Nov. 12, 2020 – U.S. Research & Development Live Session

Transcript

Jason Sparks:

Welcome, and thank you for being with us. This is the last day of our Syngenta Media Summit. Maybe I'm little biased, but I like to say we're saving the best for last, to get a chance to hear from our Seeds R&D team. It's also, well, actually a nice milestone for Syngenta today, is the 20th anniversary for Syngenta. So our company is celebrating that really exciting moment for the last 20 years, and you think, 20 years of innovation, 20 years of working with farmers. So really nice moment that ties in with our final day of the summit. My name is Jason Sparks, I work in global communications for our seeds business, and you're going to hear from three of our members of the seeds R&D community, Gusui Wu, who's head of our global seeds research, Laura Potter, who's head of analytics and data science and Warren Kruger, who is head of North American seeds development. They'll each present some slides, and at the end, we'll have time for your questions. So I'm sure you'll have some, as you're going along. As you're probably used to throughout the summit, there's the Q&A function where you could submit questions as we go along, at the end. I'll be happy to answer those questions at the end of the presentation. So I'm going to now turn it over to Gusui to get us started.

Gusui Wu:

Thanks Jason. Good morning everyone, greetings from RTP North Carolina. My name is Gusui Wu, I head global seeds research for Syngenta. It is really exciting to have you join us today. We are all very excited about where we are with R&D pipeline, with the innovations that are happening at Syngenta. The three of us hopefully will give you a quick view of what's coming in next decade and what we're working on today. I'm going to be focusing my comments on biotech research. Go ahead, advance to the next slide Jason. So Syngenta has very strong commitments in R&D, because we believe innovation is our future, and the challenges farmers face, and the challenges of environment and climate change can only be solved with innovation. So Syngenta invests $1.7 billion a year into R&D, a major part of that is in .

As you all know, biotechnology has had a very positive impact on , whether it's at farm level, whether it's on product development in ag companies. And we continue to believe biotechnology will play a important role in the future. Syngenta R&D has a global footprint, and we have a scale that is completely global with diverse talents, our R&D staff. And we have industry leading traits, technologies, currently serving our customers, that is bringing the unique germplasm and the biotech traits together and being very competitive in the marketplace. Looking into the future, transgenic technology will be accelerated by the new innovation that is happening in biotech area, such as genome editing, which I'll touch upon little bit later in the talk.

And one other point I want to make is that, we believe collaboration is a very important part of how we conduct R&D, whether it's collaboration within a company or collaborating with external partners, and collaborating with farmers at the farm level. And you will hear some of those activities we have from Laura and from Warren. Next slide. Syngenta has always had a big presence for its R&D in North America. This picture shows you our innovation center located in Research Triangle Park, North Carolina, where I'm based. RTP is our largest biotech innovation center, where we invested over $160 million in a state of art facility. It consists of laboratories, greenhouses and offices. It currently staffs more than 500 employees. Majority of them are PhD scientists. Next slide.

Syngenta was one of the earliest companies in ag industry to develop biotech technology traits for important . Syngenta was the first in fact to launch a GMO corn for insect resistance, and over the last, more than two decades, we have a strong track record, in terms of delivering technology traits that brings true benefit to the farmers, in corn, in soybean and other crops. And in recent years, we have invested significantly in new technologies like genome editing. Just recently, the HI-Edit technology that were patented by Syngenta is example of it. It is a proprietary technology that significantly accelerate product development cycle. Next slide.

Today, Syngenta has the industry leading insect control transgenic traits on the marketplace. And in fact, in terms of lepidopteran is a control, particularly for armyworm. MIR162, Agrisure Viptera® trait, is the only fully functioning trait today, in terms of fall armyworm control. And that is being out licensed to the whole industry. In R&D, we are currently working on the next generation traits, with new modes of action and multiple modes of action to address the lepidopteran insect challenges, which is a very big challenge for both North and South American farmers, in corn, as well as in soybeans. And it has a potential peak sale at half a billion dollars. We expect to launch the next generation traits later this decade. We have a broad and a strong pipeline with robust traits to continue to deliver innovative solutions, inside control for growers. Next.

In addition to input traits, Syngenta also leads the industry in terms of offering output traits, Enogen® corn is example. Enogen corn is an amylase technology, initially was developed for production. And in recent years, we've discovered that Enogen corn actually increases feed efficiency in beef and the dairy production for over 5%. And that this is significant in that it significantly improves sustainability and reduce waste. And we are currently conducting trials for pigs and the poultry. We believe it will bring the similar kind of efficiency gain for those livestock. And we are deregulating stacks of Enogen corn combined with insect traits for North America and other markets. Next slide.

And herbicide tolerance, certainly is a valuable trait. And currently our farmers are facing a lot of choices and all lot of challenges in terms of dealing with complexity of weed control. And today, Syngenta offers the choices of different platforms of weed control to growers. In the R&D, we are pursuing a new generation of weed control, taking advantage of the new mode of action, , that is developed in our protection pipeline. New herbicides that are coming

along within the next decade, and we want to co-develop the traits simultaneously, so we can bring additional weed control options, particularly for resistant weeds to current herbicides. Next slide.

So in addition to transgenic traits, which is the next generation new mode of action for both insect and herbicide tolerance, quality traits, we believe gene editing technology will have a big impact in the years to come. Gene editing technology brings a lot of potential for new traits and for new breeding technologies, which will accelerate the product development process with additional value added traits for growers. And it has an advantage of being flexible, being more precise, and with lighter regulatory burden and timeline. So we can bring the innovations to the farm level faster. Next slide.

Here, to give you an example of the kind of innovations that the gene editing can bring. And we are working on a tomato trait, which is simple editing of a couple of genes in each tomato, that will simultaneously create long shelf life, as well as resistance to multiple diseases. This demonstrates the power of gene editing, and we are planning to launch this trait in the next few years. Next slide. And finally, example of why we believe genome editing accelerate product development. Here's a cartoon picture to illustrate the proprietary technology, Syngenta just patented last year, called HI-Edit, which stands for haploid induction and editing. What it is, is that it can skip many generations of back crossing in product development process, to introgress any traits into elite hybrids or elite germplasm. It reduces cycle time and increase of ability to deploy traits into more elite hybrids and high yielding products.

And the typical traditional trait introgression which every transgenic technology needs is to a serious multi-generation back crossing in order to incorporate a transgenic trait or any trait into a finished product, which is a costly and time consuming process today. Today, every company invest tens of millions dollars a year in that process. HI-Edit technology essentially skip all that and you can do that in one step. So this is a very exciting technology, we think it will have significant implications in terms of how we develop products in the future. Next slide.

And in conclusion, Syngenta Seeds provides our customer with high value traits developed through biotechnology. Currently, we offer very competitive traits, like Viptera and [Agrisure Duracade®] for insect control. And we have choices of weed management, different platforms offered in soybean for our growers. R&D is working on a robust pipeline of next generation traits, because we cannot rest on the current traits on the market. We need to renew and to replace the current traits with the next generation, representing new modes of action and multiple modes of action, whether it's insect control or herbicide tolerance. And genome editing is a breakthrough technology we believe will have significant impact on traits as well as our breeding process. And the examples are double haploids technologies we are investing in, as well as HI-Edit for trait deployment. Thank you. I'll perhaps take questions later in Q&A. With that, I'll hand it to Warren.

Warren Kruger:

Thank you Gusui. And good morning everybody. My name is Warren Kruger, and I lead the North America seeds development program here at Syngenta. This morning, I'm excited and thrilled to be telling you some of the investments that we are making to enhance the product development pipeline in North America as we continue to deliver on our commitments to our farmer customers, as we develop better products fit with farmers' needs. We can go to the next slide.

So this slide is really just to firstly align with you about how Syngenta's R&D parties fit with the needs of North America farmers, and are aligned to address those needs. Our North America seeds development teams work with elite and germplasm, and the best trait stacks to deliver products to the market, that offer farmers competitive options in yield and agronomics, insect and weed control, disease and abiotic stress. And these are the North stars that direct our breeding programs and product development programs for our focus in product development. Next slide, please.

We are in the midst of a substantial investment effort in North America. The investments support key sites as indicated on the slide and these key sites or technology centers in turn support many field trial locations or field testing locations throughout the and Canada as well. We have invested in current and planned capabilities that enhance our product development and deployment of new products, as well as in new ways of working. Some of the key sites are shown here. We have eight key sites spanning all of North America, and they are indicated here on the slide. The investments in capabilities in these core sites improve the delivery of new trait and germplasm products. And by focusing on core sites for a lot of our operations, we move away from the old model where each individual site was doing smaller process and processing to a more centralized model, where in the scale of the operations improve.

And this enables a lot of automation and process improvement, to make our processes that happen behind the scenes, prior to field testing, far more efficacious. This work is behind the scenes work that happens in the back when we are processing seed, packaging seed, so that we can more effectively distribute it to many of our trawling locations supported by these key sites. On the next slide, we see another example of the benefits of investing in centralization, as well as new ways of working. Over on the left-hand side of the slide, is an example of the corn and soybean trait accelerator facilities. These capabilities are located at core sites that support product development across all of North America. That is to say the work that they are doing here is work that can be centralized, taken to scale and automated, and then deployed for testing throughout North America, the US and Canada.

Investments are also being made in new ways of working. For example, on the right-hand side of the slide, we are highlighting our new sites that is under development in Malta, Illinois. This is a really cool opportunity wherein we're going to have cross-functional teams from across R&D who will be working on real time problems alongside our customer experience center. An exciting opportunity is that we are bringing new teams together in new ways of working, and

also bringing them closer to the customer, highlighting our R&D focus and connection with the customer. On the next slide, we are also taking our investment opportunity beyond just the sites. So as the sites develop greater efficiency in how we process, that enables us to take more care on the actual equipment that does the field trialing.

We are focusing in new generations of equipment and telemetry as shown in the middle panel on the slide. This enables us to monitor our fleet of planters and combines and make real-time adjustment both during the planting and harvest season. And this ensures that we can run our operations and get optimal data and quality data that fit much better with the operations that are happening out there with our farmers. If you can advance the slide. Yeah, thank you Jason.

By doing this, we are able to ensure that we are collecting the appropriate data and bringing together all of the data from both environmental and genetics information, that allows us to better characterize and place products by divvying up that information across these various data layers. If you can go to the next slide.

In summary, we have committed over $400 million into spending in North America R&D, to address farmers' needs. That investment is both in infrastructure and capabilities that happen to support and enhance our operations, both behind the scenes as well as in our field trialing and testing. The result of that, is that we are generating new types of data faster and with a higher level of precision, that helps us improve the speed of product development, and also enhances the precision of our product characterization and recommendation. Thank you. And with that, I'll hand it off to Laura.

Laura Potter:

Thank you Warren. And before we jump to the next slide, I just want to say that I'm really excited to be here today, to share our story of how we're using advanced analytics to drive innovation for our product pipeline. And I'm really proud to speak on behalf of our analytics and data sciences team. We have a diverse mix of expertise and experience, including deep agricultural and agronomic knowledge, but also bringing in insights from outside agriculture in new ways to create innovation. The common thread is the passion to translate that innovative science into solutions that are going to help farmers feed our growing population. Next slide.

So for us, what that means is we need to help farmers solve the big challenges that they're facing in this ever-changing world. Farmers need to be maximizing their ROI potential year over year, while all these changes happening. They need to produce stable yields to get to that ROI. While at the same time, there's changes happening in consumer preference, an evolution of pests and introduction of resistance happening, changes in the market and economics, and also climate change. And even just the seasonal patterns of weather that are going to impact yield. So for us as an R&D organization, our challenge is to create winning reliable genetics that are going to perform consistently, even though the conditions on the farm are constantly changing.

On the next slide, I'll show you a little bit about one of our key focus areas, and that is really understanding the farmer's environment, to help inform our product development.

So if you think about the conditions on a farm, you've got a very complex interaction of weather, the soil, and also the growing practices over time. So really what you have is these farm environments are speaking different languages across the years. So for any of you who have ever tried to learn a new language, or would like to, let me take you back 30, 40 years and think about how you would go about learning a new language. It would be books and in-person interaction. So you might have a language dictionary, you might have a conversation guide book, a textbook. If you're lucky, you're in a class with a teacher and others who can speak that language with you. And if you're really lucky, you could actually immerse yourself in an environment where that language was the primary language that was spoken. That was pretty much, those were your options 30, 40 years ago.

Fast forward to today, now, we don't even recognize just how much the technology is advanced necessarily because we're using it every day. We can instantly translate web pages into different languages, online documents. We can speak into our phone and have it instantly translate our voice and actually speak out loud in different languages. And I was playing around with that app with my kids last night, just to test it out. This technology is at our fingertips right now. My husband is learning Spanish, chatting with his phone while he rides the exercise bike. So just thinking about all the changes that have happened, all the technology underneath that, machine learning capabilities and computational power, access to data, we do the same thing in our space. We use data and analytics and different kinds of technology to auto detect and auto translate those languages that are being spoken on the farm, to help our product pipeline produce better products that are going to meet farmers needs and to make them faster.

So in the example on the right, this is just a mock up example to kind of bring this example to life. So if you think about a particular farm location and you look over time, for example, in the US, 2012 was a major drought year that impacted most areas of the corn belt. You're going to have those different patterns that occur over time, and as you look at across the years, you can analyze that and end up coming with kind of a registry of what are the languages that are being spoken across the years and how often those occur. So in these little example pie chart, are meant to represent how often the different languages of the farm environments are being spoken at those location, across the years, it's going to vary. This tells us the pattern of what languages we need to be able to speak on those farms.

So on the next slide, it's not just enough to be able to detect those languages and to translate them. That's only the first step, we have to design, select and place the right genetics that are not just going to speak the languages of those farm environments, but they need to be fluent, and they need to be ready to adapt whatever language comes into play, knowing that in some cases those languages might change in the middle of the season if there's a big devastating storm or other types of events that would influence the impact on the yield. So our analytics takes advantage of this information. We bring together genetics by environment interactions, to

deliver fluent genetics, that are going to create winning stories for farmers through strong performance on their farm. Next slide.

And this just doesn't happen. We have to pull all of this together, and it starts with having the right kinds of data at the right kinds of scales, the right volumes and the right resolutions. So let's go back to our language example. If you think about a computer algorithm and how you would go about teaching it to learn a new language, they also need the right kind of data. So if you just fed a language dictionary into a computer algorithm, you're going to miss out on all the richness of sentences and ideas and conversations. It's just going to be a collection of words and definitions. So that's not going to work. You could feed an algorithm, the complete works of Dr. Seuss. That's got sentences in it, and phrases and ideas, might be a really fun language, but probably isn't going to be useful to use to be able to speak English fluently.

Also a random internet download, probably isn't going to do the job. So just as in other areas of machine learning, algorithms are trained using what are called canonical datasets. You have to get the right mix, in this case, of words, sentences, conversations, ideas, so the computer can learn that language and be fluid. We take the same approach in breeding analytics. We have our own canonical datasets, which are the right mix of R&D trial data, experimental data, commercial data, and public data, brought together in just the right way so that we can train our algorithms. And by training our algorithms with these canonical datasets, we then have the predictive power to be able to translate that data and decisions all up and down our pipeline, including some of the examples like Gusui and Warren mentioned, and that enables us to deliver winning fluent genetics to the farmers.

So on the next slide, let's look at an example of our analytics in action, and that is predicting the performance of corn hybrids in untested environments. So we need to know for given hybrid, where is it going to be fluent? Where is it going to perform well in environments where it has never been grown? So we start out, step one, we have the data, we have data for that particular hybrid and other environments, we would have data from similar genetics, either similar hybrids or inbred parents, and we would have data on their performance in different environments. So what we do on the left is, we take that data and we translate all of those different farm environments. We detect the languages, we translate them, and we cluster on the genetics by environment patterns, to determine which genetics are speaking which languages and how well they speak that. Step two, we then predict which genetics are going to be fluent in the corresponding environments. And by doing that, our advanced analytics have achieved up to a 30% greater predictive accuracy than the standard GxE approaches.

So again, this gives us more predictive power to say with greater certainty where particular genetics are going to be fluent, in the different languages of the farms, so we can pick and place the genetics in the right locations. So to summarize, on the next slide, thank you. It all goes back to the farm. It goes back to the farmer and the local environment, on their farm that he or she are dealing with. There's ever changing conditions all around them, and the farmers need reliable genetics to continue to give them that reliable performance so they can maximize their

ROI. There's this rich dynamic tapestry of language that is constantly changing based on the changes that are happening with the weather and the climate conditions. We deeply understand, and we speak these languages. We can detect these languages, we can translate them, that helps us characterize the different environments and understand the environments that our farmers are facing, where we need to be able to produce genetics that are going to be successful.

And then we use our analytics, to leverage the genetic diversity that we have in our germplasm and create the right genetic variation, through breeding and breeding technologies, to design fluent genetics that will outperform in these specific environments. And by doing that, we help enable, combined with all the technologies and capabilities that Gusui and Warren have touched on, we bring all of that together to build the winning genetics that are going to help enhance ROI and create those winning stories for farmers. Thank you.

Jason Sparks:

Thank you Laura, Warren, and Gusui, for those presentation. What's happening on the R&D side right now is really exciting. This will end the presentation piece of the session. We're going to move now to a live Q&A. I'm going to stop sharing the screen so that you can better see the presenters when they're answering questions. Again, you have the button there at the bottom of your Zoom screen, where you can submit any questions you have. We already have a number of questions. I'm going to jump into those. First, this will go to Gusui. Julia, she asked about, can you explain more about what the HI-Edit technology is, and give an example of how it's being used right now?

Gusui Wu:

Certainly. I didn't have the time to get too technical about the technology. It’s really exciting technology. It's a technology that can be used for any crop that has a haploid or hybrid system. Corn is a prime example of it. And what it is, is that you can induce haploid lines in your inbred development process, which is really important in hybrid breeding. And this technology take advantage of gene editing, essentially combine that in that haploid induction process or double haploid development process, where one parent will contain all of the components that's needed to do gene editing. You do one cross of that line, the haploid induction line with any leads, inbred line that you want to use. The result will be a haploid progeny that will contain the trait, whether it's by editing or transgenic or any other modification we want to make.

And the beauty of that is, that progeny hybrid line is free of any . It will not have any footprint from the editing. It will just look at the original elite inbred in a haploid state, but containing the trait. So you imagine that, any hybrid producers would need to tens of hundreds of hybrids a year. And in order to do that, today, we do a lot of crosses and characterizations in order to do that. And this technology allows you to do that in one step, and in multiple inbred

lines. So that's the efficiency and that's the precision. Is going to have a huge impact in how we do hybrid product development in the future.

Jason Sparks:

Thank you Gusui. Laura, and we go back to you, you talked a lot about the language analogy in your presentation, and this is from Tom here. Could you expand a little more on what you mean by the cornfield speaking a language? Maybe some specific factors that you're looking at.

Laura Potter:

Yeah, absolutely. It comes down to the environmental interactions between the weather and the soil and also the growing practices and when those happen. So if you have a severe drought event, that's severe enough, it's going to have an impact on yield no matter when it happens. But other kinds of fluctuations, depending on when they happen in the crop cycle, you could have an event that happens right before flowering, that could be devastating, and you could have another event that happens towards the end of grain field, that really has no impact on yield at all. So what we have to do is, of all the thousands of different combinations of variables that come from the weather, whether that's radiation, whether it's humidity, whether it's temperature, precipitation, and then also the characteristics of the soil.

Depending on your soil characteristics, if you have a really strong rain, of course, that's going to affect the way the water flows through the field and how that then gets received by the plant. So what we do is, we basically break down all of these interactions that are happening and use our analytics to understand which ones are the most impactful on the plant, which ones contribute to the key stresses that are then going to bring down yield. So then we can break that out and understand what that impact on yield is going to look like when you get those patterns over years. So then you have more predictive power to be able to tell what's going to happen next, if you get a particular environment.

Jason Sparks:

Thank you Laura. For this next question from Frank, I think Warren can touch a little bit on this. With coming water shortages and climate change, how do we grow high corn and soybean field with hybrids varieties that need less water? Maybe you could touch a little bit on what's happening on the breeding side right now.

Warren Kruger:

Yeah, I know, that's a great question. So at the end of the day, as Laura just articulated, knowledge of the environment and in particular how the germplasm that we're developing along with the traits we have, perform in those environments. And so the key actually is regularly having a robust and accurate field trialing or field testing operation. This is one of the key

outcomes from our investment strategy, is that by centralizing some of the operations outside of individual sites and into key sites, that enables our trialing locations to expand and be more comprehensive in how we sample and test, in the appropriate environments. So some of this is accomplished by actual validating in the field and testing in the field in a very expensive way.

Warren Kruger:

And this is just sampling the many, many environments that are out there, making sure our testing and trialing network is appropriately distributed to sample all those changing environments. We also take advantage of what we called our managed stress environments, and these are highly localized, highly specialized environments, where we can manage stress in this case, water stress, or the amount of water we apply to the crops to see the response. So it's really a combination of the two. By optimizing our operations, we are able to expand our testing network to make sure our corn and soybean are performing in those low water stress environments, and combining that with also managed stress environments, that also within our trialing network.

Jason Sparks:

Thank you Warren. We come back to Gusui here, we have a couple of questions on gene editing, I think. And before the question, it's probably good to know that we've obviously seen this year a lot more mainstream awareness and interest in gene editing. We had the Nobel Prize in Chemistry, that was focused around CRISPR technology. So some of the questions are, Margy asked, "Specific to row crops, is Syngenta targeting gene editing in corn and soybeans first for a product line?"

Gusui Wu:

Yeah. Before I address that question, let me just make a couple of comments of gene editing. Gene editing technology is probably the most significant developments in the last decade, in the space of . It's a technology that's going to have significant impact in multiple space, human therapeutics, industrial production, of course agriculture and crop improvement. It's very much like in the early '80s when transgenic technology was a reality, the scientists realizing. And gene editing certainly has the potential to have the similar impact, perhaps even more than transgenic technology. And in terms of our current focus, we are applying gene editing technology in top six crops that we're working on. Corn and soybean, certainly are among the among them. We're also working on projects that are targeting crops like , tomato, sunflower, wheat. So those major crops where we have multiple projects in those crops.

Jason Sparks:

Great. And another follow up question on gene editing, how does Europe’s stance on gene editing, their current stance, impact the future of your work in HI-Edit and other tools? And this is from Willie, can this issue be overcome?

Gusui Wu:

Yeah. Thank you for the question. We have been encouraged to see several countries that moved in a positive way in terms you viewing the technology and the coming up with a regulatory framework for gene editing technology. Countries like US, Brazil, Argentina and Japan have come out with clear regulatory framework, treating gene editing technology as a new innovation and they're regulating it differently than GM technology. Europe, when the other way with the Court of Justice ruling from EU, and certainly that is a step back for the industry. That ruling not only does not make sense from science perspective, how we should look at gene editing technology, it also has many challenges from a practical sense, how you regulate that. One example, many of the products gene editing will produce will be indistinguishable from a genetic standpoint from the natural varieties or hybrids. Therefore, you cannot detect, you cannot trace unlike transgenic technology.

So therefore the current framework used in EU for GM regulation cannot be applied to gene editing. With that said, we have been involved in discussions with the regulators in EU and working with industry partners. We have seen significant positive signs and potential movements in terms of having a more science-based regulatory framework for gene editing. Several member countries in EU has come out with different positions and we expect there will be some positive development in that space, but we’re actively working on that. I do believe ultimately it can be overcome.

Jason Sparks:

Thank you Gusui. We had one quick follow up from Julia. She asks about the hybrids created by HI-Edit technology, are they considered GMO?

Gusui Wu:

Yeah, the answer is no, unless you're using HI-Edit to try to move a transgenic trait from one line to another. But if you are just doing editing or deploying a natural change into different lines, the end result will be GMO free, so to speak.

Jason Sparks:

Great. Thank you for clarifying that. We had a question about, looking at the next technological advancements, what we're excited about over the coming five, 10, 15 years. Maybe Laura you can start, something that your team is excited about as you look to the future, and something Gusui and Warren can chime in, as well.

Laura Potter:

Yeah, I'm really excited about satellite technology. There's a lot that we can do with drones right now, and other kinds of sensors, but as the satellite technology continues to improve, we get higher and higher resolution images, and then the ability to have different kinds of spectral images coming in as well. It gives us the chance to be able to measure phenotypes at a larger scale and a deeper scale in ways that we can't do right now. And in addition to that, I think another area that's really exciting is in the weather space. If we could predict in advance what the weather is going to look like, even a few months out, we can then start auto detecting and auto translating those languages during the season, and that's going to help us run different scenarios, to be able to plan out which genetics we want to design to be fluent in the right languages. So that's another area that we keep an eye on. And as that improves, that's just going to help our data and our analytics.

Warren Kruger:

Yeah. Jason, I can add to that. I think in the general space of what we call phenotyping or trialing, when we think about sensors and sensor technology. So I like Laura's point on satellites, but even on terra firma, and measuring to a high precision through soil sensors, what's going on in the farm. As well as coupled with automation, both in where we are, but even in the general equipment space, out there in industry, new approaches to automation, to planting. You see a lot of automated tractors out there. These are just really exciting opportunities to enhance agriculture output and new ways of farming. So these are all very exciting opportunities that I think about going forward.

Gusui Wu:

Yeah, I totally agree with Laura's and Warren's comments. My build would be maybe a couple of things. I'm really excited about our trait pipeline and the investment that we have been making. We are seeing a robust pipeline that is advancing at a very fast pace, and there will be next generation traits that will really help farmers address some of the big challenges currently have, either with current traits or new traits. So that's one, the other is the convergence of different science and technologies that will help us in terms of how we do R&D differently. Laura talked about the data and the data analytics, Warren talked about the field trials, so phenotyping capabilities, how we use technologies in our breeding process. And even biotech is converging with breeding, HI-Edit is one example of it. There will be, I'm sure a number of new innovations happening in this converging area of different technologies and the science disciplines.

Jason Sparks:

Thank you Gusui. And I'm going to stay with you here. We had a question from Frank come in, about, what's being done research wise in developing a stronger wheat genetics program in North America?

Gusui Wu:

Maybe I can start on that, then Warren maybe you can chime in. So Syngenta has invested for about a decade in hybrid wheat technology, and we are very close to launching hybrid wheat technology. Next couple of years, we will be projected, we'll be launching the technology. And we've done that with barley and very successfully, and my expectation is, it's going to have a big impact on how wheat genetics, how wheat breeding will be done in the future, once the hybrid technology come to the scene. And in North America, we are also putting more emphasis on new technology in addition to traditional varietal breeding. Maybe I'll turn that to Warren to make some comments about what we're doing there.

Warren Kruger:

Yeah, thanks. Thanks Gusui. And it is a great question. So I am not going to repeat what Gusui said, he said it really well. Obviously a focus on hybrid wheat I think is the direction we're going, sort of pivoting away from all the varietal approach. So maybe the only thing that's worth adding to what Gusui already said is, one of the advantages of being a global company is that, in North America, we can partner with some of the developments and learnings out of hybrid barley, and also the hybrid wheat focus in Europe.

Warren Kruger:

And so this is one of the opportunities where our scientists, our breeding partners, even across world areas, can actually take advantage of the learnings and knowledge garnered from over in Europe, in terms of some of the learnings for hybrid wheat enablement. So we continue to be focused at, we definitely see it as a step change in wheat performance and something that our teams are looking at, how we launch that in a very targeted way, in the appropriate geographies and regions, where we'll see the greatest benefit. So it is an exciting opportunity as we reimagine essentially how wheat product and performance is going to be, into the future.

Jason Sparks:

Thank you Warren and Gusui. We had a quick follow up there from Juliet. She asked about, can you give us a preview of how the hybrid wheat would be an improvement? That's a good follow up Julia.

Warren Kruger:

Yeah, that is a good follow-up. So obviously one of the benefits of a hybrid or hybridity is, you can take advantage of this concept well established in a crop like corn called heterosis, and that's some technical jargon, maybe you've heard of it. But really what heterosis helps to do, is to improve, you get a better performance of the progeny versus either of the individual parents. And so there's a one plus one equals more than two type of thing, and that's really the benefit of

heterosis. So you get, firstly, an improvement in overall yield, and then some other benefits, where you get greater uniformity and better agronomic source stability around having a hybrid product. So just in brief, it's really around improving heterosis versus just selling a fully inbred variety.

Jason Sparks:

Thank you, Warren. Lynn brought a question in on corn hybrids and right now what we're developing and how that's marketed or sold in other countries at this time.

Warren Kruger:

Is that for me?

Jason Sparks:

I think yeah, it could be you or maybe Gusui could touch on the research. So I know there's still a lot of work being done there.

Warren Kruger:

Okay. Yeah, it's not very often if at all that individual hybrids are developed in one country, for example, in North America, are being sold in other countries. With that said, there is a component of targeted germplasm exchange. So within a hybrid, I think Gusui may have touched on this earlier, and hybrid is made up of individual inbreds, and so they can be important traits that we can take advantage of in other world areas that may be bringing embedded disease resistance, for example, is, is one that's pretty well known. Where, in one parent of a hybrid connect, she contributes significantly to a hybrid product in another country. But given the geographic and environmental differences, it's not very often that a hybrid is sold. So I think it's more about how the parents of a hybrid can be leveraged and utilized in a constructive germplasm strategy, that way we see benefits that kind of underlines that question.

Jason Sparks:

Great. Thank you Warren. Back to gene editing, so Gusui, you talked a lot about what gene editing can do, the benefits of it. Are there any areas where you feel gene editing cannot do or has limitations? That's from Pamela.

Gusui Wu:

Great question, Pamela. So gene editing certainly we're all, as a technology, we're very excited about. As I said, I think that these are early days about the technology. Like I said, in the '80s of transgenic technology, where we certainly realized the potential. I think that we're still learning about additional potential, additional opportunities that technology can offer, as well as perhaps

limitations. And working in R&D, you always are surprised by what the scientists can do. Every time we thought we had a limitation, you get this brilliant scientist says, "I have a solution for that." So very much we're in exploring phase, further developing the technology. The potential is there, not everything is a reality today to say to some of the potential we have to work on it's efficiency, it's deployment, make it operable in practical way. But the potential is there, along the way, I'm sure we will learn about a lot of the limitations. But today, we are more excited about the potentials than the limitations, because we don't know, and we cannot validate those limitations until we actually fully use the technology. We're just at the beginning of it.

Jason Sparks:

Great. Thank you Gusui. We're going to finish off with one last question around open innovation. This obviously is a popular topic in the industry and something that we're very passionate about as Syngenta , both on a research and development side. So I'm going to start with Laura first, talk about what open innovation means to Syngenta. Kind of what are some examples of how we're employing this?

Laura Potter:

Yeah, I'm going to focus on the data and analytics space, and then I can hand it off, for a broader perspective. We have a rich history of collaboration and open innovation crowdsourcing in the analytics space. We started the Syngenta Crop Challenge several years ago, which is quite a big event, and we just recently had a celebration to celebrate the winners of the 2020 Syngenta Crop Challenge. We also have strategic partnerships with universities and we work with companies regularly as well in partnership, to advance innovation. So there are places where we want to be pushing new innovations and new ways, and that fits really well with the university partnership. So we pursue those as well as also leveraging the open innovation platforms where that makes sense.

Gusui Wu:

Maybe I can build on that. Open innovation is a significant part of our R&D strategy, because we don't believe we can solve all problems ourselves, we can innovate by closing the door. And working with the best people within the company, particularly the best people outside the company, is a significant strategy for us. Therefore, we invest significant portion of R&D dollars for external collaborations, supporting research, maybe not even directly, obviously related to what we're working on today. So it is a very much a component of how we do R&D. We collaborate with universities, we collaborate with industry partners, even with competitors. And whoever can help us come up with the best solution for our customers, we will support it and then willing to pursue it. So that's how we look at open innovation.

Warren Kruger:

Again, not to repeat to the great comments already made by Laura and Gusui, the same as is true, even in field research. So as we think about helping our teams automate some of our processes as discussed, or even develop new harvest or planter equipment, these are all opportunities where we can bring our internal expertise, as well as the appropriate partnerships and external expertise, to help get to the best outcomes. So it really translates all the way into the field as well as in these other domains. So just wanted to add that quickly, Jason.

Jason Sparks:

Great. Thank you all three. And thank you for your time today to present the material and answer questions, and a big thanks to all the media representatives for your time in the past few weeks, the summit. We appreciate the engagement and all the time you've spent speaking with our colleagues on both sides of the CP, the crop protection side and the seed side. And one last reminder that if you do want to schedule interviews, there's still this opportunity to do interviews over the next week or two, and those can be arranged through the summit site, or also our team at G&S who we’ve been working with can also support in this, scheduling their time. But that should be it. And thank you and have a wonderful rest of your week.

Product performance assumes disease presence.

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