 is Dr. Gary Seacour, he co-author with Viviana Rivera and Belvin Bolton, and he's going to be talking to us about sensitivity of the sort of conflict with people to follow here it's fun to decide on how to play too. Good. So anyway, I do want to talk again as I talk every year about sensitivity to fungicides. And this is for obviously for 22 because we just finished the testing. Most of the accolades go for Viviana Rivera who does all the work and I get the credit for delivering the presentation. So anyway, thank you for that. The first one I want to talk about is TIN. TIN resistance, incidence and severity of TIN resistance in our population, in our isolates, collector from Beatfields in North Dakota, Minnesota. In 2022, we collected 648 samples. And that's about half the number that we've had collected previously because the other half were tested at the beginning of the season. So we wanted to collect a number of 600 samples at the beginning of the season and then 600 at the end of the season. So I think Nate's going to do some talking about some of the detection at the early thing. Earlier, the agronomist brought the samples to us. We lyophilized the samples and Nate did the PCR assay. So we're starting to get a good joint project, expanding our efforts and expanding our horizons a little bit. So we tested, so the data I'm showing is these 648 samples. So this is from the left hand side from 1998 through 2022. The blue bars are the field incidence. So this is the percentage of fields with TIN resistance. So that ranges, it started out in 1998. 64% of the fields have resistance. Look at 2021 and 2022. Almost 100% of the fields have TIN resistance. So that TIN incidence, you can see it popped up here. It went down here for some reason. I have no idea why. And then I think we started using TIN again because we were worried about the DMIs. And so look at the incidence of TIN. So TIN is really a lot of resistance in TIN. This red line is the percent spore germination. So we look at 100 spores for germination or not. If they germinate, they're resistant, of course, because they can grow. So you can see that the incidence of spore germination, that's also increasing not only the number of fields, but the amount of spores that germinate. So it stabilized between 2021 and 2022 at about, what's that, 65%. So a lot of spores are resistant. Most fields have got resistance. So we got a pretty big issue with TIN. The good news about TIN is there's a fitness penalty. So when you quit using TIN, the sensitive ones out-compete the resistant ones. So we can get sensitivity back again by quitting using TIN. But then we got the risk we're not gonna get as good a control. So maybe we can do something with the CR plus varieties to get rid of a TIN application or something, okay? So anyway, that's TIN, okay? This is the incidence of fields with isolation resistance at TIN. Is that me? No, back there. So that's resistant to TIN from 2019 to 22 by factory district. So you can see that the TIN resistance, blue is 22. You can see the TIN resistance has increased in every single factory district. So you're not alone in any of your factory districts. So you can choose your factory district and you can see that it's a high incidence of TIN across the all growing area. So this is an industry-wide problem. Okay, so we'll switch now to resistance factor. We'll switch to the DMI fungicides, the triazole DMI fungicides, okay? We have four of them, eminent, inspire, proline and provisal. So we get a lot of those good ones there, okay? So this is the resistance factor from 2018 in the left-hand column to 2020 in the right-hand column for each of these four fungicides. And you can see that for inspire, it's gradually or pretty dramatically increased from 2018 to 2022. Proline did not really increase a lot, but we're not sure we're using the right product to do the testing there because it changes from profile to desktop and desktop's got all the activity and we're trying to figure that out collectively. Eminent, you can see that eminent is not really increasing. And that's kind of a surprise to us and it's sort of stabilized and leveled off during these years from what's that, 19, 20, 21 and 22. That's kind of a surprise at look at our friend provisal, that's been rapidly increasing as well. That's only just been a product that we've been using just recently and it's quickly become developed a lot of resistance. So this is kind of their resistance profiles from 18 to 22. This is the distribution of sensitivity to these same four DMI fungicides as major by EC50 is what we measure in the laboratory in 2022. And these colors showed up way better on my laptop than they show up here. So as well, oh, here they are. Oh yeah, this is what they're supposed to be. Thank you. So these colors, look on the side screens but you can see eminent here, okay? Red is, well, the red color is greater than 100. EC50 value is 100. The, what's that orange color is 10 to 100. The yellow color, yellow color is one to 10 and then the other colors are sensitive, okay? So you can see the amount of red, the amount of red increases, the amount of resistance increases with the different fungicides. Eminence very low, Inspire is a little higher, Proline's a little higher and Provisal is even higher. But these middle values of 10 to 100 is where most of the activity is, okay? You can see that color better. But I wanna look now at each of these, each of the DMI fungicides individually, okay? And this is my factory district, okay? So you can choose your factory district here and you can see, okay? The interesting thing, this is eminent. This is the eminent across factory districts, okay? But look at, there are no highly resistant varieties to eminent anymore. Those are all zeros at that high level and they used to be higher than that. So eminent is decreasing in resistance, okay? And that's probably because we're not using it as much because it's kind of got out of disfavor to some of the other fungicides. So maybe there is a fitness penalty in there that we don't know about. So eminent looks like it's doing pretty well, okay? No highly resistant. Again, the reds are greater than 100. So most of them are in the 10 to 100 now. Very few are in the fully sensitive at the very bottom of those bars. So that's kind of a surprise to us. Here is the same kind of data for Inspire and you can see we got a little bit more resistance from over a hundred parts per million, okay? So a little higher resistance here. Again, the 10 to 100 is still present. The one to 10 is still there in the lower levels. There's pretty low levels, okay? And if we look at Proline, remember this is by factory district, okay? So you can find your favorite factory district there. And you can see we got a little bit more red here with Proline, a little more resistance going in with Proline. Even though if you talk to the industry people, Proline seems to be doing really well in the field, right? And if you look at Provisol, again, you can see way more resistance across all factory districts to Sir Cospro. So we've got a little bit of difference here. So if you look at eminent, it hardly has any high resistance all the way to Provisol with lots of resistance. So there is a difference among the triazole DMI fungicides. They're not all created equal, okay? And I think Melbourne's gonna talk about this sometime, not this time, but sometime you can talk about this. So they've got a big project trying to elucidate why those differences exist. And this is the same thing in testing and doing the EC50 values. So it looks like we can maybe make a little headway among some of these DMI fungicides. They're not all the same. And they use different ones in Europe than we use here. Okay, so here's our friend headline, okay? Remember, headline used to work really well in what's that, 2012? We barely had any resistance in 2012. Well, of course, it works so well. We kept using it and using it and using it and more resistant develop. So anything that's read is basically 100% resistance. And you've seen this trend over the years because I think I've talked to every one of these years. So you can see that it continues to be highly resistant at the expense of sensitive isolates. So again, headline continues to be resistant. We don't have, there's no point in using it because almost everything is highly resistant. Don't have any sensitivity. And if you look at factory district, this is headline from 2022 across all the factory districts, pretty much all read. So you got resistance across all the factory districts. It's not just those that continue to use headline. It's just there, okay? So that's all I'm gonna, the only slides I'm gonna show. So maybe some summary and conclusions that I'd kind of like to just share with you all. Tim, still our best weapon. We're the only ones in the world that has this. US is the only one where it's labeled. Number of fields with 10 resistance declined 36 and 65% the past two years, but increased 69% to almost 100% in 2021 and 22. So 10 resistance is increasing. Incidents of resistance spores was 20% in 18, 30% in 19, 40% in 20 stabilized to 65% in 21 and 22. So the number of resistance spores also increased. We need to preserve this fungicide because resistance is easy to get and it's easy to get rid of when you quit using it. So we need to make some mechanisms to try to save tin, I think. Popsin, we don't test for Popsin and we didn't test for Popsin this year. It's still registered, it's still viable, but resistance is out there and more than 70% of the fields, resistance to Popsin doesn't go away. So it still can be a player but it's not really an important player, okay? The triazoles, this is where the action is. We have these four DMI fungicides. The resistance factor decreased slightly for eminent and it's been relatively stable the past four years. So eminent, even though it could be in use, it still looks like it's working pretty well. Resistance is increasing for Inspire, Provisal and Proline, but less for Proline than the other two. And we've got some evidence that some of the fungicides work the same and others work a little bit differently and you can alternate those two different ones so you can maybe manage that resistance a little bit. We hope there's a fitness penalty and for those with higher F values, because the more resistant they get, the more they might have to give up some other factor and have some fitness penalty because they're so highly resistant. We are evaluating some mutations in Bolton's lab to try to get a PCR test. And Nate, well, actually they're both doing it, Nate and Melvin to try to do, get some PCR testing. So it's easier to monitor these, so it doesn't take as long. And I think we need to continue to use Mancozeb or a copper partner. Every time we put on a fungicide, the copper inhibits for germination at 10 part per million. No resistance has ever been reported to Mancozeb since its registration in 1948. So we don't ever have to worry about resistance to Mancozeb. That's a pretty solid fungicide, okay? QOIs, single gene mutation, resistance since 2016, greater than 90%, doesn't appear to be a fitness penalty for those who are resistant to headline. And QOIs is still not recommended for CLS management because it doesn't work, because they're all resistant, still can be used for, or it still is used for frost protection, okay? I think we need to develop better CLS resistant varieties. Well, we've done that, we got CR plus now. So now we need to figure out how does that fit in with fungicide resistance? How does CR plus fit in with that fungicide resistance? Okay, do the new varieties with high resistance affect fungicide sensitivity or fungicide resistance? We don't know the answer to that. I may not be around long enough to answer that question, but I think it's something that needs to be answered. We've done some work on adjusting the forecasting to include sport production and germination for earlier fungicide application, okay? Because we think that's an improvement over the existing model of when you put that first spray on, and Viviana is going to give a presentation, I think three after this, we're going to talk about some of the work we've done with early forecasting or early sport detection, and Nate's going to talk about some early testing to detect latent infection of beets in the field before you can ever see the spots. So I think there's some early application of fungicides that are going to be talked about later and are going to be important. The other thing is Viviana noticed that when she's looking at all these samples, we saw a lot more alternatoria this year than we've seen in past years, okay? Is that because this was such a wet year? Did that favor alternatoria? Or are we getting more alternatoria because the fungicides you're using are also making alternatoria resistant? Or do we just simply have more alternatoria for variety susceptibility? I think that's something that we may want to do some thinking about. We don't really know what species of alternatoria we have out there, and there's a number of long-sport and short-sport alternatorias. We need to find out which one they are. We've done some work with Mark Anfenrode, who brings his samples on a regular basis, whether we want them or not, right, Mark? You know, I'm saying that jokingly. So we've been able to get a lot of alternatoria samples that we need to look at because alternatoria might be a bigger player than we think. And Ashaq and I talked a little bit about that this morning, too. So that'll continue to get you more awards in the future. Can you do that? Job security again. Job security, exactly right. So anyway, is it opportunistic or is it really an important player in the sugar-meat industry? So I need to acknowledge all the support that you all gave us and the companies that provided the technical grade product that we use and technical assistants of Judith Rangifo, who is just phenomenal in her. She's really strict and she really goes right after it. So she's really good at that. I also have to give acknowledgments which I forgot to put up here of our USDA colleagues who we continually interact with and have lots of good conversations over beer or over lunch. And which do you think are the most productive? Beer and napkins, right? They're the best, so. Okay, our next presentation will be is entitled Crop Sequence and Tillage Effects on Crop Pests, Soil, Microbes and Soil Properties, being presented by Mayowa Adirju, co-authored with Sunil Bandari, Guy Kinyan, S. Banerjee, and Mohamed Khan. Good afternoon, everyone. My name is Mayowa Adirju. I'm a graduate student of Plant Pathology Departments, North Dakota State University. Earlier this morning, a lot of my colleagues have talked about the importance of crop sequence and tillage type on crop production and pest management. So I'll be giving a similar presentation. This time I'll be talking about the impact of crop sequence and tillage type on crop yield and quality soil properties and microbial population. Okay. So the outlines for this presentation includes introduction, the objectives of this project. I would also be talking about the results from our first year in 2021. I'll be talking about the work done so far in 2022 and I'll be talking about the future work to be done as regards this project and I'll be making my summary on completion. So it is very important to note that there is a need for a sustainable management option for crop production and also an eco-friendly approach to weed control, disease management, and pest management. So most importantly, to having the right rotation crop and the best tillage practice could help us control disease, infection and pest infestation and also conserve and improve soil fertility. So these over version now laid the foundation for the objectives of this project which is to determine the impact of tillage and crop sequence on yield quality of major crops, growing in rotation, the microbial population of the soil over time and we would also look at the disease severity caused by a number of plant pathogenic organisms in sugar with another crops. So this will help us account and document the best practices for managing insecticides, abyssal and fungicide resistance of the crop in this sequence. So I need to note that the crops we are looking at for this project in sequence are we have sugar beet, which is more of the focus crop and soybean, corn and wheat. So in the first year, which is 2021, we looked at two factors, the impact of two factors, which is tillage type and crop sequence. And so for the tillage type, we had the conventional tillage type, the strip till and no till and we had this, we did this sequence for the first year. So in the first year, we analyzed the results we got after harvesting and we looked at the impact of tillage type on a number of parameters. And so for the purpose of this presentation, I would be highlighting the parameters that showed significant results because I wouldn't want to waste your time with results that are not really significant to what we are here to do today. So we observed that for the yield, I need to note that this yield is for the corn because for the first year, we had corn in rotation with soybean. So for the first year, we observed that conventional tillage had a yield of about 214 bushels per acre, which was significantly higher when we compared it to the other tillage types. So we also looked at the moisture content and we also observed that the conventional tillage also had the highest moisture contents, which is quite similar to the strip tillage, but significantly higher than the no till type. We also looked at the impact of tillage type on organic matter. And we observed that the conventional tillage had about 4.89 organic matter contents significantly higher than the others. But when we at the depth of zero to six inches, but when we went deeper into the soil, sorry, we observed that the conventional tillage retained the highest organic matter contents. But when we compare the numbers from at the depth of zero to six inches to the one we have here at six to 24 inches, we observed that the organic matter content reduced from 4.89 to 3.89 year. And that's kind of answers the question that was posed earlier about the impact or those tillage type influenza, the organic matter on microbial activity in the soil. So I think we do have a guess because the project is still ongoing. So we also looked at the average log abundance of cysteinezine from the soil samples, which accounts for the abundance of moisture microbes in the soil bacteria and fungi. But this data, I'm sorry, it's not clear. This data shows that of bacteria. And we observed that the conventional tillage, this box plot is for corn, why this is for soybean. And we observed that the conventional tillage had a higher log abundance, but which is quite similar to strip till. But when we compare it with the no till, we observed that it was actually significantly higher, but we did not observe any significant difference for the soybean box plot. Also, we looked at the impact of the second factor we were considering, which is the crop sequence on the same parameters like we did for the tillage type. And we observed that we did not really see that much significant impact of crop sequence on the parameters. But we did see for sorbita and organic matter. Sorbita being a parameter that accounts for the rate of respiration and CO2 activity of microbes in soil. We saw that the crop sequence too, which is actually soybean, add a higher percentage of sorbita as compared to the crop sequence three and four. And for the organic matter content, we observed that there was no significant difference at the depth of zero to six inches. But yeah, we have a significant difference for the crop sequence. I need to remind you that the crop sequence for is corn. And corn showed a higher significant organic matter content compared to the other crop sequence. So we continued the project for the second year, which was 2022. And we maintained the tillage type. But this time we added different crop sequence as shown here. So this shows the narrative of the old project for 2022. And the crops we add in rotation are corn, wheat, soybean, soybean and sugar beet. The picture up here shows the conventional tillage and this shows the strict tillage. And the blue arrow is pointing towards the soybean plots while the red arrow towards the sugar beet plots. So after harvesting this last year, 2022, we looked at the yield across the tillage types. And we observed that irrespective of the erosion and late planting last year, we observed that strict tillage had a higher recoverable sequence of 3,041 per hectare, which is significantly higher when we compared it to conventional tillage and no till. And that also gives an idea about what Aaron showed about strict tillage as a potential option for controlling erosion in sugar beet. So when we also compared the yield for soybean, though the conventional tillage at numerically at the highest bushel per hectare of 27, but when we did the statistical analysis across tillage that we observed that there was no significant difference as regards the yield of soybean. We also did some laboratory work to account for nematode population in the soil for each plot. And we did the soil sampling earlier, if I remember correctly, at the middle of September after harvesting. So we homogenized the soil samples, we extract the cis nematode in the soil, and we did the cis count under the second microscope. And this year shows the cis nematode that you can see. The arrow pointed to this circular cis-like object here. And that's the cis nematode under the microscope. And the preliminary results showed that we had more cis nematode in the sugar beet compared to soybean. And this is one of the focus of this presentation because we are starting to get concerned about the possible increase of sugar beet. It's a guess, right? But we need to look at the increasing population of sugar beet cis nematode, the guess, in sugar beet plots. So we actually compared, we looked at the impact of the two factors, which is tillage type and crop sequence on nematode population. And we observed that there was no significant difference when we looked at impact of crop sequence on nematode population. But here we do observe that tillage really played a significant role in impacting the nematode population as we observed significantly higher nematode population in the no-till. So for the future work, what we do know is that we do have cis nematode in the soy. But we have our guess around we do not know what cis nematode we have in the soy. Though we have our guess around it could potentially be the potato cis nematode, soybean cis nematode, heterodera glycine, or the sugar beet cis nematode, which could actually be a problem. So we hoped we would conduct DNA extraction and PCR to identify which nematode we have in the soy. We would also conduct pathogenicity tests in the greenhouse to provide information about the virulence of this cis nematode to sugar beet or soybean. And currently, we are conducting microbial extraction and identification. And we would also look to quantify the impact of tillage type and crop sequence on earthworm and insect population. In summary, the research so far shows that the conventional tillage shows more promising potential in increasing the productivity in the soy earth amongst all other tillage types. Also, the nematode population was greatly impacted by tillage type and could significantly increase in a field where there is no tillage. We also observed that the strip tillage shows a better potential for erosion control in sugar beet with a significant recoverable sequence of 3,041 per acre. Conclusively, the overall results shows that the tillage type had the most significant influence on yield, as we've seen so far, and in moisture contents, organic matter, so with a nematode population compared to the second factor, which is crop sequence. Thank you for listening. OK, our next presentation has been titled Survey Identification and Characterization of Storage and Pathogens of Sugar Beet in the Red River Valley of North Dakota, Minnesota. It's being presented by Mohamed Zia, Bjuan Booyan, Peter Hock, co-author and Mohamed Khan co-authoring. Good afternoon, everyone. Yeah, I'll be presenting the research report on survey identification, characterization of storage, pathogens, the sample collected from different locations of Red River Valley of North Dakota and Minnesota. So as you know, sugar beet is a big industry, and North Dakota and Minnesota combinedly contributed 57% of total sugar beet production, which is approximately $5 billion economy. But sugar beet, after harvest, sugar beet, actually the end product sugar quality deteriorates. It's believed that association of microbial pathogens, respirations, own injury, even the storage environment significantly reduce the quality of sugar. So it was experimented earlier that around 0.14% partage sugar content losses due to the storage condition. Even if it is poor, it's reported approximately 60% reduction of sugar content. So for this study, we collected sample from three different locations of sugar bacteria of Minnesota and four North Dakota locations. East Cornfrogs, Crookstone, Moorhead from Minnesota, Ardoch, Reynolds, St. Thomas, and Opiton, Mindak. So for this study, we did morphological characterization and identifications. We did microscopic observations. So we grown the pathogens in malt extract agromedia and clarified V8 juice media. So we studied the colony morphology and growth pattern. And as well as on microscopic observation, we studied the color Conidia, Conidio 4, and the Mycelia. So for molecular identification, we considered five different primers, ITS, second largest ribosomal protein subunit, RBV2 primer, translational elongation factor, beta-tubulin, for short base pair length and calmodulin genes. So briefly, the molecular states we followed. Initially, we extracted the DNA from the bio-isolated pathogens. And then we did conventional PCR followed by Sanger sequences and alignment of the sequences. And then we blasted in NCBA. So we identified 10 different penicillium species. As I believe, most of them are not reported yet in sugar beet for red river bilio of Norgicon and Minnesota. So especially penicillium expansion, penia, penam, polonicum, crustosum, primarum, and celerum. These are very brand new in sugar beet. And other pathogen associated for the samples we collected. So both try these Klerosporium, several species of mucor and aspergillus. We got some minor species, poma, beti, sardaria, fusarium oxysporum, rhizopus aureusia, and macrophomina fasiolina. And we also reported four different trichoderma species. So one of them, sorry. So trichoderma polysparum. As we know, trichoderma hergienum is an oil-known and oil research biocontrol agent. In addition to that, we already conducted in-between greenhouse studies. So we found that trichoderma polysparum could be a promising biocontrol agent for controlling. We studied on sclerotinia, scleroshiorum, and rhizoptinia saloni. So we did pathogenicity test. We didn't, I was not able to conduct test all of them. So from them, I tested nine storage pathogens. So we did both surface-surfaced onding or injury and cork borer agarplug method. We incubated for four weeks at storage temperature, cold storage at NDSU. And then we evaluated the disease severity or disease development. So we calculated the most prevalent species, genus, from the collective samples of spainicillium, followed by trichoderma, botrybis, and aspergillus. Fusorium and clodosporium, they constitute approximately 8% and 7% and other phoma, sordaria, rhizopause, they constitute 12%. So among 20, 267 isolates, we isolated 175 pathogens from North Dakota samples and 92 from Minnesota. So from all of the sample percent, statewide percent distribution, we found around 65% of the isolates are isolated from North Dakota and rest of 35% from Minnesota. This graph indicating a statewide distribution of individual microbial pathogens, but it's indicated in both cases, penicillium are the most predominant prevalent storage pathogens followed by botrybis, fusorium, and other species. So we can summarize and contribute to this presentation that penicillium, botrybis, and aspergillus are the most prevalent and common species causing storage disease. As I am not yet sure the other pathogens, we need to be tested for pathogenicity and further molecular characterization. North Dakota is surprised the amount of isolated from both the state, North Dakota and Minnesota. And minor pathogens, as we mentioned earlier, phoma, sordaria, rhizopause, and macrophomena. And trichoderma could be an excellent addition to further biocontrol study controlling some soilborne and other pathogens. And I would like to give big thanks to my PhD research advisor, Dr. Mohamed Khan, Dr. Karan Fugate, John, Dr. Shyam Kandel for the discussion and valuable suggestion. All my lab lab mates, Sunil, Peter Haig, who got the samples. And Sunil, Sushmita, Myoi, Emma. And I would like to give big thanks during my PhD journey or research funded by Sugar Beet Research and Education Board and my NUSA department, Plant Pathology, and all faculty and teacher and everyone in Zoom and in person. Thank you very much for your patience hearing. And I would be happy to have any questions. So our next presentation is entitled Early Sercospor of a Tickle of Spore Detection and Germination in Commercial Sugar Beet Fields, presented by Viviana Rivera, co-authored with Gary C. Core, Nathan White, and Melvin Golden. So as we know, management of the Sercospor of a Tickle of... Can you hear me? Yes. Oh, Sercospor of a Tickle of a Tickle of a Spore continue to be a disease in sugar beet that is endemic in our region. Management requires an integral approach which consists in resistant varieties, cultural practices, and timely fungicide application. The fungicide use for Sercospor of a Tickle of Management are mostly protected and they work better when they apply before the infection or cure. No curative to not stop the disease once it's the disease development. Timing of the first application varies greatly. It can be used calendar, appearance of the first spot, before road pressure, or using four-cast models. In this model, we have two models, Chen and Chen, developed in the 80s and a big-cast model developed in 2004. Both of these models use the weather data to develop the daily infection value. Weather data are mainly related to humidity and temperature. This model is used by the industry and the growers to predict the spread of the disease and also the first applications, the fungicide application. Both models predict condition failure for the disease development in the field after the first spot is detected. Both of these models don't include the condition failure for the sport production and germination, and this is very important in early infection. Early first infection needs early fungicide application. So this is the reasoning for doing this research. Philocellivation indicates that there is this control with early fungicide application compared to the later fungicide application. Previous work in our lab shows that a sarcospera viticona can grow in lower temperature than previous reported, because sarcospera can grow and produce a sport in temperature as close as 50 Fahrenheit or 10 Celsius in a period of time. Free water is more important than high relative humidity for sport germination. So based on these thinking, we developed this study and the objective was to see how early the sarcospera sport can be reproduced and if the sport is present before the crop is emerged. And also we want to determine how early the infection can occur. I'm going to refer to the two first points and Dr. Wyatt will talk about the third one. So for this we did a study, two years studying 21 and 22. We used a sport trap that was a weather station that was installed at age of six field, the commercial sugar field in three locations in Minnesota. This sport trap we're putting the field right after planting and before emergence. We have two field sites for cooperative and selected by the agronomies. These fields were adjacent to a field that they have a sugar beet of previous season. And in 2021, we have a field in Comstock, Burley and Brambill and 22 in Kindred, Burley and Brambill. So once the cadres were in the sport trap were installed, we collected the cadres three times a week for 14 weeks in 2021 and three times a week for eight weeks in 2022. The cadres membrane were tested for the presence of a Cercospora viticula DNA by using a PCR. This was a quality test. So we just want to see if there is a Cercospora present or not, we didn't quantify the amount of the sport present in the membrane. So in this picture, we can see the sport trap located at the edge of the field and these are the weather station. So a close up of the sport trap, this is where the wind goes into the little tunnel and the cartridge goes in between, in this part. So the membrane captures all the insect dirt that's poured and flying into the sport trap and we take this membrane and we test for the presence of Cercospora viticula. So the result in 2021, Cercospora sport were detected the first week in May in all three locations and it's periodically after until June 2nd. In this year, in that year, we tested 250 cartridge during this period, the sport were detected 45% of the collection day in Comstock and Perley and 52.4% of the time in Rending. Of course, you all know that 21 was a dry year and with a very early planting date. In 2022, we detected, we installed the sport trap like in May and during the first week of collection, we detect the sport in all three locations. 22, of course, was a wet year, wet spring and delayed the planting date. In that year, we collect 141 cartridge that was processed during the eight week period and we detect a sport since the first collection day in Kindre and Perley, 82, almost 83% of the collection date and in Rainville, about 96% of the collection day we found a Cercospora viticula in the membrane. As I mentioned before, for detection, the Cercospora viticula, we use a set of primer that detect the presence of the mutation G142A, the confer resistance to headline. This is a wet set of primer that is very specific for Cercospora and in addition to detect the Cercospora, also this primer gives us an estimated sensitivity to a bioconstruing of the sport collected. So what we find out, there is a big difference in sensitivity between the population tested at the beginning of the year compared to the sensitivity we report at the end of the season. This was valid for 21 and 22. So here is the graph that is very interesting. If you see the first date is the profile of the sport collected in that season to headline. So this is at the end of the season of 2020 and then we have the profile of the sport we collected in 2021 across all the side. And we can see the resistant isolate really ended up with 68% of the sport being full, being resistant to headline. And we found out only 13% of the sport are resistant to headline. And if you look in the bottom, which is the sensitivity of the sport, we have 30% of the poor sensitivity. When in 2001, we ended up only with 1.2% of sensitive sport. Now, if we look at the end of the 2021, we see we revert this little amount to all the ways to 75 and almost we don't have any susceptible isolate. Looking now at the year 22 beginning of the collection season, all the resistant almost disappear being less than 1%. And we can see the sport that have some degree of sensitive is almost 70% of the isolate. So if we look what we find out at the end of last season, we see like almost 88% of the isolate are fully resistant or they're resistant to headline and we lose almost all the 1% is just a sensitive one. Same happened, maybe we look by a co-operative. We see the same trend. We have a 13% at the beginning of the season and we end up with 83%. We have a fair amount of isolate that are sensitive to headline and almost less than 1% that are sensitive. Same happened in Minde and southern Minde. This is for a year 2021. Same for 2022. In this case, we have a little more, we see a little more resistant, a percentage of isolate that are resistant to headline and we start about 10% in Minde and southern Minde and a little more in American Greece. But you see also the susceptible one, there are very big percentage of them that are fully susceptible to begin of the season. So what is this difference? We are not sure. We see there's a finite penalty that for the score, the carrier of the mutation for some reason they don't survive the winter here. Or also we know in our previous work that isolate that sensitive to all fungicide and the resistant one tend to have a significant more exfoliation, a lower temperature than the resistant one. And this is true until we reach a temperature about a 65% Fahrenheit. So maybe the fact that the resistant one don't germinate our temperature or cold temperature or just is a fit that penalty. So as a summary, we know that now the score are present in an early spring, even in wet or dry spring. Infection can be late early in the growing season before we see the spot or the first sign of disease. Fungicide don't cure plants already infected with Cospora veticura. Fungicide should be applied early in the season before the spot appear. We know a sport germination is favoritized, the free moisture compared to high relative humidity and the morning view during the early spring is very common. There might be a fit penalty for Cospora with resistant and better preserving that disappeared during the growing season and we don't know the reason now for now. And we plan to work a little more on this in the future years. One to say thanks to the sugar-free research and location for Minnesota and North Dakota for their support, the companies for help us with the field work and also the assistant or jewelry and grateful in our lab. Thank you. Our next talk is entitled An Incidence of Plant Pathogens in Sugar-Beet Storage being presented by Shiam Pandel with USB-A, ARS and Fargo. Thank you, Mark. Today I will be giving some preliminary report on incidents of plant pathogens in sugar-beet storage. Just the introduction here in the Red River Valley about 10 to 20% of the total crop is harvested in early fall and those roots are processed immediately without any storage but the remaining crop is harvested in the month of September, October. And from that harvesting about 20 to 30% of the crop goes for freezing. The remaining crop keep in a big storage piles in a different location. If you look at this map here, this is the map of North Dakota and Minnesota and each orange dot represents the sugar-beet storage piling location over the valley. And in these storage, you know, preserving sucrose is a big challenge. High respiration and the storage disease can cause sucrose loss and the deterioration of those storing roots. So the research objective of this study is to identify and characterize the post-harvest pathogen in these storage piles and to assess the pathogenicity and the virgins spectrum of these pathogens in the sugar-beet cultivars. In this study, we collected samples from the Patriot and the storage piles here. This is one of the Patriot that we collected samples. Here we collected samples from three different spot as you see that indicating by those arrows, we collected nearly 150 root samples that are showing the visible symptoms of microbial growth. And for the storage piles, we collected samples from the three different spot from the top kind of medium and the bottom of the piles. And we collected the samples when these piles are opening up and reloading the roots from piles to the Patriot. We collected samples from the right and the left soldier and collecting samples from these patches kind of challenge because they are huge. They are more than a hundred, more than 1,000 feet long and they are more than 20 feet tall and climbing and getting the samples from the different parts of the pile is not that easy but we got the help from the factory people. They are very helpful. And these excavator that's reloading the roots from storage piles to the factory that helped to scoop some of the samples from the upper layer of the pile, some from the kind of in between, from top layer at the bottom and he scooped those roots and a dump over here and we collected those roots that with the visible symptoms of the microbial growth. This is the kind of general workflow. We received those samples and we collected the root tissues with the microbial growth. We vigorously washed those root tissues with the Israel water and we plated those tissues on the nutrient of our medium. Few rounds of soft-culturing we received the pure culture of the individual isolate and we are maintaining those isolates at negative 80 degree now and we are working from there. So far we have characterized some of the isolates that I'm going to share now. This is the list of the fungal isolates that we identified so far. So far we identified 23 fungal isolates. Most of them are the penicillium, mucus and some other fungal pathogens as shared in this slide before looks like that there is a significant overlap in some of these fungal pathogen. This is the list of the fungal pathogen that so far we identified from the factory yard. As you see here the mucus is the kind of dominant fungal isolate in the case of factory yard. When we combine both from the storage piles and the factory yard this is the summary about like 50% of the incidence of those storage is associated with the penicillium species about like 20, 22% is associated with the mucus species and with some other species. For example, hypochrya and trypoderma, fusarium species. Trypoderma and hypochrya they are the enomorphic and telemorphic of the same fungal species. We don't know which one is the dominant one yet. And this is the list of the bacterial isolates that have been identified so far. As you look at those list some of the known bacteria are here like Nucanus bulcanobacter, basically in a sugar beet, two groups of the bacteria, lactic acid bacteria and acetic acid bacteria are known to degrade the sucrose into the alcohol and acetic acid compound. Probably they are the important bacterial isolates to degrade the roots in a storage. I don't have the concluding slide. This is, sorry. This is my last slide. As you see here, bulcanobacter is the most common bacteria followed by pseudomonas, ronella, bacillus and some other bacteria. This is my last slide. We haven't done the pathogenicity test and the postulate verification yet. We are doing that now. Hopefully I will have those results and I'm happy to share those results in my future conversation. With that, I would like to very thankful to Sugar Beet Research and Education Board for funding for this research. And I'm also like to thank Dr. Mohammad Khan and the future Hock for introducing me to the Sugar Beet Cooperatives and helping me to get these samples from different locations. I would like to thank my student, Emma Nelson and the corner heads. They helped to process those root samples. Emma is here in the audience. If you get a chance, please say hello to her. She is still working in my lab. And I also like to thank my technician, Ella Montalbo. She has been working really hard in this project. And I would like to thank all of the Sugar Cooperatives from the Red River Valley. That helped me successfully conduct this research. Thank you. All right, our next presentation is entitled Forced Selection by Exposure to DMI, Fungicide and Tank Mix Partner Combinations Reveals Variations in Phonetic Diversity of Cercospora Beticula Population, presented by Austin Lee and co-authored with Shuk Chanda. Well, good afternoon, everyone. So I hope most of you have been able to hear my presentation in the last two reporting sessions because today I will be expanding beyond the field trial I've conducted and discussing the impact that DMI's have on the genetic diversity and population structure of a Cercospora Beticula population. So, Cercospora Beticula is caused by the fungus, Cercospora LeaSpot is caused by the fungus, Cercospora Beticula. And you've heard an introduction from the other speakers here today. And I'm sure many of you are aware of the destruction the disease can cause. But I just want to emphasize that even with the implementation of the new varieties we have available, fungicide treatments are and will remain essential for maintaining healthy crops and high quality yields. Therefore, fungicide efficacy must be sustained for as long as possible by delaying the development of fungicide resistance. So I just first want to recap those inoculated field trials we conducted in 2020 and 2021 where we evaluated several DMI fungicides and tank mix partners and combinations of those products in which we attempted to determine which treatments and which combinations provided the best Cercospora LeaSpot control and allowed for the highest quality yields. And considering the two drastically different growing seasons we had in 2020 and 2021 where 2020 was very wet, we had very frequent rainfalls and 2021 was almost record breaking drought conditions. We were very interested if we saw the same trends in both years of this field trial. So just first looking here, this is the DMI, this is disease progress for our DMI treatments. We evaluated Proline, Inspire XT, Provisol and Minerva which is similar to eminent as well. And we did see the same trends in both years. And we had this no DMI treatment group which reached, had the highest disease levels in both years. And this group includes treatments such as Mancozeb, Copper, Sulfur and other tank mix partners. And then we do see the same trends where Minerva and Provisol are comparable in both years and then Inspire XT and Proline are also comparable in both years. And next looking at the disease progress for all of the tank mix partners, we see that Mancozeb and Copper are ending the season with the lowest amount of disease. But also we looked at a foliar, phosphite product and sulfur and they did provide a reduction in disease compared to a no partner treatment as well. So compared to a DMI by itself. And the biological, we also looked at a biological product and sodium bicarbonate. And that actually did provide some disease reduction in 2021 and for the most part in 2020. So ultimately the aim of this field trial was to provide some practical information for growers and maybe add a new, a few new tools to the toolbox for managing Cercospora. But we're also interested in why we are seeing that differing performance between those treatments. And we're also very curious to how tank mix partners are playing a role in interfering with the development of DMI fungicide, our DMI fungicide resistance. And really what underlying molecular mechanisms of resistance are at play? And especially considering a majority of our knowledge is limited to only tetraconazole which is eminent and Minerva. We're really interested in looking at these other DMI fungicides as well. And so this field trial also acted as a forced selection experiment in which successive generations in a year were exposed to repeated fungicide applications because all of those fungicide treatments were repeatedly applied five times throughout the growing season. So just to set the stage a little bit better, I wanna take a quick moment and provide a brief explanation for how fungicide resistance evolves in a field. So at first there's just a very small number of individuals in a fungal population that have mutations that have occurred randomly through natural processes. And some of these mutations will allow that fungus to survive a fungicide application. So when that specific fungicide is used, it will control almost all of the population except for the ones with the mutation. And over time, the individuals that survive and that are also fit will reproduce an increase in frequency within the population. I also wanna take a quick moment and explain the differences between the two main types of fungicide resistance. So the first is sometimes referred to as single step resistance here. And essentially, well, and this results from usually one mutation in the gene that the fungicide targets. And so essentially this is like a light switch. And once that light switch gets turned on, it confers complete resistance to that fungicide, which is what we see with the QOI or the Strobe-Elier and fungicides. But on the other hand, we have what's referred to as multi-step resistance. And this results from several different mutations within the target site, but also involves several non-target genes. So as more mutations evolve over time, the more resistant a fungus can be to a certain fungicide. And this is what we see with the DMI fungicides or the triazols. So to help us begin to answer those questions I posed in the earlier slide, we collected Cercospora isolates from the field trial in 2020. And the first collection took place as soon as leaf spots began to develop, which was on July 20th. And then we collected again at the end of the season on September 16th. And once again, fungicide treatments were repeatedly applied five times throughout these two collection points. So once we had all of our peer cultures and all of our DNA extracted, the next step is this DNA fingerprinting process. So essentially this process allows us to identify isolates that are genetically identical. And then as well as evaluate how closely related each of the isolates are, which provides the information necessary to evaluate genetic diversity and population structure. So just to show you some of the diversity we found, this photo shows isolates just collected in September and only from one treatment. And so each row here represents four isolates collected from the same replicate of the field trial. And the isolates that have the same number are genetically identical. And what's interesting is that we see those identical isolates showing up in multiple replicates of the field trial. And this just offers strong evidence that the fungicides are selecting for some of the same individuals. And here, just to recap, we did 16 isolates from this one treatment and nine of them were unique individuals. So the first bit of data I wanted to show is the variation we see between the two time points. So we were able to get data from 237 isolates that were collected in July. And of those, and these are represented by this blue peak and also hidden in the background here. And of those, we found 59 unique individuals. And for the most part, this population was actually dominated by one particular unique individual. And for the September collection, we were able to get information from 497 isolates. And of those, we found 120 unique individuals. But what's really interesting is that we only see 34 unique individuals are found in both of the time points. And that's represented by this overlapping peak here in the middle. And that means that only half of the individuals did not survive that repeated fungicide application. And 34 of them were able to survive those five repeated applications. So the next figure here is a dengergram of the Sercospra isolates that were exposed to the DMI fungicide treatments and collected in only September. So we're only looking at the end of the season now. And here we start to see some very strong groupings where the isolates exposed to Minerva and Proline are actually clustered together. Well, the isolates exposed to Provostol and Inspire XT are also grouped together and are diverging from those other isolates. And the isolates that were not exposed to a DMI are just kind of off by themselves. So here we're still looking at the samples collected in just September, so just the end of the season, but categorized by the exposure to those tank mix partners. And what we see here is that there's just very little divergence between those treatments except for Mancozeb. So Mancozeb is kind of off by itself separating out from the others. But what we should take note of here is that the scale here for genetic distance is actually four times smaller than the genetic distance when we look at the DMI treatments. So these are all much more closely related. So next, now this is a, we're still looking at the end of the season and this is a discriminant analysis of principal components. And first what we did is remove any prior assumptions of our treatment exposure. So I'm essentially just giving all these isolates to the computer and telling the computer, you tell me where they belong. And the first thing we had to do is determine that three main clusters that you see here best represent that population structure. And so once we have these three clusters, I wanted to see what individuals fall into each cluster. And so we begin to see the same similar groupings here where when we look at cluster number one, it's predominantly isolates exposed to Proline and Minerva. And when we look at cluster number two, we see a similar trend in Spirext and Provasol or treatments exposed, isolates exposed to those treatments are mostly found in that cluster. But then we also have this third cluster here where there just doesn't really seem to be any clear connection to those DMI treatments. So here are the same three, oops, yeah, the same three clusters shown in the last photo, but now we're trying to fit the isolates that were exposed to the TankMix partner treatments. And we see here as well that there really isn't any connection between those three groupings and the exposure to the different TankMix partners. So based on these findings, it seems that DMI fungicides provide a much stronger selection pressure on the population compared to the TankMix partners. And the DMI's are really the main force influencing population structure. Additionally, the strong, yeah, the strong groupings that we see or the strong clustering that we see with isolates exposed to DMI's suggests that there may be a very high risk of cross-resistance. And based on information, especially from Gary Secor's lab, we know that in Spirext and Provasol may have some similarities, but based on this, it seems that there may be a high risk of cross-resistance to Minerva and Proline as well. And on the other hand, the lack of clustering we see with isolates exposed to TankMix partners suggests that the risk of cross-resistance between contact fungicides is very unlikely. So by looking at genetic diversity and population structure, we have strong evidence that the population is highly differentiated at the DMI exposure level. And now we can start to investigate hypotheses as to why these populations are so differentiated, such as what mechanisms are leading to cross-resistance and in what way do fungicide mixtures interfere with the development of DMI resistance. So to really evaluate the effect of these combinations or fungicides, we need to first get fungicide sensitivity values from each of the isolates. And to do this, we've also developed a new protocol for fungicide sensitivity testing that is more efficient in the use of resources and time. And by doing this, we measure absorbance of fungal cultures growing in microplates that you see here in the background. We'll also start sequencing whole genomes for all of the unique individuals we found so we can conduct a genome-wide association study to see what genes are most associated with fungicide sensitivity. So with that, I would just like to thank the SugarBeat R&E Board for funding. I'd like to thank the many companies for chemical product and seed, especially for the field trial. I'd also like to thank everyone involved with collecting all of these leaf spots and helping with lab work. And a big shout out to Dr. Nathan Wyatt and John Newbauer for answering a lot of my questions and helping me get started with this part of the project. And thank you to my advisor, Dr. Ashok Chanda. So if I have any time, I welcome any questions. Okay, Mark. And so on the case impact of Chicago leaf spot on a certain journey through the story, I am in Portland. It's being presented by Dr. Karen Hubey and co-author of it, Mohan Karjanay, Peter Hock, and the boss, Bob Kelly. Well, thank you, Mark. It's a real pleasure to be here today and to be able to present some of the research that we've been doing over the last several years. This is a project, but I'm standing in the wrong place, apparently. This is a project that's really kind of a joint project between Mohamed and me. It's been known for many, many years and there's been many, many studies that have shown that Sercospora has a large economic impact on sugar beets at harvest. It's known that Sercospora reduces root yield as well as reducing sucrose content. What's not known, however, is how Sercospora affects storage. There's a lot of anecdotal evidence that suggests that having severe Sercospora during the production season affects the storage of the roots after harvest, but there really hasn't been any large studies or comprehensive studies that have been conducted with Sercospora infected roots or roots from plants that have been infected with Sercospora and how they respond to storage. And yet, we really do need to know what the effect of CLS is on storage because it has huge implications for both storage and processing. What we really need to know is, is there a level of disease severity that would impact storage to such an extent that you wouldn't wanna store the beets? That's the first question. The other is, if there is an effect of CLS on storage, is there an advantage to segregating the beets from the regular piles so that they could be processed earlier to avoid losses during storage? It's also important to know if there's any changes in quality in these beets during storage because that affects what happens in the factory and any adjustments that they need to make for any increased level in impurities. So we've teamed up with Muhammad. Muhammad really does the first half of the study and my lab does the second half of the study. Muhammad does all the field work and the production of beets with different levels of Sercospora. And what every year Muhammad gives to us are beets that have four levels of disease severity of Sercospora. He gets this by taking a CLS susceptible variety, planting it in field plots out near Fox home. Those plants are then grown up, inoculated with seed-particular infected leaves about mid-July. And then Muhammad uses different regimes of fungicides to get different levels of control. Right before harvest, the beets are rated on a one to 10 scale with one being healthy beets and 10 being very severely infected with defoliation due to Sercospora. After rating, the beets are harvested and Muhammad then gives them to us in our lab where we take these beets and put them into a storage study. The beets are stored under controlled environment conditions. So we store them at five C or about 41 degrees Fahrenheit at a constant temperature and at high humidity, which is good storage conditions for sugar beets. We store them for up to 120 days and we evaluate them at harvest as well as after 30, 90 and 120 days in storage. What we're looking at in these storage studies is root respiration rate. We're looking at how much sucrose they lose in storage. We also quantify the accumulation of invert sugars as well as looking at sucrose lost in molasses or any changes in sucrose lost in molasses and any changes in recoverable sugar per ton. The last point is that we've got three years of data now and the study has been completed and so this is the final report. And I thought because the results from these three years of study have been so clear and so consistent that I just kind of cut to the chase and go to the conclusions first and then we'll go back and look at the data. And the conclusion is that we saw nothing happening with beets that were infected with sucrospera as far as any changes in their storage properties. And it was irrespective of the severity of CLS. And we saw these same results in each of the three years. And so I may be getting ahead of us getting ahead of things but based on what we saw in these three years of study is there's really no reason from what we saw. This is to think that you need to take any special precautions during storage with beets that come from sucrospera infected plants. So that's the conclusion. So this is actually the data of what we've got. What's shown here is the respiration rate. There's three graphs. So a graph for each year, year one, two and three. In the first year we had CLS ratings. We had these four different levels of disease severity. In the first year, our low group had a rating of 3.0 and the most severely infected roots had a 9.8. So we had very severely infected roots. Year two, the CLS ratings were very similar, 3.0 to 8.8 for the highest CLS rating. And year three, there was a higher incidence of disease or a higher severity of disease and the CLS ratings ranged from five and a half to 10. What we did is we looked at, so these four bars, these groups of four bars of the four different severities of CLS symptoms from which these roots were derived. And we're looking at the respiration date at 30 days, 90 days and 120 days in storage. And the first thing you might notice is that there really isn't any pattern when you're looking at these groups of four. Sometimes you see an increase, you see it here. Sometimes it looks like it's going down. Sometimes it's doing something else. And the reason for that is because what you're seeing are these small differences in respiration rate, but it's noise in the data. None of these changes are statistically significant. So it didn't matter if we had beats that came from the groups that with a sarcosper rating of 3.0 or at a 10, we weren't seeing any significant difference in storage respiration rate. And we didn't see it at 30, 90 or 120 days in storage. It's well known that sarcosper causes sucrose to be lower at harvest. And that's what's shown here in the slide. So there's nothing interesting here really, because this is well known. If you have high levels of sarcosper, you're gonna have a lower sucrose content at harvest. But what we were interested in is do the sucrose levels change more or less if you have more or less sarcosper up? And so we're looking here in the second half of the slide or on the right panel at the sucrose loss during storage. And again, the first point to make is none of these beats in any of these years really lost that much sucrose during 120 days of storage. The most we saw was about a little bit less than a 1% loss in sucrose content based on fresh weight. So regardless of severity, we didn't lose much sucrose to over 120 days. And there's no relationship between the severity of CLS with the sucrose that was lost. And again, what we're seeing again is, we see variations, but it's just at the level of noise. There's nothing statistically significant in any of these differences. We also looked at invert sugars at harvest. We didn't really see a whole lot of difference between beats with low levels of sarcosper and beats that had high levels of sarcosper. There were a little bit of variation, but the variation was more year-to-year variation. And again, none of these differences based on sarcosper rating are statistically significant. We also looked at how invert sugars change during storage. And again, we see year-to-year differences, but not differences that are related to sarcosper rating. So if you look at the top panel, we saw an increase in the inverts in year one, really no change in inverts in year two and a decline in invert sugars during storage in year three. But again, none of these changes in invert sugar concentrations are related to CLS ratings. Sucrose lost to molasses was variable at harvest time. And that actually matches with what we've seen in literature. Some people have seen that sarcosper causes an increase in sucrose lost to molasses. Some people have seen no effect. We saw a very inconsistent effect in that year one, regardless of sarcosper rating, the sucrose lost to molasses at time of harvest was pretty much the same. At year two, it was a little bit elevated in the beats that had the higher sarcosper rating. And in year three, strangely, it was a little bit lower, but it was statistically significant. And again, really our interest though is what's going on in storage. And you could just look at the three graphs, you can look at the four bars in those four graphs and they're all pretty much the same. And again, we're seeing no effect of CLS rating on any sucrose lost in molasses or any changes in sucrose lost to molasses that occurred during storage. So essentially nothing happened as far as sucrose lost to molasses. The last trait we looked at is recoverable sugar. Again, this is something that's well known at harvest. You have lower levels of recoverable sugar per ton in beats that have high levels of sarcosper. So we saw exactly what you would expect here where our two higher ratings of sarcosper have lower recoverable sugar per ton at harvest. But again, it's what's going on in storage. So what's shown in this panel is the change in recoverable sugar per ton after 120 days of storage. And you can see while it may look like there's a little bit of an increase here in year three, there's really no consistent effect of CLS rating on the amount of recoverable sugar that's lost in during the storage period. Okay, so just a quick recap, you've already seen the conclusion. So this is just what you saw before. Sarcosper leaf spot has no detectable effect on the sugar beet root storage properties, at least nothing that we could pick up in our studies. And it doesn't seem to matter how severe the rating is because we've had severely diseased beats in all three years of the study. And again, that leads you to conclude or to assume that there's really no special precautions that need to be taken with beats that are derived from CLS infected plants. If anybody's interested, all the full details of this research is available online. It's been published. And with that, I'd like to thank the Research and Education Board, which funded all three years of this research. Our next presentation is identification of new genetic sources from CB to improve sugar beet resistance to the Cosper leaf spot. Good afternoon, everyone. My name is Massab. As I just said, I'm a post-doc and working with Dr. Changin's group. And here I'll be giving you an update on our project, which is to identify the genetic sources of resistance in wild beet or CB to improve the resistance in sugar beets. So first, a brief background on Sarcosper as many of the before participants have already given, but I'll just go through it. So Sarcosper is the most important foliar disease in sugar beet. And it can cause yield loss up to 50%, but the economic losses are also much higher because of the high processing cost that it causes. And the low host resistance in CLS is both quantitative and qualitative. And recently we have seen a CR plus gene, which is a monogenic gene. And this gene is actually also derived from the wild beet, the CB. So it will be interesting to look more genes in that, you know, in that germplasm collection. So right now in sugar beet, we still have the lack of the resistance genes. This is our whole aim, you know, to go and see if we can find more resistance sources in the wild beet. So the wild beet or the beta meritoma is the progenitor of all the sugar beet that we have right now. And for that reason, we believe that since they have been co-evolved with all the diseases, there should be resistance present in them at present as well. So we tested the historic evaluations and we find out that out of the 792 accessions, 132 were resistant with the disease rating of three and less, which is very promising. And this is just a tree graph showing the differentiation of the 2000 sugar beet, not just sugar beet, the accessions of beet in the NPGIS database. And we found out that the beta meritoma once, the wild beet, which is right here, is the 355 lines, which were very separate away from the other sugar beet accessions. So we know the sugar beet is a very new crop. The inception is just 200 years old. And compared to the other crops, it does not have that tools available at the breeders disposable to play with. So having this kind of germplasm, which is away and having a distinct genetic diversity, which is really could be helpful in finding mule or scyfe or diseases and pests. So our focus is on this part to find if we can, to see if we can find new resistant sources on the seed. Some, a little background on the genome by the association studies. So genome by the association studies, it uses SNPs, which covers the whole genome and it links it with the trait. So we have a trait, which is a phenotype, and then we have a genotypic data in the form of SNPs. We try to find out if there is a genomic region, which is associated between the both phenotype and the genotype. The advantage of this is that here, you don't need to make a cross, you don't need to make up breeding population or a bi-paranormal population. You just need a diverse set of accessions, which could be readily used in the field, which is a very big pro, especially in sugar beet, because sugar beet is highly heterozygous and to make a bi-paranormal homozygous line is difficult. So GWAS could give us a really high insight into the, to find the common alleles, which we can use later on for integration in sugar beets. The objective of our studies were to find the resistant CLS lines in the wild beets, and then develop the DNA markers. Sorry, first we will do the GWAS studies. We will see if those phenotypic data, that resistance is associated to the SNPs. And if we find any genomic regions, if they are linked with each other, we will convert them into DNA markers. And then those DNA markers once selected and made could be used in the breeding programs, and which could be assisted in a way that we will save not just the time and we will have high precision in making the true hybrids. The next step will be to identify the candidate genes to understand the possible mechanism of the host resistance. In our study, we had 602 accessions total, and these accessions were collected from 25 different countries divided into seven geographic regions. I'll just go through the results of the genotypic data first. So we did the genotype by sequencing for all the Meritema lines, and we had almost 500K the raw SNP data. After thinning and filtering, we got with 147,000 SNPs, which were spread across all the nine genomes. And the density of this was almost 3.5 KB per SNP, which is very good actually. This is the population structure analysis that we did. It's based on the seven regions that we did. And as expected, we see that the lines which were from the same region, for example, we see Southern Europe here, has more incidence of the lines which are from that region. And that mixture that we found was from the same geographic proximity. If you see in the Western Europe, we have the Western Europe and also we have the Northern Europe. Similarly, Northern Europe, we have Northern Europe and then the Western Europe lines. And the same pattern you observe in Southern Europe and Africa. If we look at the population structure at the country levels, because some of the countries had higher number of accessions than some other countries. So we see interestingly that one country that popped out was Denmark here, had no admixture at all and Morocco. The rest of the countries, for example, United Kingdom has admixture with France and Ireland, which are actually neighboring countries. So it makes sense. Similarly with Italy and Greece and Ireland. So we did again, the population structure using the 602 Meditama lines that we did and we found the same, we observed the same results as previously we had before with the whole set of germplasm, the 2000 lines. And these two clusters that we observed before were very much significant here. And we see that those two were similarly separated out. So this is a graph showing the country's based population structure and the regional based. The whole purpose here to show it is that maybe some countries have the lines which have higher resistance compared to the other countries. For example, here, these France, United Kingdom, Ireland had the highest resistance percentage, including Italy as well. And this Denmark line, there were 21 lines from Denmark and 14 of them were highly resistant. So which gives a good idea that this Denmark has a very distinct genetic structure and also has high resistance. So maybe this is a good source that could be utilized. So we tested our 600 accessions in Foxholm, Minnesota and we detected 236 lines which were found to be highly resistant with disease rating of one to three on a rating scale of one to nine, which is a high number, good number. 33 of the lines were highly susceptible and the rest of the lines were moderately resistant and moderately susceptible. If we look at the disease incidence or CLS rating on the regional scale, we see that almost all the countries have the higher ratings up to seven. But I mean, these countries, they had only few lines. So I mean, they are not very significant here. The important was the Denmark that we studied, then Italy, it has a higher number of resistant percentages and as well as France and England. So we did the preliminary GWAS studies and we found out that there were 15 SNPs associated with the phenotype on 14 genomic regions across all nine chromosomes. And these were the results of those 15 SNPs. These SNPs explained up to 4.5% of the phenotypic variation. After that, we did a genome scan in the nearby regions of those SNPs to see if we can find any or we can predict any gene which could be responsible for the resistance. So we found some genes which are directly responsible or directly involved in disease defense mechanism and there are other genes which were not directly or you can say which were indirectly involved in disease resistance. So in conclusion, we had identified 236 lines with disease resistance of three or less. And these resistance accessions may be associated with the geographic region where they are from which has to be looked further on. And the GWAS, we detected 15 SNPs and these SNPs will be, I mean, we will have another data next year and we will see if these SNPs remain in the next year as well in the next application. And if it happens, then we will have an idea of, we will see if we can convert those SNPs into the markers. For next, we will focus on the 300 lines that had the highest disease ratings. Sorry, by highest I mean the highest resistance rating. And we will test them again in the applications in multiple locations and we will use control conditions this time. We'll try to do more inoculations. So to produce higher disease pressure with a missing education system and other practices. So this was all, I would like to thank all my team members and also Dr. Melvin Bolton, the group, Dr. Changan, who's my advisor and SugarBeat R and E and to all of you. Thank you so much for being here. Okay, our next paper is evaluating C particular populations over time to determine fungicide resistance in SugarBeat being presented by Sushmita Kalikasingh and co-authored with Dr. Khan. So my name is Sushmita Kalikasingh. I am a first year PhD student in the Plant Pathology Department at NDSU. My advisor is Dr. Mohamed Khan and my task this afternoon is to walk you through my presentation which is based on an evaluation of sarcospora beticola populations over time to determine fungicide resistance in SugarBeat. This is the outline in which the presentation will follow which includes a brief introduction to SugarBeat. Some solvon or foliar diseases affecting SugarBeat especially sarcospora beticola the use of fungicide mixtures and CR plus varieties to control or manage sarcospora beticola and the future direction. So let's get into it. Beta vulgaris commonly known as a SugarBeat is commonly produced as a source of sugar. The juice of SugarBeat contains high level of sucrose and although the commercial use of SugarBeat is for processed sugar there are several other uses of SugarBeat. The process of processing the beads to sugar the byproducts, molasses and pulp they can be used as a livestock feed and they can be used in commercial baking and pharmaceuticals. This map is showing some of the states that produces SugarBeat in light blue and here we can see Nardakota and Minnesota and the red is showing the states that have SugarBeat factories. In 2020, Minnesota produced the most SugarBeats in the states followed by Idaho and Nardakota and from this table we can see if we add the production from Minnesota and Nardakota they produce approximately 50% of the SugarBeats in the states. So some soil born are foliar diseases that affects SugarBeats are a fun of my seeds which causes root rot, rhizomania which also affects the root, fusarium which causes fusarium yellows, claritinus, claritorium which causes leaf light, sarcospora and alternatoria leaf spots. However, the main focus of today is a sarcospora leaf spot which you already heard a lot about and this is caused by sarcospora bethicola and it poses as one of the biggest production problems in Nardakota and Minnesota because this disease results in lower tonnage as well as lower sucrose concentrations which could result in losses of up to 40%. This fungus is spread from field to field by wind and the infections developed rapidly in warm and wet conditions. This disease is favored at a temperature range from 25 to 32 degrees Celsius and with a relative humidity being more than 85%. And individual spots, sorry, individual spots individual spots, they usually occur on older leaves and then they progress to younger leaves and the spots, they are usually ash color in the center and they are purple or brown on the borders and they are circular to over shaped. So this is what a healthy field, sugar beet field looks like from 2020 in southern Minnesota. However, this is what an unhealthy sugar beet field looks like when it's infected with sarcospora leaf spots which gives the plants the appearance of being burnt and scorched. And the varieties used here were the normal commercial varieties that are available to growers and these varieties they are becoming resistant to individual fungicides such as DMI and QOIs. And this graph, it is showing the effects of individual fungicides on sarcospora leaf spot severity and the recoverable sucrose. And here you could see in the non-treated check that the recoverable sucrose was under 10,000 pounds per acre and the severity was 10 and anything above 5.5 severity is considered as an economic threshold to growers but when we use the individual fungicides such as Inspire which is a DMI, you can see that even here the severity of 5.5 is exceeded. However, when we use fungicide in mixtures and they are alternated, we can have better results. And this year was a very wet year and the conditions were favorable for sarcospora leaf spot. And again, we can see that the non-treated check had a severity of 10, but when we use fungicide in mixtures, the severity dropped to 5.5 and the recoverable sucrose per acre increased to approximately 5,000. And here this picture is showing how the favorable environment conditions resulted in severe disease severity from September 2nd to September 24th at Foxholm with the CLS rating being more than five. And when the conditions are dry, this was a dry year, if we use fungicides in mixtures and they are alternated, we would have even better results than the wet year. And again, we see that the non-treated check, the severity was 10, but when we use the fungicides in mixtures and they are alternated, the severity dropped below 5.5 ranging from 3.8 to 4.3 and the recoverable sucrose per tonne, it increased to over 13,000 pounds per acre. And these pictures, they are showing what was stated and you can see from the non-treated check that when we use the fungicide in mixtures, they perform better. And this picture is showing a field trial where individual fungicides and fungicides in mixtures were used. They were applied five times and it was found that only the fungicides using mixtures were effective and this can be seen in the areas where we are seeing less severity. And this picture is showing another trial where fungicide mixtures alone were used in rotation. And we can see clearly that this, what more treatments were effective here compared to the previous. And if we, since the weather can be unpredictable and we can protect our sugar beet from sarcosporobesicola by using CR plus varieties which Dr. Seeker would have mentioned earlier. And this variety is better to use because it is somewhat tolerant or resistant to sarcosporobesicola and it produces better results, production and protection from the disease. And also this variety can reduce a number of fungicide application used and keep the disease to a minimum which can be seen here. And we have two CR plus varieties which is the ACH which can be seen on top and the BTS or the beta variety which is at the bottom. And for each variety we have two treatments where for each where we have a non-treated check and here we have a treatment where applications of fungicide was done before real closure and then a 28 days interval and then fungicide were applied as needed which means they were applied when spots were seen. And this graph is explaining the data from gathered from that. And it is actually showing us that not all of the CR plus varieties are the same. Here we can see that the ACH variety is performing better because the recoverable sucrose is higher compared to the beta. And also we can see that in both you don't need to apply fungicides at 28 days interval because when they were applied as needed they produced the same result as when it was applied at intervals. This picture is showing what the non-treated check would look like if we use the normal commercial varieties. And this picture is showing what the non-treated checks look like if we use the CR plus varieties which clearly shows that this is a better variety to use. And Dr. Kan and his team they have been collecting samples with infection for the past seven years and I will be using those samples to determine in laboratory and greenhouse the temperature and humidity required for this pseudo stromata of sarcospora bethicola to germinate and cause infection on healthy sugar beads to determine the presence or absence of gene mutations from sarcospora bethicola populations exposed to the major fungicide classes such as DMIs and QOIs and to evaluate the two CR plus varieties for the levels of susceptibility to different sarcospora bethicola populations. Okay, the next paper is entitled Optimizing Fungicide Timing for Management of Sarcospora Bethicola in Sugar Beans, CR plus varieties being presented by Sunil Bhandari and it's co-authored by Luis Del Rio Bendoza and Mohamed Khan. Thank you so much and I'm sorry. I'm Sunil Bhandari, RPSD student at NDSU and my supervisor is Dr. Khan and today I'll be presenting on optimizations of fungicide applications for management of sarcospora leafy spurs on CR plus varieties. The two CR plus varieties recently released by KWS and here is the basic outline of my presentation today. I will like to skip the introductions because we already knew a lot about the sugar beads it's growing reasons and many other things. So sarcospora leafy spurs, this is actually a very well-known pictures. We know it's life cycle. Generally the spores when they gave the way, sorry, when the dispose into a susceptible host, sugar beads, they will germinate and penetrate through the stomata and enter inside the leaf tissue and produces this characteristic spores which we call sarcospora leafy spurs. And within these spurs, there may be hundreds of pseudo stomata which are actually a conidicinous cell that can produce thousands of, okay, that can produce thousands of conidia which again disseminates into the field and produce the cycle again and again. So this cycle typically we call polycyclic cycle. And again, when this happens, the polycyclic onset occurs, the field will turn into a brunt and we then that again, this pseudo stomata again overwinters and then in the next season, when they gave the suitable environment, they produce the conidia and the cycles keep continue. So I think the picture quality is a little lower, I think, but we all aim to get this healthy field and this is what happens when the field is infected with sarcospora. And we need a better management practices and we know some management practices like integrated practices when in which we use crop rotations and incorporations of the infected residues. These can reduce the chances of infections but that cannot fully reduce the chances. For that, we want to get a better resistance through host resistance and also the fungicides. So today we will see both of them, how the new varieties that has been developed by KWS reacts in response to the vital response as well as the fungicide applications. And these ACS 973 and Beta 7029 is the recent product produced by KWS using the Beta Maritima, which is actually a wild type CLS resistant plant and they incorporate this CLS resistant trade into our commercial cultivar and then through the continuous back grows and selections, they finally produce these two varieties and it took actually 21 years for this production. So it offers stronger sarcospora productions even in the higher disease pressures and also the yield performance is similar to the current cultivar. So the objective today is to see the fungicide efficacy of the common fungicide that we use on these two varieties and we'll also see the fungicide efficacy on current commercial cultivar crystal 572. So for this research, we have started plantations on 23rd of May and on 8th of July, we inoculated the field with all the plants with sarcospora inoculum using the previous year leaf residue, infected leaf residue and we apply the fungicide as needed and based on our plan. We actually plan 10 treatment strategies. I will show you later. And finally, on 27th of September, we harvested. And here you can see the list of fungicide mixes that we have used during this research. We have started with suppotin and bath mixtures. Then if needed, we go with another mode of actions, fungicide. We are just rotating the fungicide so as to reduce the chances of getting fungicide resistance. So for treatment strategies, we have 10 treatment strategies with non-tutile control as we pause. Then we have one treatment at before row closure using 10 to 14 days calendar interval. Then we have three treatment at row closure using 10 to 14 days interval with 20 days interval calendar and based on the daily infection value that we monitor from and on. And we have another three sets of treatment at disease onsets. We'll apply fungicide with 10 to 14 days calendar interval at disease onsets with 20 days interval at disease onset and we'll start looking at DIV again. If the DIV threshold goes beyond six, which is actually called the threshold for CLH, then we'll apply the fungicides. And finally, the three to 5% severity level. If the plant reads at three to 5% severity level, then we'll apply fungicides with 10 to 14 days interval. And after reaching three to 5% severity, if the DIV goes beyond six, we'll again apply the fungicides. I think he was asking about like, what is the actually as needed applications? These are the as needed like, if the threshold reads beyond DIV, that is the as needed. If the threshold reads to three to 5%, these are the treatment we have planned this year. So this is actually our field at Paxom Minnesota. This is Beta 7021 and SCS 973. These two are the CR plus and we compare all our onsets with current commercial cultivar Crystal 572, which is actually a substantial one. So we inoculated pathogens on nine of July and the plots, it is not well clear here, but they don't have any pathogen or onsets at July 15th. Again, they don't have any pathogens at August one, but on August 6th, the Crystal developed the first symptoms in the field. I put the data database on the 15 days interval, but on August 6th, we have first spots on Crystal. And these CR plus variety developed spots two weeks later on August 20th. So these have a delayed circus for induction based on, sorry, compared to current commercial cultivar and on August 31st, those two field still look more healthy and green, but this has turned into a yellow and a little bit brown. So the incidence rate was very high in Crystal compared to these two CR plus. So here are some pictures. We have been to our field at 30th of August for our extension tour. And I think many of us were there at that time. The plots at that time, that's look really green and healthy, but after two weeks, when we have another tour at that field, the plot has turned into brown and scorsi. And it is, you can see in the other screen and you can see the plots in the back of Dr. Khan, they were turned yellow and brown. So the yield potential of these two variety when compared with the CR plus, you can see the yield or cultivar main between Crystal and the Beta 7029 is not statistically significant, but it's a little bit different in numerical term. But ACS 973 has little lower yield at this time. And if we see out of 10 treatment, we have applied the treatment six and nine were statistically different. Otherwise all the treatment were not that different. And this data, the Crystal has more yield compared to other two CR plus variety. It was really resembles the data that Dr. Khan recently presented because the Eastern count on this one has significantly higher. Normally I have data. The ACBeta 7029 has Eastern count of 142 and ACS 973 has 149, but the Crystal has 192. So this high Eastern count contributes to the high in potential of Crystal 572 this year and the research conducted by Dr. Khan in previous years shows that if we have a dry wet season, the potential of Crystal gets maximum. Similarly, based on the number of applications, you can see this is for CR plus variety, both of them, the treatment one is untreated control and treatment nine and 10, we applied when the severity reached at three to 5%. So in both of them, the severity never, even in the control, it never reached to three to 5%. So we don't have any applications on nine to 10 treatment. And the CRS rating, you can see it was below two in beta or CR plus varieties. So based on our schedule or plan, we applied the fungicide even it wasn't as that significant to say like we actually need say fungicide applications with in 2022, since we have very less disease pressure at that time and disease started very, very late. So if the year is like 2022, we actually don't need to spray on CR plus beta 7029 and SCS 973. While if we look at the Crystal 572, the untreated control, which doesn't have any treatment, it has the disease potential, disease severity of 8.8. And we have to apply to the three to 5% severity, even the disease potential was very low, but they crossed the three to 5% severity. So we applied and this was so, this shows that the treatment after reaching three to 5% threshold is not effective to control the disease because severity is above seven. But there are some treatment, these which are done at before road closure and after road closure and they have more treatment compared to other, these treatments are actually good for controlling CLS. You can see the CLS rating is very low. But if we look at the application cost, because they have higher treatment, the application cost was really high and there are two other treatment, treatment seven and eight. If we look, the CLS rating is still under the economic threshold. So, and if we see the application time, we applied four times in, four times CL, sorry, treatment six and three times treatment eight. The cost for these applications is just under $70. So if we are using Crystal 572, these two treatment can give a better control. But if we wait for a later applications, then the cost is almost comparable but the disease intensity or disease severity will increase very high. And you may wonder like, how the cost of four treatment in this case is just under $70 and the same, the three treatment in treatment five was $105 because we are using mixer fungicides and in rotations, the mixers or the cost of the fungicides makes this difference. So these are the real results. So beta 7029 when treated treatment five with three applications, the plant has disease under 1.5. It's control source, very untreated control actually has very less exposed, we can see. Similarly, the ACS 71 treatment with treatment four with three treatment or three applications has no disease and the control has also the untreated control has very less disease, but the Crystal, the similar results we only get after six applications with treatment two, which was it before row closure and the untreated control has very high disease which are above seven. So in summary, the ACS 793 and beta 7029 was significantly tolerant to the CLS compared to the standard susceptible crystal and in susceptible variety calendar-based treatment prior row closure and after row closure seems to control effectively but it is not seems economically viable because the application cost is higher. The disease severity on CR plus variety never raised three to five percent. So if we have year like 2022, disease induction was late and disease density, sorry, disease severity was low. We actually don't need any applications at that time but we need to monitor our craft frequently. And the sugar yield was higher in susceptible variety as Dr. Son also mentions, there are some reasons late season dry environments and high stand count contributes to the high sugar rate potential. But if we have a late wet season, then CR plus showed the higher yield potential. Dr. Khan already conducted that experiments last year. And further recommendations for CR crystal 572 we can recommend the applications with 28 days calendar interval and this is answered followed by DIV which is actually four applications and two applications can give a better control for surface quality spots. So future work regarding this the further analysis of this CR plus variety will be needed at high disease pressure and evaluations of genetic variability between those susceptible varieties see crystal 572 and CR plus variety which is still got infections. We will conduct the variability among them. And finally, I'll be working on the multi-spectral analysis of multi-spectral analysis for early detections of these surface for an ultra area and let's take a bit fail using UAV techniques. So if you have any voices, then I'd be happy to answer. And our next presentation is early detection of such out of the big one, what infection in MRTL sugar beet fields and the impact of CR plus resistance on pathogen population. Hi everyone. My name is Nate Wyatt. I'm your local USDA research plant pathologist and sugar beet epidemiologist. And today I'm gonna talk to you about two projects that we've been doing in large part in collaboration with Gary Secor's lab, Viviana and Dr. Melvin Bolton. The two projects are latent detection of CLS infection in commercial fields. And briefly I'm gonna touch based on some of the monitoring we've been doing of the Sercasa population and its response to being introduced to CR plus genetics on a broad scale in the Red River Valley for the first time in 2021. So keep in mind, I'm gonna be talking about 2022 data up here and 2021 data here because we now just have the 2022 isolates from this year to do this analysis and see if that's consistent. So jumping right into latent infection, the reason we were interested in this study is because we're trying to get a really good understanding of this disease cycle timeline. And primarily we're trying to get an idea of when infection starts following planting, which this year occurred mostly in May unless you had a boat that you could pull your planter behind. And then after the latent infection starts and we've established a trend line for that, we're interested in then what factors then happen in between latent infection and symptom development. So that's what we'll be working on moving forward into the future. A little bit of background on this process. So as Gary mentioned, we've been using molecular markers to detect sarcospera DNA in asymptomatic green, healthy looking sugar beet leaves. And one of the nice parts about working with Dr. Bolton's lab is they've already developed these molecular probes for mutations that are specific to sarcospera's resistance adaptation to QOLI fungicides, DMI fungicides and topsy. And these are really useful because they're incredibly specific to sarcospera. And in the case of the cytochrome B marker, the QOLI resistance target is cytochrome B in sarcospera particular. And this is really useful because it's a multi-copy gene, which just means that we can detect sarcospera at a much lower threshold because we're detecting two times as much DNA as for the other two markers. How this process works is we get sample shipped to us and we punch holes through the leaves. This last year we did about 10 punches per leaf and then that goes into our processing where we drive the leaf and then extract DNA. And then that DNA goes into our molecular assay where we get fluorescence curves where if they pass a certain threshold, we can say that that's positive for CLS. And if they never make that threshold, obviously they are negative for CLS. Now in 2021, a pilot study was done primarily by Joe Hastings and his team looking at exactly the same thing. So CLS late in prevalence kind of in the Moorhead district of Crystal Sugars growing region. And one of the things that's important to note here is that they actually were able to sample early enough to capture what we would consider a zero time point. So no infection detected in these 31 fields that they were able to sample. Detection as you would expect rises as the season goes on with first spots detected in at least one of the fields as early as the 6th of July. And this kind of curve immediately gets us thinking about what kind of weather events lead to this initial detection. Because we know from Gary's data that we have spores in this year specifically as early as May 3rd. So you have spores that have clearly been exposed to the sugar beet almost a month before we start detecting latent infection. Now in 2022, we decided to expand on this project by sampling 280 commercial fields across the entire growing region. We had agriculturalists from all three co-op submit five leaves per selected fields for four to five weeks. And because we have these marker sets available to us we decided to run each of these resistance markers to see if we could also profile the latent infection fields for resistance to DMIs, QIs and topsoil so that theoretically in the future if we can establish that this is consistent we can make decisions on first fungicide applications based on the resistance profile present in that field. Now in 2022, we actually see essentially data mirroring what was observed in 2021. Right away we started sampling at the four to or three to four leaf stage which typically occurred around the middle of June this year rising prevalence until approximately 100% prevalence by the fourth week of our testing which would be the 7th of July. And CLS symptoms were visually detected on some of the submitted leaves by that point as well which if you remember from just two slides ago first spots were detected in 2021 in select fields on 76. So approximately the same. And one of the interesting things about that and also useful things about that is that you have very different weather patterns leading up to this and that allows me then to go in and look at the different weather data that correlate with this latent infection kicking off and really start to cross out things that are clearly different between these two years. Now before, so because we ran multiple fungicide resistance markers we were able to get an idea of how fungicide resistance or spores that are initiating latent infection in these fields, what their resistance profiles look like. And one of the main things we see is that initially QOI resistant isolates were dominant on these latent infections but that was usually during what we would call low prevalence latent infection. So when samples were of the 280 samples we were getting in the lab, they were around 20 to 30% of those were positive for CLS infection. Now that the resistant to sensitive frequency here it collaborates as we move on into the season. And so really by the time the season kicked off we had about a 50-50 ratio of those resistant to sensitive isolates detected. Now for Topsin it was a very different event. You had sensitive isolates being dominant in the early season and then as prevalence rose so did the resistant detection of resistant isolates in those fields. And now I'm gonna show you some DMI results but before we do I have to touch base on the different mutations that can lead to DMI resistance. So this work was done in Dr. Bolton's lab. They used a genome-wide association study in a large circosper of a particular population to identify the mutation E170 and L144F. Both of which when this mutation from a G to an A in the DNA of circospera happens you get an increase in resistance to tetraconazole. Same thing happens here with the mutation from this G to this C where you get this big jump in resistance with either of these two mutations. So one of the things we wanted to do is validate the utility of these two markers for determining resistance to the DMI fungicides. And so in order to do that we paired up with Dr. Gary Seacore and Viviana and I'll spare you all of the materials and methods behind this but essentially in a very large almost 600 isolate population from the Red River Valley. Viv very painstakingly went through and phenotyped on serially diluted fungicide plates resistance profiles for eminent, proline, inspire, and provisal. And then they handed that data off to me and I was able to go through and cross correlate our marker data with whether or not it's predicting resistance. And a couple of things to point out here in that population cross resistance from proline and eminence, which were essentially the same in this year to inspire and provisal was as high as 98% and the inverse is not true where we actually see that inspire and provisal resistance is only cross resistant to proline and eminent 67% of the time. So what this is telling us is that the two mutations may have a different effect on resistance to different DMI fungicides. And that's actually what we see in this data. We developed a little flow chart using E170 and the mutation you identify and L144F and the two different combinations of mutations you can identify. And the important part of this is that if we use the marker for DMI resistance from E170 and the marker for sensitivity from L144F and you go down this chart we are able to accurately predict resistance to each of these four DMI fungicides at 96% accuracy and 96.3% accuracy. So this one up here, 96% accuracy being for tetraconazole and protheoconazole which would be eminent and proline. And then 96.3 would refer to definite conazole and the ventral flu conazole. And that would be inspire and provisal. So if you are interested in how we've verified the accuracy of these markers come and find me I can run you through all that data later. But essentially what we see in 2022 is that resistance to proline and eminent rose as prevalence of latent infection rose in the fields. And the exact opposite was true of inspire and provisal. And we were able to take a look back at some of the fungicide application data from the previous year. And oftentimes what we found was that inspire and provisal were some of the first DMI's applied. And which were then followed by either a tin, a top center, another fungicide chemistry. And in regions where DMI was sprayed twice we would see proline sprayed last which is I think why you see proline resistance at the beginning of the year starting off high and inspire resistance essentially having the opposite trend where you're mostly detecting sensitive isolates. So a couple of takeaways from the CLS latent study results in pretty much mirror what we see in 2021 which is promising because as we move into doing this study in 2023, this is gonna give us a really good foundation for modeling the environmental effects that are leading to the development of CLS latent infection in both years by the first week of July, sorry. So in the first week of July we have first spots detected but in 2022 we had approximately 100% prevalence of CLS latent infection in all fields tested. And our earliest isolates are usually detected for QOI resistance, Thompson sensitivity, inspire and provisal sensitivity, eminent and proline resistance. And this has a trend where it correlates very well with previous year's fungicide usage. So one of the things we're really interested in moving forward is diagnosing whether or not any of these things, so any of these fungicide resistance profiles that we see when we compare between years have any effect on fitness but that will, or those studies are still ongoing. Last but not least, I wanted to touch base very quickly on some of the work we're doing on CR plus, specifically on how Sercasa in particular is adapting and trying to warp around this resistance because the pathogen will always try to evolve around anything you throw at it. And what we've seen through our whole genome sequencing of 100 isolates from both CR plus and non-CR plus material, so it's 100 and 100, so 200 total isolates. What we see is that the isolates coming off of CR plus material are a reduced diversity subset of what we find in the non-CR plus population. So there's no, at this point, there's no specific mutations that we've observed that we would say are now CR plus virulent. However, it's this first stage of evolution where the weed out cycle happens and this bottleneck has occurred where only certain isolates are able to make that jump on to CR plus genetics. And you could think about it a little bit like if you go to an amusement park and there's a ride that says you must be this tall to ride, that's what's happening to our isolates moving on to CR plus diversity. And so what we would anticipate moving forward is that these isolates that can infect will begin the process of adaptive evolution and trying to optimize their virulence on CR plus moving forward, which is why we'll continue to monitor this moving into 2023 and we've got 2022 data coming to match this 2021 data set. With that, I have a few quick thank yous to make. First off, the sugar beet research and education board for funding of these projects, Dr. Melvin Bolton's lab and specifically John Newbauer who helped me get set up with the DNA extraction machine, the QPCR assays and did a lot of teaching involved or taught me a lot of things during that section. Also Dr. Gary Secor's lab and specifically Viviana because Viviana has done an immense amount of work with funder side resistances and they were able to hand me a ton of data which is a joy for me. And then Joe Hastings, Mike Metzger, Emma Burr, Mark Bloomquist and all the agricultural staff from those three call from Crystal Sugar, Bendak and Southern Bend because without them and their ability to collect and send me leaf samples for this study it would have never happened. With that, I'll take any questions you might have. Our final presentation is, I've got a lot of notes here. Lessons learned in managing Sercospro particular in sugar beet presented by Dr. Mohamed Khan. Good afternoon and thank you. Thank you for waiting to this late hour. All of you are informed that I've been around for 24 plus years. So I will share with you in the next 20 minutes or so some of the lessons learned. And as I told you earlier, I'm a slow learner. Some people say I never learned. So I'll share my little story more or less using pictures. I'm not very good at reading. So I'll tell you some stories about some basic research because when I started working with Lee Spott say for you to manage your enemy, you must study and know him or her. So we studied the basic biology. I'll tell you some stories about that. Gary, I'm getting like you can barely see the computer. You want to bring it up a little bit closer to Mark. I will discuss a little bit about site specific fund decides. I thought a little bit on resistance when it happened, how it happened, the use of multi-site fund decides so that our industry could be saved and CR plus varieties, which you heard a lot about and then an overall management strategy so that we can keep these CR plus varieties for a long, long time. So customer started way back in 1876 in Italy in a few years because we were importing seeds from Italy. We brought the seed as well as the fungus. Was it on the seeds? Was it on the debris? We're not sure probably seedborne. There's lots of work to show that. We weren't too sure how long the fungus survived in the soil. So I did some work, imagine a short brown guy but a lot of lady pantyhoses having brown leaves smelling like, you know what? Putting in these hoses, bearing them and then coming back either one year, two years or three years afterwards and checking to see if these pores will survive. We had them on the ground at four inch and eight inch depth and what we found was that those that were not buried that were on the ground could survive for over two years and cause infection. If you bury them, they decompose and after one year they are gone. So anything you can do to decompose the debris which has a pseudostromata will reduce your fungal population. We weren't too sure about spore trapping. So we decided, first of all to be innovative and those were, that was a long time ago. Fluid intelligence was working then. So we use coffee cans, different sizes, different heights, different directions. We use Elvis Presley, his Vaseline from his hair with some slides and we were able to collect Sarkospora so much so that we then moved on to pressure cooker. We had a lot of pressure cookers converted into spore traps and then we also had spore traps. We found that you can collect spores and at one time in the early 2000 I would probably provide information to Alan Katana, Tyler and others in June and when we found the spores in the field they'll say the tradition was if it were warm and wet about two weeks afterwards you'll see leaf spots in the field. If it was dry, it would probably take about three weeks. I worked with Dr. Larry Smith at the University of Minnesota Crookston. He had some resort site with Sarkospora and this was where we kind of found it was easy to collect the samples using different spore trapping methods. The cans was of course a system whereby the wind will just blow the spores in. The bar cow spore traps was actively pulling in spores. They had more spores in those spore traps. We also wanted to find out where these spores were coming from. We were recommending to producers and all of them were doing this here having three years rotation some of them a little bit longer. So if you had rotation did you have spores in those fields that you had beats maybe four years ago or were they coming in from the previous year or previous years, two years of inoculum? And this little trial that we did here where we had bare soil or the soil was covered with plastic and then we use a cage, put it over the bare soil or over the plastic. We found that once we had a plastic cage you had very little to no disease which meant the spores that you were getting in a particular year once you followed crop rotation system were coming from previous years more or less inoculum. That's what this graph is kind of telling us here. And this is published in plan disease if anybody needs to look at that. Now once upon a time we used to do surveys with all our producers and it told us a story as to how many applications of fundicides were used and they were also honest enough to tell us if these fundicides were working or not. Way back in the 80s, in 87 we hardly use much fundicide. In 1995 we use more fundicides because we had a small epidemic then and in 1998 when we were using mainly tin and a little bit of Mancozeb we had an epidemic because the tin was not working. We saw from Dr. Seacoal's data that over 65% of the sarcosper isolate collected were resistant to tin. So our growers lost over a hundred million dollars because of the disease. The growers in the southern area where it's warmer, wetter and they start planting earlier had many more applications compared to growers at American Crystal and Mindac and they probably lost the most money as well. As a matter of fact, after their hands were burnt so much they continued to apply fundicides year after year three or four times sometimes when it were not needed just because of the fact that the disease was so severe. You can see based on this graph here that after 1998 by around 2003, 2004 growers were using at one time just about two applications per year and these are growers in North Dakota, Minnesota most of that was used in the southern areas in the northern area they were probably using just one application. And I'll tell you the story about that why from 1999 to about 2015 it were more or less glorious years because sarcosper was well managed. This is the year of Lord 1999 the previous year we lost a hundred million dollars we did not need to inoculate. This is the plot, you came on July 4th you already had symptoms you've got the rows were closed the varieties that we had were very susceptible. Tin applied four times this was what was being used a year before they were not effective because of resistance issue what saved us was the fact that we had eminent we use eminent tin eminent in a rotation program from 1999 to 2002 and that's what saved our industry. From 2003 we had the product called Headline which was one of the best product that we have ever used for managing sarcosper Leespot but we have to be careful and I want you to remember this. Headline was one of our best product I'll show you some data that by 2016 it was no longer effective. Today CR plus varieties is one of our best tool let us not let our CR plus variety go the way that headline has gone. So we use eminent headline and eminent again from around 2002 to 2005 our roles use rotation one product at a time at about 14 days interval starting around the middle of June of July excellent control. At the same time when we were doing this here we saw the tin which you just saw just now was not working in 1999 because of the fact that we were using two other chemistries these DMIs and QOIs wiped out those resistant isolates so much so that by 2005 using tin alone was just as good as anyone of the site specific fund decides. So what did we start to do after 2005 our growers now had once again an additional chemistry in addition to the DMI and the QOIs the tin which was just as effective in their arsenal. So for a number of years from 1999 to 2015 you can see when we use fund decides in a rotation program three or four applications be it in the south or in the north you had excellent disease control, high recombinant sucrose and we were in the business of making money. In the year of the Lord 2016 it was the warmest and wettest of 122 years of record keeping in Minnesota. It was good for sugar beet production. They grew, they loved the heat, they loved the water but so did the fungus. And one of the things about Sorkospera it multiplies and it multiplies rapidly. In one season you can have five or six generations and each acre you have over a trillion spores. So you have large numbers. If you control 90 or 95% you can still have serious infection. So this is what happened in 19 in 2016. So a lot of these pictures here the one to your left to your right was taken at Fox home where the growers were using headline as the third application. Most of our growers at that particular time headline was the mantra use it around the 25th of August. You'll have good leaf spot control. You'll have high recoverable sucrose. If you're in the northern part of the valley you'll have frost protection. Those fields start to look brown. This was our grower field. He applied two more fun decides and nothing helped. And that continued. And the reason was as explained earlier we have QOI resistance. It was full blown. But not only was there QOI resistance. Please take a note of this picture here. This was taken on our plot tour on the 29th of August. The 29th of August. This is a check top left. I'll show you a picture that we had in 2022 of the entire site. Piaxol which is part of which has headline inside it. As I said was one of our best fund decide. By 2016 you had resistance. The rating was similar to the check. Your trials old which was just as good as your headline also started to become ineffective so much so that some of them were not very much different from the check. You can see the QOIs. It didn't matter if you were using headline or gem or pyroclastrobin which had become generic. They were not working because of resistance issues. The trials old they didn't matter which one of them we had. They were not working. We tried biologicals. They too were not effective. What saved us was tin. A multi-site fund decide that was working from 2016 and it is still working today and I'll show you some pictures with that. What we also saw, we couldn't just use tin alone. We had to use some of the trials old and the one that has consistently been most effective has been proline. We've seen that if you had trials old or an EBDC or a copper multi-site fund decides to the trials you have better disease control. You'll see some pictures whereby once you mix a tin by itself with anything else it will be good. The numbers tell you the same thing and this is also very relevant for the growers in the north and our growers throughout the valley based on the fact that last year we didn't have much disease throughout the production area even in southern Minnesota where you have the most severe disease. There are certain multi-site fund decides such as mandate, the coppers and the tin that are able to give you excellent disease protection without using a QOI or a DMI. Mancosibid is a mixture of a copper and a EBDC. If you add a copper and inspire it works well and the story goes on the same for an EBDC and proline. So for a number of years of our growers if you apply fund decides in mixtures after 2016 in a rotation program and in nearly every one of those application you had a multi-site fund decide especially EBDC or a copper you had excellent control. We also saw especially at the Fox home site without using a DMI or a QOI without using a DMI or a QOI you had excellent disease control. Here again this is another message that we may be able to use this in a low disease year or low disease years. So when it's dry and you can apply your fund decides without getting washed off you're in good business. What happens when it's wet? In the year of the Lord 2020 we could spray over and over again every time you sprayed a day or two afterward you'll have two inches or three inches of rainfall. When this disease rating was done the CLS rating for the check was 10. We did five or six sometimes seven application when the checks had 10 the ones with fund decide had about 5.5 but by the time of harvest you couldn't tell the difference between the checks and those that were sprayed and don't blame the fund decides. It's just that when you apply the fund decides the rain will come, it'll wash it off. So all you have is the inherent resistance of the hosts to withstand the disease and none of our varieties were capable of doing that as this picture clearly tells. This was the Fox home site anything that you see there that looks a little bit green those were CR plus varieties. Everything else that we had all the other commercial varieties were all brown no matter how many applications we made. I told you earlier I want you to remember the date August 29 this is August 26th. This is a site with susceptible and CR plus varieties. We inoculated this as well. And still as Sunil told you earlier with the CR plus varieties we could not find spots. We could not find spots even one spot until the 20th of August. We had our plot tour on the 30th of August a number of you were there. And one of the things I've learned from my early days in planned disease was you have to get a susceptible host a very lent or very infectious pathogen and the environment must be favorable long enough for us to get infection. That has not changed over time and no matter how much inoculum I put a picture to the top and the bottom shows that all varieties including CR plus varieties that I have up there at cartilaginary stage throughout their life, four leaf, six leaf this one was at six leaf stage they are all susceptible to sarcox probeticula in greenhouse condition. In greenhouse condition if you make it warm if you make it humid and you put all three things together you have disease. At the same time these varieties were in the field they were inoculated and we didn't get any infection until July at August the 20th. Way back in 2002 when we were trying to improve a model I did work in Fox Home, I did work in St. Thomas and what it kind of told us then based on daily infection values and when we apply fund decide was if you apply fund decides if you were to apply fund decides starting when you or your neighbor see the four symptoms or a district and you continue to apply fund decides at least 14 years afterwards based on the presence of symptoms and DIV values you will have excellent disease control if you don't have too much rainfall. That held true then it will still hold true now. The one thing that we have to take into consideration is that time is money. You need to go out into the field and to scout to make sure you can apply at appropriate time and then do it in a timely manner. So what we have seen in the fields for a number of years now is that in our trials we inoculate it and you can talk to my other colleagues who inoculate you can inoculate one, three, five or 10 times as Dr. Katana when he was inoculating way back in the eighties in Fargo he will go out in the morning, he will go out in the night and he can spray and he can inoculate if that weather is dry you don't get any disease. So what we were seeing at Poxum for the past several years a lot of times especially if it's dry the disease does not come up until very late in the season. And in my 24 years of working with fundicides it was only around 2005 and 2022 that the disease came up so late and in some trials in some trials the non-treated check was not significantly different in yield or recombinant sucrose than those that you spray several times just because the fungus was not infecting. So yes you can get infection it usually happens late in the season in this particular case here the picture on the top left was taken on September 8th. As we spoke earlier we do have CR cross varieties they are not immune. I showed you pictures from cutilinary stage throughout the lifespan they are susceptible if you have the right environment and the right load of inoculum. In the field it seems that it take a much longer time than susceptible varieties but we have to be careful and make sure that the fundicides we use are effective at controlling them. The one of the sad thing about this new tool is that it's so good it's so good that sometimes you apply fundicides and you're having accident controlling you're thinking it's the fundicide no it might just be from the natural host resistance and if you're using fundicides that are not effective that are not effective at controlling the pathogen after a time we can lose this new technology. Now we have low inoculum right now we have CR cross varieties some of our fundicides are not working is there anything new on the horizon? Yes we have QOIs the quinone outside inhibitors that's the strobilurins but they're gone. There's a new chemistry called a QII quinone inside inhibitor. Several years ago I went with Gary Seiko to Germany to see to get the ASF to give us this product which was first announced. Unfortunately they couldn't give us. Right now Corteva is working with this product here and hopefully ran 2025. 2025 I hope you can push them to do it a little bit earlier. This chemistry is different from QOI and it can control isolates that are resistant to QOIs. I will expect it to also control isolates that are resistant to the other modes of action. This can be a game changer for the sugar beet industry to help preserve our CR plus varieties. So I expect based on previous experiences when we've had an epidemic after a few years of that epidemic the population seems to die down. It's like COVID you have a spike of the population then it kind of comes down and we're okay. Right now it seems like it's our cost per lease spot our disease pressure will be down. Our fields will be green but the good Lord does not like a vacuum. So we have to be careful. We still have to look at our fields. There are certain other diseases that are willing to take its place. Dr. Ashok Chandler told you a little earlier about Alton area. There is Alton area. There's one called white mole that can be there when it's cool and wet. Especially if you had lots of soybean with disease there. There's one called Stemphilium that looks like sarcospera and is as damaging as sarcospera with if white mole it can cause infection to the leaves as well as the root which is kind of dangerous. So keep on the lookout. You are the ones, the producers especially our agriculturists who are out there all the time seeing what's happening, bring it back to your researchers and I'm sure they'll be able to find solutions. So as my take home message is our enemy is sarcospera. It has very large numbers. It's very prolific and it has been known to develop resistance to nearly any different type of fun decide you have especially the more modern site specific fun decides. Even with good CR plus varieties in the future we shall always always take a lesson from the Greeks and use a product such as they use chlorotarnil we shall always use probably an EBDC with any other chemistry to protect our CR plus varieties or any other new varieties we get. And I will highly recommend to KWS that you start looking for another resistant gene to use because it will only be a matter of time before we get resistant to the CR plus varieties. Use a holistic system using crop rotation incorporating your debris. Anything you can do to use your fun decides in a timely manner, use your time to scout use it only when necessary. And the reason why I tell you this is I have two young daughters as pretty as their mother they didn't resemble me and I've told them since they were kids I don't want you to become addicted to anything cigarette or rum that your dad is drinking and if you don't want to become addicted don't ever start using any of those stuff. Anytime you use any pesticide or beside insecticide, fun decide anytime you start killing anything there is something called selection pressure. And once the more you use something the more you use it the higher the selection pressure. So sometimes it's good to say yes let's use more fun decides to control a disease but you use it judiciously because if not over time we can lose them and as you have seen over time it takes a long, long time to get a new effective mode of action. With that I'd like to say thank you for your many years of support for the R&E board for providing funding all the allied industry for providing seeds and other inputs that we need Luke for taking out the picture to show what happened on August the 26th Kevin for allowing me to contaminate his field all my colleagues for harvesting and Peter for doing all the hard work with our interns thank you.