 Our next presentation will be given by Joe Cornelius, the chief executive officer for Bill and Melinda Gates Agricultural Innovations, which is known as Gates Ag 1. The title of his talk is innovations to improve agriculture productivity and sustainability in the face of global climate change. From a Bill and Melinda Gates perspective, I'd like to build on what Don actually set the stage for and as an organization that often calls itself impatient optimists. There are a lot of points of intersection as we think about agriculture and what I'd like to lay out for the next 25 minutes are the challenges, many of which we've discussed over the last two days of the workshop and the opportunities going forward. Alright, so from a historical perspective, agriculture has been an enabler of forest civilization and agriculture, as we know it, is really about domesticating both crops and animals. And over the course of time, the agricultural sector has actually had numerous inflection points. In this particular case, if we look back, going back to Neolithic period, there have been at least three major agricultural revolutions that have occurred during this particular period. One thing that I think is particularly interesting about the timeline or chronology is that we seem to keep budding our heads against the same problems, whether it's population growth, climate, and ultimately it's technology that's actually been a primary driver of our ability to actually move to the next century. The key question for us where we are today is are we going to be able to actually close this gap between now and 2050 and more importantly between now and the end of the 21st century? One chart that actually is pointed to quite regularly as an achievement of the agricultural sector is the significant progress that's been made in the last 75 years and in this particular chart showing Maze in North America. There are comparable charts in Europe for other cereal grains, but I would also challenge that this is not only a success story, it's also a story that's actually been enabled by inexpensive energy, mechanization, fertilizer, and a number of other significant innovations that have actually enabled the growth, but have also created scenarios that now we as a civilization have to address and clean up. The key thing also about this chart is that yields are starting to plateau and across the board all crops are seeing this similar effect. Actually several crops are in a negative year-over-year growth. Corn, which gets the lion's share of the R&D investment from the private sector, is growing at a scant one to two percent per year. So the food security is one of the issues that we've touched on that basically we have to increase agricultural productivity by roughly doubling between now and 2050 and at the same time do that without bringing any additional land mass into planting. If we were to just use the current yield curves that were on, that would require our finding a land mass the size of North America to actually be able to satisfy that need. So basically that's not going to happen and we've got to look at agriculture stepping up to be able to close that gap in other ways besides procuring additional land. Next slide. Fresh water is also a significant challenge from an agricultural perspective. 70 percent of the blue water or the potable water that we drink actually goes to agriculture and 40 percent of the land that is being cultivated is currently under irrigation. This is a bank account that we've been drawing down over the last century and basically we have to find a better alternative to current existing farm practice. Next slide. Land use, arguably the most important single greenhouse gas challenge we have, whether it be deforestation or just the cultivation of crop land year over year, we basically have to find better farming practices that allow us to manage this in a more sustainable, sustainable fashion. Next slide. And if we look at the productivity gains that have actually procured to agriculture, it's been at a significant cost to the environment. Several of the speakers previously spoke about hypoxia as an example. Half of the fertilizer we put on the farmland ultimately ends up in fresh waterways and has deleterious effects globally that have to be reversed. And essentially all of us are going to be impacted by climate but no one more severely than those who are trying to farm in Sub-Saharan Africa. Of the 500 plus million farms around the world, disproportionately those that are in Sub-Saharan Africa and Southeast Asia are being severely impacted by a number of different climatic effects, not just drought but also disease and insect pattern shifts that we're seeing on a mega-scale that are having significant implications. Next slide. And of all the sectors that exist at our disposal, agriculture is a pathway to equality for all economies. And this is a particularly important aspect as we think about well-income countries and their ability to actually move to a more sustainable economic model. Next slide. All right. So doom and gloom is over. Let's now change gears and talk about the optimistic. Agriculture is biology. And as a result, it's actually can become a significant contributor to what we're trying to solve here. Genetics are programmable, as Don alluded to in the previous presentation, that like software, we have the capability to actually improve the genetics that we are currently farming. What's said another way is we don't have to play with the deck that we have. Seeds are scalable. All the genetics that we develop actually are very specific to a specific geography. Subsequently, we can customize and deliver those improvements, genetic improvements globally. And carbon is currency to the farm or agricultural system, whether it's carbon and grain or carbon and soil. At the end of the day, it's monetized. Subsequently, it has an economic incentive that's aligned with the objectives that we're trying to achieve. Next slide. The Academy actually published a report that came out this year, and it was the workshop was conducted last year that outlined fields of opportunity from an agricultural research perspective. And these break down into a number of different buckets, such as efficiency, sustainability, and resiliency. Increasing nutrient use, reducing soil loss, mobilizing genetic diversity are very much in that high efficiency bucket. Optimizing water use, improving food and animal genetics, early and rapid detection, as well as reducing food loss. These are all low hanging fruit in the context from a research perspective that we do have tools and paths or particular strategies that can allow us to actually impact these areas. Next slide. What I'd like to talk about in the context of natural climate solutions from an agricultural innovations perspective, that there are two particular inflections that we can actually focus on in the near mid term that actually have long term consequences. One is precision breeding and the other is knowledge farming. Two very overused terms, but two that are quite important going forward. First, I'll talk about precision breeding. Breeding is very inefficient. It's basically just like photosynthesis that Don talked about, that inefficiency gets amplified by the fact it takes us another eight to 12 years, even when we find a or discover genes of interest to be able to move that into a commercial context. The process of crossing parents, conducting field evaluations, and ultimately translate into commercial hybrids and varieties is a very slow, methodic process. And what particularly slows it down is the fact that we truly need to understand the genotype by environment by management attributes as relates to crop breeding. Next slide. So on the left, a figure that most of you are probably familiar with, Norman Borlaug, who has been very, who is very much involved on the green revolution side. What I want to talk about is what Mendel started several centuries ago, and that was our understanding of breeding. And what are the variables that go into breeding that actually allow us to realize genetic gain. And in this particular context, talking about genetic gain as a phenotype of interest, and what we're looking for are the outliers in a normal distribution. This is a very simplified version of that equation. What I want to highlight in this graphic is the fact that there are several parameters that a breeder is trying to optimize in order to get to the next generation trade. Once they discover a gene, what they want to make sure is that it's heritable, that it actually can be passed down from the parent to its progeny. And it's important to understand how the phenotype in this particular case could be yield, or it could be disease tolerance, or it could be carbon partitioning, how that is influenced by genetics, by environment. And it's a function of how the breeder actually conducts their activity, how much phenotypic variability do they have in their trials, what kind of selection intensity, and what's the length of the cycle that they're running on their breeding. At the end of the day, the clock speed can be affected by our ability to either impact the numerator or the denominator in this particular equation, and actually increase the number of breeding cycles on an annual basis. Next slide. So once a breeder actually is successful in creating a new commercial hybrid or variety, then it moves into the farmer's field. Where the breeder is trying to actually increase genetic gain, the farmer is trying to optimize what the breeder hands them. And the farmer was actually battling with nature on a day-to-day basis. During the course of the year, they're making several hundred critical decisions that any one of which can determine success or failure from productivity standpoint. And certainly, most of those, if not all of those, have significant impacts on sustainability. Next slide. So a quote I came across in nature several years ago, which just resonated with me, was that science is informed by what is possible to measure, and it takes great leap forward when we measure something new. Next slide. And fortunately, we are all living in this age of convergence. And the question is, can we actually integrate these technologies, biology, genomics, engineering, data analytics, mathematics into the fourth agricultural revolution? Next slide. So Dom touched on just one aspect of this innovation frontier, which is biotechnology. We saw an explosion of activity in genomics at the turn of this century. We've also seen significant other omics breakthroughs that have occurred. And we now actually have the means to actually be able to discover genes and traits that actually impact a number of pathways, one of which is carbon fixing photosynthesis that was discussed by Dom. We've also had genes and traits that affect carbon assimilation and transport, which can actually enable us to think about ways to optimize root chute partitioning differently than we've had before. The ability to identify new genes that actually have greater recalcitrance, which have impact on soil carbon. Genes that potentially affect water use efficiency, as well as self fertilizing plants. So we have multiple strategies that we can actually address that would actually contribute toward our ability to adapt and mitigate a number of climatic factors that we're facing. And all of this, we know, has to be done in addition to being able to make the plants more abiotic and biotic stress tolerant as a result of the challenges that we're facing. The good news is that we've seen productivity in the space. This was an article that was actually published in the Wall Street Journal just several weeks ago, August 12th, the robot producing the crops of the future. This was a test bed that was developed by the Department of Energy along with USDA and NSF several years ago. And the primary objective of this was to actually create a test bed that would allow us to conduct high throughput testing of genotype by phenotype by environmental conditions. It's on a site that's approximately two hectares. It's in the desert of Arizona, so it allows us to actually phenotype on a 12-month basis. In addition to its work on developing biology discovery efforts, it also provides very high resolution data sets that can actually be innovated around. And it also provides us with the capability to bring in new sensor modalities and test those on crops as we think about developing high throughput capabilities. It also has a place in our ground truthing, our satellite network, and potentially creating a better informed algorithms that can be used in other deployment vehicles like drones and small robots. Next slide. Just a short video. I don't know if you can click that to start. So this is showing the the scandalizer that's used in the field. It weighs approximately, I'm not sure if it was 20 tons or 30 tons, but it essentially has every sensor that we currently are that's known to civilization and provides us with an opportunity to be able to identify sensors and down select so that we can then then take those sensors and use them in more deployable formats. It's a system that basically runs 24-7 and it's a collaboration between the public and private sector. The end game is for us to get to small deployable units like this or drones that can actually be scalable or low cost and can provide farmers with information about crop stand, insect and disease pressure, soil moisture, all the other parameters that actually enable knowledge farming and allow them to actually be much more responsible with the resources that they put into their agricultural platforms. So as we think about the integration of physical and life sciences, you can go through the next couple of clicks to fill out the slide. We see things, innovations on the physical science side around sensing, power, analytics and communications that are directly attributable to biology. On the sensing front, microclimate sensors, metabolic, chemical, nutrient, biologic are all examples of things that are currently in the process of being atomized and deployed. We also see new technologies like acoustic that for example can pick up insect feeding or anomaly detection using advanced data analytics where we can actually identify disruptions in a field using satellite imagery long before human eye or even robotics can do on a field scale. New power systems that basically are low power. DARPA had a program called Zero Power as an example. There's energy harvesting which has been around for quite some time. The question is, can we make these systems biodegradable and can we also find ways that actually leverage the existing latency that exists within the plants themselves? From an analytics perspective, building state-of-the-art data sets that allow us to actually create much better algorithms using machine learning and also building out the models more providing the models with more informed information so that we actually have better predictive platforms. And then from a communication standpoint, remember most of agriculture is in very remote sites so our ability to actually be able to create new communication capabilities that will operate any place in the world is of particular interest in our fields of opportunity that are currently under development. And if we look at computing capacity now getting down to the size of a grain of sand. All right, next slide. For the last 10,000 years we've only bred for what we can see which means that we've pretty much ignored anything below the soil surface. And this is a particular example showing rooting depth that has been totally ignored by breeders for since the beginning of time. Next slide. Taking technologies that are coming from aerospace as well as military and oil drilling as an examples and medicine, we're actually repurposing those technologies that allow us to actually be able to measure root growth as well as soil physical characteristics real time. So rather than wait having to wait 10 years before we've got measurable data being able to do things on a much shorter time horizon. And these are just two examples of using X-ray root imaging or using thermoacrystic imaging to actually be able to allow us to make new measurements that can speed up the breeding process but also can potentially become new tools that actually allow farming to be more sustainable. Next slide. So at the end of the day what we're asking for is the integration of biology, engineering and data science. In this particular domain, there are significant advancements occurring in each one of these nodes, genomics, phenomics, sensors, robotics, data analytics. But the integration of these technologies, that's where we create the transformative impact that allows us to amplify crop productivity, climate resilience, and environmental sustainability. And these are efforts that are beginning to ramp up. It's certainly areas where we need to invest more. And now we're actually getting into the domain of systems research that enables us to actually be able to harness all of the elements that are absolutely essential for us to be able to deliver goods and services that have a potential to affect climate solutions. And one thing that we've all learned is that science leads markets follow. This is an example of the ag funders 2020 Farm Tech Report that came out earlier this year, characterizing the 2019 ag tech funding approximately $5 billion that went across a number of different platforms. This represents startups in ag biotechnology, novel farm systems, farm management, bioenergy, et cetera. So the capital is there in the marketplace. The imperative is for us as scientists, researchers, policymakers to actually determine what's the appropriate path for us to actually be able to affect the change. I kind of look at these technologies as being the first generation of that fourth agricultural revolution that we're capable of delivering. Next slide. So there's a lot of opportunity and there are a lot of tools out there and I think many of us here on this call today are in a position to actually be able to affect that change. Last slide. A short quote from Martin Luther King, great sciences, compassionate science. Thank you. Awesome. Excellent. Thank you so much, Joe. That was wonderful. I can see the questions pouring in. So I would like to turn it over to Jenny to start the Q&A. Thank you, Sarah. And thank you, Joe. Wonderful talk. I'm really enjoying all this plant biology talk. So we have several questions in from the audience members. We'll start with the Davy Parker. Davy, would you like to unmute yourself when you're able to and ask your question? I'll say the omics technologies have been around for quite a while now and he was showing that the cycle time breeding hasn't decreased. So what's missing? I mean, there are new innovations coming through, but the basic omics technologies have not fundamentally changed. So one of the things that's actually been missing is that, as you know, biology is noisy and it's very, very difficult for breeders to actually be able to separate the actual desired phenotype from a lot of the environmental noise that occurs in this particular space. There have been a lot of attempts to actually be able to address that by just increasing throughput on the front end, such as on the genetics and throughput. But the environment is such a compounding factor and the plasticity of the plants has actually made it much more difficult for us to actually be able to again be able to get our arms wrapped around some of that particular noise within the system. And the hope anyway at this particular stage is that with the new sensing technologies and the new data analytics capabilities that we can actually become much more astute at being able to identify those needles in the haystack. The other aspect I would touch on also is where the funding has gone traditionally. So a lion's share of the funding, at least on the private sector side, has gone into a very few number of crops. So the focus has been on a very narrow bandwidth of particular endpoints that has also limited our ability to actually get more of these innovations into a broader array of food crops. Thank you. Well, if we can, I'd like to squeeze in one more question from Francesca Cotrufo. Francesca, would you like to unmute yourself and ask a question? Hi, Joe. It was a very interesting presentation. One thing I see is that currently we are addressing this huge problem on two parallel rails, if you want. One is this high tech high precision farming that you have mentioned. And the other is the regenerative farming that the farmers are actually putting in place and companies like General Mills, McDonald's, Indigo are supporting with their initiatives. And even in departments, like I have some project which we're doing high tech and I have other projects with I think what we're doing with Gen and I don't see those two crossing, which, you know, I didn't see the world ecology on your slide. And I really think that that's where we can make the difference that the only biotech is sorry to say, but it's one of the problems that brought us here. And we need to integrate that with the ecology to make sure that we don't get into an unknown problem in a century. Excellent point, Francesca. And I agree with you completely. I use biotech in the context that it's a tool that allows us to actually be able to discover and advance genes and traits that are in the natural gene pool as well. So whether it's through conventional means or through gene editing, we're talking about a particular capability to identify those genes and traits and then be able to move them in the most expedient format. And to your point, there's 550 million farmers globally, 500 of them are farming less than two hectares. So if we're going to have an impact, we have to develop technologies that are scalable to those 500 million.