domino effect, where the genes that rely on those regulating photosynthesis are silenced, and the cycle continues. As a result, when photosynthesis is halted, the plant may experience other detrimental side effects, like no longer being able to reproduce or defend against pathogens. The chain reaction could even kill a plant before it has the chance to be revived by a big rain.

    Des Marais says he wishes there was a way to stop those genes from completely shutting off in such a situation. To do that, scientists would need to better understand how exactly gene networks respond to different environmental triggers. Bringing light to this molecular process is exactly what he aims to do in this collaborative research effort.

    Solving complex problems across disciplines

    Despite their crucial importance, GRNs are difficult to study because of how complex and interconnected they are. Usually, to understand how a particular gene is affecting others, biologists must silence one gene and see how the others in the network respond. 

    For years, scientists have aspired to an algorithm that could synthesize the massive amount of information contained in GRNs to “identify correct regulatory relationships among genes,” according to a 2019 article in the Encyclopedia of Bioinformatics and Computational Biology. 

    “A GRN can be seen as a large causal network, and understanding the effects that silencing one gene has on all other genes requires understanding the causal relationships among the genes,” says Uhler. “These are exactly the kinds of algorithms my group develops.”

    Des Marais and Uhler’s project aims to unravel these complex communication networks and discover how to breed crops that are more resilient to the increased droughts, flooding, and erratic weather patterns that climate change is already causing globally.

    In addition to climate change, by 2050, the world will demand 70 percent more food to feed a booming population. “Food systems challenges cannot be addressed individually in disciplinary or topic area silos,” says Greg Sixt, J-WAFS’ research manager for climate and food systems. “They must be addressed in a systems context that reflects the interconnected nature of the food system.”

    Des Marais’ background is in biology, and Uhler’s in statistics. “Dave’s project with Caroline was essentially experimental,” says Renee J. Robins, J-WAFS’ executive director. “This kind of exploratory research is exactly what the J-WAFS seed grant program is for.”

    Getting inside gene regulatory networks

    Des Marais and Uhler’s work begins in a windowless basement on MIT’s campus, where 300 genetically identical Brachypodium distachyon plants grow in large, temperature-controlled chambers. The plant, which contains more than 30,000 genes, is a good model for studying important cereal crops like wheat, barley, maize, and millet. For three weeks, all plants receive the same temperature, humidity, light, and water. Then, half are slowly tapered off water, simulating drought-like conditions.

    Six days into the forced drought, the plants are clearly suffering. Des Marais’ PhD student Jie Yun takes tissues from 50 hydrated and 50 dry plants, freezes them in liquid nitrogen to immediately halt metabolic activity, grinds them up into a fine powder, and chemically separates the genetic material. The genes from all 100 samples are then sequenced at a lab across the street.

    The team is left with a spreadsheet listing the 30,000 genes found in each of the 100 plants at the moment they were frozen, and how many copies there were. Uhler’s PhD student Anastasiya Belyaeva inputs the massive spreadsheet into the computer program she developed and runs her novel algorithm. Within a few hours, the group can see which genes were most active in one condition over another, how the genes were communicating, and which were causing changes in others. 

    The methodology captures important subtleties that could allow researchers to eventually alter gene pathways and breed more resilient crops. “When you expose a plant to drought stress, it’s not like there’s some canonical response,” Des Marais says. “There’s lots of things going on. It’s turning this physiologic process up, this one down, this one didn’t exist before, and now suddenly is turned on.” 

    In addition to Des Marais and Uhler’s research, J-WAFS has funded projects in food and water from researchers in 29 departments across all five MIT schools as well as the MIT Schwarzman College of Computing. J-WAFS seed grants typically fund seven to eight new projects every year.

    “The grants are really aimed at catalyzing new ideas, providing the sort of support [for MIT researchers] to be pushing boundaries, and also bringing in faculty who may have some interesting ideas that they haven’t yet applied to water or food concerns,” Robins says. “It’s an avenue for researchers all over the Institute to apply their ideas to water and food.”

    Alison Gold is a student in MIT’s Graduate Program in Science Writing. More

  • in

    Researchers design sensors to rapidly detect plant hormones

    Researchers from the Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP) interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, and their local collaborators from Temasek Life Sciences Laboratory (TLL) and Nanyang Technological University (NTU), have developed the first-ever nanosensor to enable rapid testing of synthetic auxin plant hormones. The novel nanosensors are safer and less tedious than existing techniques for testing plants’ response to compounds such as herbicide, and can be transformative in improving agricultural production and our understanding of plant growth.

    The scientists designed sensors for two plant hormones — 1-naphthalene acetic acid (NAA) and 2,4-dichlorophenoxyacetic acid (2,4-D) — which are used extensively in the farming industry for regulating plant growth and as herbicides, respectively. Current methods to detect NAA and 2,4-D cause damage to plants, and are unable to provide real-time in vivo monitoring and information.

    Based on the concept of corona phase molecular recognition (​​CoPhMoRe) pioneered by the Strano Lab at SMART DiSTAP and MIT, the new sensors are able to detect the presence of NAA and 2,4-D in living plants at a swift pace, providing plant information in real-time, without causing any harm. The team has successfully tested both sensors on a number of everyday crops including pak choi, spinach, and rice across various planting mediums such as soil, hydroponic, and plant tissue culture.

    Explained in a paper titled “Nanosensor Detection of Synthetic Auxins In Planta using Corona Phase Molecular Recognition” published in the journal ACS Sensors, the research can facilitate more efficient use of synthetic auxins in agriculture and hold tremendous potential to advance plant biology study.

    “Our CoPhMoRe technique has previously been used to detect compounds such as hydrogen peroxide and heavy-metal pollutants like arsenic — but this is the first successful case of CoPhMoRe sensors developed for detecting plant phytohormones that regulate plant growth and physiology, such as sprays to prevent premature flowering and dropping of fruits,” says DiSTAP co-lead principal investigator Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT. “This technology can replace current state-of-the-art sensing methods which are laborious, destructive, and unsafe.”

    Of the two sensors developed by the research team, the 2,4-D nanosensor also showed the ability to detect herbicide susceptibility, enabling farmers and agricultural scientists to quickly find out how vulnerable or resistant different plants are to herbicides without the need to monitor crop or weed growth over days. “This could be incredibly beneficial in revealing the mechanism behind how 2,4-D works within plants and why crops develop herbicide resistance,” says DiSTAP and TLL Principal Investigator Rajani Sarojam.

    “Our research can help the industry gain a better understanding of plant growth dynamics and has the potential to completely change how the industry screens for herbicide resistance, eliminating the need to monitor crop or weed growth over days,” says Mervin Chun-Yi Ang, a research scientist at DiSTAP. “It can be applied across a variety of plant species and planting mediums, and could easily be used in commercial setups for rapid herbicide susceptibility testing, such as urban farms.”

    NTU Professor Mary Chan-Park Bee Eng says, “Using nanosensors for in planta detection eliminates the need for extensive extraction and purification processes, which saves time and money. They also use very low-cost electronics, which makes them easily adaptable for commercial setups.”

    The team says their research can lead to future development of real-time nanosensors for other dynamic plant hormones and metabolites in living plants as well.

    The development of the nanosensor, optical detection system, and image processing algorithms for this study was done by SMART, NTU, and MIT, while TLL validated the nanosensors and provided knowledge of plant biology and plant signaling mechanisms. The research is carried out by SMART and supported by NRF under its Campus for Research Excellence And Technological Enterprise (CREATE) program.

    DiSTAP is one of the five interdisciplinary research roups in SMART. The DiSTAP program addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical, genetic, and biosynthetic technologies. The goal is to fundamentally change how plant biosynthetic pathways are discovered, monitored, engineered, and ultimately translated to meet the global demand for food and nutrients.

    Scientists from MIT, TTL, NTU, and National University of Singapore (NUS) are collaboratively developing new tools for the continuous measurement of important plant metabolites and hormones for novel discovery, deeper understanding and control of plant biosynthetic pathways in ways not yet possible, especially in the context of green leafy vegetables; leveraging these new techniques to engineer plants with highly desirable properties for global food security, including high yield density production, drought, and pathogen resistance and biosynthesis of high-value commercial products; developing tools for producing hydrophobic food components in industry-relevant microbes; developing novel microbial and enzymatic technologies to produce volatile organic compounds that can protect and/or promote growth of leafy vegetables; and applying these technologies to improve urban farming.

    DiSTAP is led by Michael Strano and Singapore co-lead principal investigator Professor Chua Nam Hai.

    SMART was established by MIT, in partnership with the NRF, in 2007. SMART, the first entity in CREATE, serves as an intellectual and innovation hub for research interactions between MIT and Singapore, undertaking cutting-edge research projects in areas of interest to both. SMART currently comprises an Innovation Center and five interdisciplinary research groups: Antimicrobial Resistance (AMR), Critical Analytics for Manufacturing Personalized-Medicine (CAMP), DiSTAP, Future Urban Mobility (FM), and Low Energy Electronic Systems (LEES). SMART is funded by the NRF. More

  • in

    J-WAFS announces 2021 Solutions Grants for commercializing water and food technologies

    The Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) recently announced the 2021 J-WAFS Solutions grant recipients. The J-WAFS Solutions program aims to propel MIT water- and food-related research toward commercialization. Grant recipients receive one year of financial support, as well as mentorship, networking, and guidance from industry experts, to begin their journey into the commercial world — whether that be in the form of bringing innovative products to market or launching cutting-edge startup companies. 

    This year, three projects will receive funding across water, food, and agriculture spaces. The winning projects will advance nascent technologies for off-grid refrigeration, portable water filtration, and dairy waste recycling. Each provides an efficient, accessible solution to the respective challenge being addressed.

    Since the start of the J-WAFS Solutions program in 2015, grants have provided instrumental support in creating a number of key MIT startups that focus on major water and food challenges. A 2015-16 grant helped the team behind Via Separations develop their business plan to massively decarbonize industrial separations processes. Other successful J-WAFS Solutions alumni include researchers who created a low-cost water filter made from tree branches and the team that launched the startup Xibus Systems, which is developing a handheld food safety sensor.

    “New technological advances are being made at MIT every day, and J-WAFS Solutions grants provide critical resources and support for these technologies to make it to market so that they can transform our local and global water and food systems,” says J-WAFS Executive Director Renee Robins. “This year’s grant recipients offer innovative tools that will provide more accessible food storage for smallholder farmers in places like Africa, safer drinking water, and a new approach to recycling food waste,” Robins notes. She adds, “J-WAFS is excited to work with these teams, and we look forward to seeing their impact on the water and food sectors.”

    The J-WAFS Solutions program is implemented in collaboration with Community Jameel, the global philanthropic organization founded by Mohammed Jameel ’78, and is supported by the MIT Venture Mentoring Service and the iCorps New England Regional Innovation Node at MIT.

    Mobile evaporative cooling rooms for vegetable preservation

    Food waste is a persistent problem across food systems supply chains, as 30-50 percent of food produced is lost before it reaches the table. The problem is compounded in areas without access to the refrigeration necessary to store food after it is harvested. Hot and dry climates in particular struggle to preserve food before it reaches consumers. A team led by Daniel Frey, faculty director for research at MIT D-Lab and professor of mechanical engineering, has pioneered a new approach to enable farmers to better preserve their produce and improve access to nutritious food in the community. The team includes Leon Glicksman, professor of building technology and mechanical engineering, and Eric Verploegen, a research engineer in MIT D-Lab.

    Instead of relying on traditional refrigeration with high energy and cost requirements, the team is utilizing forced-air evaporative cooling chambers. Their design, based on retrofitting shipping containers, will provide a lower-cost, better-performing solution enabling farmers to chill their produce without access to power. The research team was previously funded by J-WAFS through two different grants in 2019 to develop the off-grid technology in collaboration with researchers at the University of Nairobi and the Collectives for Integrated Livelihood Initiatives (CInI), Jamshedpur. Now, the cooling rooms are ready for pilot testing, which the MIT team will conduct with rural farmers in Kenya and India. The MIT team will deploy and test the storage chambers through collaborations with two Kenyan social enterprises and a nongovernmental organization in Gujarat, India. 

    Off-grid portable ion concentration polarization desalination unit

    Shrinking aquifers, polluted rivers, and increased drought are making fresh drinking water increasingly scarce, driving the need for improved desalination technologies. The water purifiers market, which was $45 billion in 2019, is expected to grow to $90.1 billion in 2025. However, current products on the market are limited in scope, in that they are designed to treat water that is already relatively low in salinity, and do not account for lead contamination or other technical challenges. A better solution is required to ensure access to clean and safe drinking water in the face of water shortages. 

    A team led by Jongyoon Han, professor of biological engineering and electrical engineering at MIT, has developed a portable desalination unit that utilizes an ion concentration polarization process. The compact and lightweight unit has the ability to remove dissolved and suspended solids from brackish water at a rate of one liter per hour, both in installed and remote field settings. The unit was featured in an award-winning video in the 2021 J-WAFS World Water Day Video Competition: MIT Research for a Water Secure Future. The team plans to develop the next-generation prototype of the desalination unit alongside a mass-production strategy and business model.

    Converting dairy industry waste into food and feed ingredients

    One of the trendiest foods in the last decade, Greek yogurt, has a hidden dark side: acid whey. This low-pH, liquid by-product of yogurt production has been a growing problem for producers, as untreated disposal of the whey can pose environmental risks due to its high organic content and acidic odor.

    With an estimated 3 million tons of acid whey generated in the United States each year, MIT researchers saw an opportunity to turn waste into a valuable resource for our food systems. Led by the Willard Henry Dow Professor in Chemical Engineering, Gregory Stephanopoulos, and Anthony J. Sinskey, professor of microbiology, the researchers are utilizing metabolic engineering to turn acid whey into carotenoids, the yellow and orange organic pigments found naturally in carrots, autumn leaves, and salmon. The team is hoping that these carotenoids can be utilized as food supplements or feed additives to make the most of what otherwise would have been wasted. More