Hi, YouTube family and welcome into today's video, which I am so pleased to be bringing you is a very requested video about concealing under eye dark circles. In a minute, you're going to see me with just foundation on my eyebrows done and that is about it. And we're going to tackle this under eye area. I do want to say just a couple of things to you before we start though. Please remember that as you're aging, you're not going to have everything be absolutely smooth and absolutely perfect. And I feel like this is such an important thing for me to say because I am not trying to make you feel like it can be absolutely perfect because I know that my eyes, my under eyes aren't absolutely perfect. So I want you just to remember that this video is specifically about taking care of dark circles and not having it crease. But I still have texture and I still have wrinkles underneath my eyes and I have pretty deep ones. And I know that if I were to have procedures done where I, you know, maybe had Botox put right here or fillers put right here, it might help with those. But unless I go under the knife or I get that kind of thing done, I'm still going to have that to deal with. So I just want you guys to realize that you're beautiful even if you do have them. We work with what we have and really our confidence shows through when we just feel the best that we can feel. Let's get into the video so that you can see how I conceal my dark circles from Hades. They're horrible. They're bad. So let's get into it. What I want to show you before this gets started is how pronounced my dark circles are, but also my wrinkles under my eyes. I don't have any way that miraculously we'll get rid of them. I'm not here to tell you that I do. These are things that I have tried and then I do my best with. Okay, to start with what I'm going to tell you is that even before you touch a concealer, a color corrector, anything, you have to moisturize.  Now if you have oily skin, this might not be a problem for you, but I have super duper dry skin right here. It's really dry and that's the reason that it's so creepy is because my whole life I've had very dry skin. So recently I found the Tsuki Yaka Suhara Yuria Moisture Eye Cream and I love this stuff. So I will use this two, three times in the morning and it really does plump up that area as much as is possible. And plumping that up is so important. So really pat that in. If you want to, you can pat it on your eyelids. If you have really bad creasing problems during the day, you might not want to do that. The next step is using just a tiny bit. And when I say a tiny bit, I really seriously mean a tiny bit of a primer that has a little bit of a silicone in it, but not tons of silicone because the silicone is still going to, you know, accentuate those fine lines. So I use this one that I'm really liking from Rimmel. It's the Lasting Finish Breatheable Primer. And I have been using that and I really like it. And what you do is you just use a teeny tiny bit over top of that moisturizer so that it can lock that moisturizer in place and you can, you know, keep the moisture from wicking away during the day and, you know, go ahead and just pat that in as well. Now, for my eye shadow primer, I'm doing something a little bit different. This takes care of the discoloration on the top. I actually have two products. You don't have to use two products, but I do just because the discoloration is so bad. Now, if I didn't have a Mac painterly paint pot, that's the first thing I'm going in with. I'm just using this up. It's not my favorite. But if I didn't have this, I would actually just use my concealer. So I'm just trying to take care of this discoloration across here. Now, the other one I'm going in with is from Wonder 2 Cosmetics. And this is called Wonder 2 Prime and Behold. It has a little bit of a luminosity, which I really do like. And again, this isn't like my favorite in the whole wide world. And you're going to see that it's really goopy and nasty. It's because I was trying to use up the end and I took the stopper out. And I just ended up with a little bit of goop going on. So I'm just going to put some of that on this one. I really like because it I can feel it immediately set down everything. And the other reason I like it so much is because it does have that luminosity that helps to brighten this skin in the area where it's so dark and really shows up some nasty shadows.  And since my circles are so dark, I use the one that's in apricot. The reason that I like this so much is twofold. Not only does it cover really well and it hides those or, you know, cancels out the color, the discoloration. It also is a really thin formula and it's not excessively creamy. And why I want that is because I don't want it mixing with my concealer. You have it mixed with your concealer. Then your concealer is just going to look orange and you're going to look weird. And what I will do is I will just dot it right there where those terrible lines are. And now once I get it on there, then I'm going to spread it out with my ring finger and just take care of all that discoloration. Now, if you feel like you've gotten too much on there, sometimes I feel like that. I just continue to dot it with my finger and I'll clean my finger off with a towel just until I feel like I've got the right amount on there. So after I get that on, I get it padded across. I let it sit there and kind of, you know, meld with the rest of the moisturizer and the primer that's going on there. I just kind of let it just sink in so that it's not moving around at all. I'm going to be doing my eye makeup and then I'll be right back with you. OK, eyes are done. What I want to tell you at this point is is that when I get all of my makeup done, it's going to look better and it's not going to draw so much attention to that under eye. And I also want you guys to think about something when you're standing this far away. I'm like I'm like four feet away from the camera at this point.  They look so bad. What in they're not going to be doing that.  You are being very critical of yourself. Remember that aging is beauty. It is not something to be ashamed of. I have three concealers. The first one that I want to tell you about is the Tarte Creaseless. This is an extremely emollient concealer. So if you use this on your own, this is going to settle into your fine lines and your wrinkles under your eyes, which is why I don't use it alone. But I am going to put a dot of that on each side in order to and I'm going to bring it down just a little bit because I have a lot of redness right there. And then I'm going to use two other concealers. And the reason that I'm telling you about different concealers is this is the Too Faced Born This Way, the Conceal Contour and Highlight, which I really, really like. This is in the color Vanilla. And then this one is the Makeup Revolution Super Size Conceal and Define. They are really good as far as their coverage goes.  And I also want to say at this point, use as little as you possibly can. I just put a dot on there because that doe foot is really saturated. And that's all I'm going to do on this one. I'm just going to use a dot. Now, if you need more later, you can go in later. But to start off with, don't use too much. So I'm going to start down here on my cheeks where I have all that discoloration to try and work that out a little bit. It's actually not going to be that much difference between the two eyes. It's going to be more about the way you put it on, the way you set it. Those two concealers are really, really close. Now, as I'm patting this across, I'm going to go up into the cavern in here inside my nose. There's always a lot of darkness up there. And I'm going to bring that out right there towards the tail end of my eye or the corner of my eye out there because there's a ton of darkness out there as well. Now, I'm just working this around and I'm really, really pouncing my finger in. And I'm just, you know, the warmth of my finger, the warmth of my face, those two things together are really going to help those meld and look really pretty good as far as the under eye goes. Now I'm going to switch fingers to my ring finger on this side. And I'm going to do the same thing. And again, I'm just bouncing. Now, the reason that I don't ever pull my finger across like this is once you do that, then the color corrector underneath is going to get mixed with your concealer.  No hating of your look today.  And then we're going to take a look now. All of that discoloration is gone. It is just it's wiped away. And I feel like it looks fresher. It looks like I'm more awake. It doesn't look like I'm tired. It doesn't look like I don't feel good, all those things. So at the point I'm at right here, what I'm going to do is I'm going to take my Flower Beauty, seal the deal, hydrating hydrating, setting mist. And I'm going to spray my whole face. I absolutely love that spray because it comes out so fine. It's such a good bottle. And now what I'm going to do, what I'm going to be using is the It Cosmetics Your Skin But Better CC Airbrush Perfecting Powder. This powder is can be sheared to full coverage. I love this powder. It feels just really creamy and smooth. And it does give a little bit of added coverage without being too heavy. The next thing I'm going to show you is two different ways that you can go about setting your under eyes. I do not use a lot of powder because I feel like that powder will immediately dry me out. But I've already sprayed some hydrating setting spray on there. I just want it to not crease. So I'm going to show you first with this aesthetic H22 brush. And I'm going into that powder and this brush is so it's so fluffy. I can't even begin to tell you how light and airy and fluffy it is. So I'm picking up just a little bit of the powder and I'm just going across there. And instead of swiping it, I am just like putting three dots on there to do that. Now, the other thing that you can do is you can take your dampened beauty blender and you can go into the side of the powder. You can pick up some of the powder and then go ahead and go underneath and set your and set your concealer that way. I don't normally do that because I feel like that will put way too much down. That will put way too much powder down.  I feel like when I do that, it will go ahead and it will take down again. Any of that dryness. So I want to make sure that I'm not putting too much powder on that area. Otherwise, it would just be looking dry and creepy and terrible by the end of the day. I find that once I do this routine that I'm set for the day.  I'm going to do the rest of my makeup and I will be right back with you. OK, you guys, so that is it. That is the finished look. Go ahead and take a good look at the under eyes. I'm going to squint for you guys so you can see what it's all about. I'm going to turn this light off for just a second. And you're not going to be able to see very much. But maybe you can see, you know, what the under eyes are doing there. I do have a lot of creasing and I do have a lot of issues with my under eyes. But the thing is, is I try really hard not to let that get to me. And I hope that you guys kind of take away from this video. That very thing is that even though you're aging, even though that under there, it might be a little bit of texture. This technique doesn't have any creasing that goes along with it. So that really goes a long way as far as, you know, the way that it wears during the day and that I can be confident. Yes, I may have to touch up during the day once, but it does stay really well. So that's everything for today's video. I hope that you did enjoy it. Please give it a thumbs up if you did. I appreciate you guys stopping by and sharing some of your time with me. Thank you so very much. And I will see you all in my very next video. Love you. Bye.


For those wanting the locations of DLC3's creature feature movie rules for the new crew challenge, don't worry, I have you covered here today. How's it going guys, my name's DPJ and today I bring you another BF3 video. If you do enjoy it leave a like really helps out and subscribe if you do want to see more. So the new crew challenge of finding movie rules for the creature feature crew challenge isn't as easy as you might think. Some of the locations are really difficult to find but don't worry people, today I guide you to each and every one. Oh and for completing this crew challenge you get this new room decoration too, this guitar. Check it out. So each location for individual areas you will find timestamped in the video description and pinned at the top of the comments section.  Also at the end of the video as you may know, collecting all of these movie rules you get to see a short movie. I will play that at the end of the video if you guys are interested in seeing it. But on that note we have come to the end of the video, if you guys enjoyed it leaving a like really helps out. If you're new around here and want to see more Bordelands be sure to subscribe and if you never want to miss a video I upload a can of notifications on by hitting that bell button. Also if you want to support me directly you can by becoming a member of my channel. You can do this by hitting that join button for more information. But again thanks as always for stopping by hopefully you enjoyed the video and hopefully I will see you on that next one.


All right. Good afternoon. We'll resume our afternoon session. First, I want to thank Simitomo for the lunch today. Thank you very much. Very good. Got ice cream too. Also, I want to thank you for the research education board for funding. So just a big thank you there as well and a reminder they're seeing signups in the back. Other reminders on your programs. It has the dates for the grower seminars. So Grand Forks Fargo is the first and third of February, February 10th. Mindeck will be having there. So a date change as well there. And in Grafton, we'll have the 17th of February at the Grafton. So yeah, we'll have our first speaker come up for the afternoon. The importance of tank mixing for management of succox release spot and sugar beets. Well, Mr. Austin Lee, talk about that. Well, thank you and good afternoon, everyone. So I'll just jump right into it. As we've been hearing today, sugar beet growers deal with many challenges. But Sercospora leaf spot caused by the fungus, Sercospora particular, has earned the reputation of being the most destructive foliar disease in sugar beets. And this is caused by the destruction of the leaf tissue seen in this photo, as well as the effects of the pathotoxins produced by the fungus. And this results in reduced harvest weights and a reduction in sugar concentration and quality, and subsequently a significant economic cost. Just in 2016, over 140 million dollars were lost in Minnesota and North Dakota due to Sercospora leaf spot. And this was due to two main reasons. One, the warm and wet conditions were conducive for the development of the disease. And two, samples collected across the co-ops in Minnesota and North Dakota indicated that 90% of those Sercospora isolates were resistant to the strobilurin, so the QOIs. And this just emphasizes the fact that we cannot afford to lose the DMI fungicide or the triazoles to fungicide resistance. So the rationale for this trial is that reports strongly suggest that tank mixing or combining products with different modes of action for one single spray application can provide more than additive effects in regards to disease control, and theoretically less disease equals fewer opportunities for mutations to occur in Sercospora populations. However, anecdotal evidence along with our own preliminary field trials suggest undesirable effects can result from tank mixing certain chemistries and formulations. And lastly, reports in field trials suggest contact fungicides and compounds, other than copper and mankozeb, that could be an effective tank mix partner. So in 2020 and 2021, we conducted an inoculated field trial in which combinations of DMI fungicides and tank mix partners were evaluated for their effect on root yield and sucrose quality, and of course, control of Sercospora. Essentially, from this field trial, the questions we aim to answer are the DMI's or the tank mix partners providing equal control compared to each other. Are there any combinations that are synergistic or maybe even antagonistic? And lastly, do we see the same trends in both years of that field trial? And so the DMI fungicide treatments we use were Proline, Minerva, and Spire XT and Provisalt, and the tank mix partners mainly include contact fungicides or those multi-site fungicides such as copper and mankozeb and also sulfur. We also included a biological control agent, this bacillus species, and we included a fertilizer responsible for host plant defense induction, which is this phosphite or phosphonate, and we also included a bicarbonate-based compound that may have fungicidal properties, and this is better known as baking soda. So those fungicide treatments were applied to the middle four rows and were applied repeatedly about every 10 days for a total of five applications. And those applications began when disease was first apparent in mid-July, about two weeks after inoculation, and ended in late August. And to assess Sercospora leaf spot severity, I actually regularly collected leaves from each plot, photographed each leaf, and then analyzed it with computer software, and then took the average percent severity to determine the ordinal ratings of zero to 10, and then 12 representative roots, or the middle two rows were harvested and weighed for root yield, and 12 roots were sent to the American Crystal Quality Lab in Moorhead for quality analysis. But now before I get into the results of the field trial, I'd just like to touch upon the two drastically different growing seasons we have in 2020 and 2021. In these figures, the gray bars are showing the total amount of precipitation received, and that black line is representing the average daily temperature, and this is from April through September. And the summer months of 2020 were very wet with consistent rainfall, and in July we actually received four inches more than our 30-year average. And in 2021, we had a very dry and warm season, where in July we received three inches less than our 30-year average. However, we finally did receive some much needed rainfall there at the end of the season. So this first figure is showing the recoverable sucrose per acre for all of the main plots. And this dotted line you see across the center is the average across all of the treatments, and that solid line in each box plot is representing the median, and those asterisks represent the average. And so for this year, unfortunately, there were no significant differences among those main plots, and that could be for two main reasons. One that the no-DMI main plot here, this one right here, represents all of the tank mix partners by themselves, including the Mancos Ebb and Copper. And with the little rainfall we received, there was fairly good circospa control achieved from those compact fungicides. And also the drought conditions through most of the season kept the relative level of disease relatively low. But we can also see that that no-DMI main plot again is the lowest in terms of recoverable sucrose, and the proline is the highest. And now this is the same figure here on the right-hand side, but compared to last year, where the high disease levels we had in 2020 resulted in differences that were much more pronounced. It's also possible that the timely rainfall we received in 2020 really limited the effectiveness of those contact fungicides in that no-DMI plot, you know, being that we had almost weekly rainfall washing those contact fungicides off the leaf. And although there's quite a bit of variation among those DMI treatments, statistically the achieved yield was equivalent, but proline and inspire did come out to be the highest there. And now still looking at recoverable sucrose per acre, looking at the tank mix partners. And there was in fact some significant differences this year, most notably, it was the Mancozeb, the Copper, and actually the Sulphur, the three contact fungicides that provided the greatest yield return. But also this phosphate here was significantly better than the no-partner subplot as well. And then comparing these tank mix partners to last year, we are seeing some of the same trends where in 2020 the Mancozeb provided the greatest yield return followed by Copper and that phosphate. So just to give you an idea of the level of disease this past year, here's a photo showing the non-treated plot on the left, where we're seeing some defoliation and quite a few brown leaves there. And then the treated plot on the right, which has a full canopy and a good level of disease control. But now looking at disease progress for both years, you can see the level of disease in 2020, 2021 generally stayed below that threshold of economic damage, which is equivalent to a rating of six or also 3% severity. But we're still able to see some of the same trends as 2020, where that no DMI main plot resulted in the highest level of disease. And where disease progressed similarly for Minerva and Provisol and also the Inspire XT and the Proline were comparable. And now looking at the final disease ratings for all of the treatment combinations, so there's no DMI main plot is now broken down into that non-treated control and then all of the tank mix partners by themselves. And then each of those DMI main plots here are broken down into the DMI by themselves and then all of those treatment combinations. And we can see here that that non-treated control did result in the highest level of disease and came out at about a rating a little below an eight. But we can also see that all of these tank mix partners, when compared to the DMI by itself, are providing some improvement, except for the bicarbonate with Proline and the Inspire XT with bicarbonate, which seemed to be antagonistic. And we're also seeing that Mancozeb, this yellow plot here, is providing the greatest improvement in terms of disease control and that was followed by copper. But the phosphite, the sulfur and the biological are providing an improvement as well. So lastly, I have combined both the years of data in terms of revenue per acre based on the most recent American crystal sugar payment. However, this does not accurately reflect real world applications being that these treatments were repeatedly applied and this does not factor in the cost of the fungicide applications. But just to recap, I want to highlight the top nine fungicide combinations. And for your reference, the non-treated control plot came in around about $1,000 per acre. And the combination that resulted in the highest return was Proline and Mancozeb, where we saw excellent disease control and also good yields. And next on the list is Inspire XT and the Sulfur, which had pretty fairly good sucosper control. But in both years, we also saw a fairly large increase in sugar concentration. Next are Proline and Inspire mixed with the phosphite, where we had good control, disease control, and we saw an increase in yields as well. Next here on the list is Inspire and Copper followed by Minerva and Mancozeb. Next is the Proline and the Provasol with the biological. And this Provasol and biological combination, we also saw a pretty big increase in sugar concentration in both years as well. And then last on this list is Minerva and Copper. And for those of you who are just curious about using only Mancozeb, it came in around about $200 less than Proline and Mancozeb combined. So hopefully by looking at this table, you can see that each DMI performs best with a particular tank mix partner. And it's not just one tank mix partner that works well across the board. So results show similar trends were observed in both 2020 and 2021, where tank mixing improved circus relief spot disease control and yields despite the drastically different growing seasons. In addition, however, depending on that DMI and tank mix partner combination, interactions occurred that resulted in variable performance. So for example, the Proline and Mancozeb work great together. But when you combine Mancozeb with Inspire, we just don't see the same performance. In addition, the Phosphite, the Sulfur and the biological all seem to be candidate tank mix partners. And depending on the combination, overall performance of those products were just as good or even better than some combinations with Mancozeb or Copper. And just so you all know, we are also looking into how the addition of a tank mix partner interferes with the development of fungicide resistance on the molecular level. And hopefully next year, I'll be able to show some of those results at our next reporting session. So with that, I would just like to thank the Sugar Beet R&E Board for funding. I would like to thank the many companies for chemical product and seed. I'd also like to thank the guys at our farm, particularly Jeff Nielsen and the rest of our summer crew. And of course, thank you to Dr. Ashok Chanda for his guidance and support. All right, next was after with the topic of management of rice-actonia diseases in Sugar Beet is Dr. Ashok Chanda. Good afternoon, everybody. Thank you for sticking out for the afternoon session here. So this is the only second talk today for talking about rice-actonia. So I'll just touch upon actually three research trials that we did in 2021 and what did we find out. So, you know, first thing I always emphasize, you know, we just need to figure out what are the diseases that we have in a particular field, right? I mean, if you don't know what we're dealing with, there is no way we can manage them. So if you look at the number of samples that I received in 2021, it's very minimal. It's 29 samples, right? So in a normal year, we get about 90 to 100 samples that speaks volumes about the impact of weather on disease, especially the soil-borne diseases, right? So if you look at those 29 samples, again, the pattern that that's very common over the past few years, right? We got about 17 samples of rice-actonia, one of FNMICs, only one with both of them, two fissurium, you know, chemical. And then given how dry it was, there were so many samples that we didn't recover any pathogens. You know, most of them were like carrier issues, some kind of herbicide injury from previous seasons, right? So I think many people touched about the rainfall patterns again, you know, it's from north end of the valley to all the way to the southern Minnesota. Most of the early season was dry, but as we went into August, we got some moisture September, October, it's pretty good actually, you know, I was just quite amazed how resilient these beets are to pull up that yield by the end of the season. When we think about rice-actonia, it's a full season pathogen, but, you know, it can affect any time before even the seedling is emerge from the ground, right? We call this a premature stamping out, but then it starts killing any time it's active in the soil. It can actually infect at the soil line, you lose the seedling, but as you go into three, four weeks after planting, some of these young seedlings can be very susceptible to rice-actonia. And as you go later into the season, you know, the best thing is to pick a nice warm afternoon, right? And then see some of the wilted plants, but don't just depend on the tops, you just need to pull those beets and then look at the roots. And fair enough, you'll see a lot of root rot, but right next to the wilted plants, it's not uncommon to see already wanted to get plants, you know, that's where rice-actonia tends to move up and down in the row there. But again, when you look at the roots, you know, more and more, we don't see that much crown rot just because we're doing less and less cultivation unless it just changes with other tillage practices right now. But we are seeing more of the root rot, you know, towards the bottom end of the roots, which is very challenging for the growers to manage, you know, for that we have some solutions. But what happens when these beets die, you know, the rice-actonia will go into the dormant phase. It makes these resting structures, we call them sclerosia, which can be inactive in the soil for two to three years. If you have a corn or soybeans in the rotation, they can infect those crops and then it just keeps sustaining until you have the next sugar beet crop. So most of the growers are actually doing a pretty good three to four year rotation with sugar beets, you know, that's what needed to keep the rice-actonia levels low. But if you have a susceptible host crops like soybeans, dry beans or corn, you know, there is some amount of rice-actonia that's always present in the soil. And also the weeds, the pigweed or lamb squatters, coaxial, these are actually good hosts for rice-actonia too, you know. And then early planting is very good because soil is still cooler, which is not very good for rice-actonia. So early planting, you get those head start for those seedlings, so they can actually get past that seedling phase. And other options we have, we have pretty good resistant varieties. Not only these are good for rice-actonia resistance, but also yield very well, you know, thanks to the breeders, which are combining both traits. And also we have several fungicides that can be applied as a seed treatment or in for all, or only do a post-imaging application, right. So three different trials, I'm going to show some data here. So number one, I'm calling this as integrated rice-actonia management. In this particular trial, what we do is we evaluate two different varieties with different seed treatment or in for a fungicide and a different post-emergence application times. So this was planted on May 7 in Crookston and prior to planting, we broadcast in our climate 50 kilograms per hectare. I got a 3.8 and a 4.8, two different varieties, low and then high resistance for rice-actonia there. And then for at planting, there's nothing on the seed or in for all, only sisteva seed, sisteva with quadricein for all, or only quadricein for all. These are our treatments. And then for a post-emergence, no post compared to, you know, for leaf, that's a normal time that we do it, and then eight leaf, that's a little bit later. But now more and more data that we are seeing that benefit from eight leaf application too. And it's a split-split plot design. I'm listed here, everything. And the data collection, we do a lot of stand counts right from anywhere from two weeks all the way to six weeks. And we collect a lot of data at harvest time. And then in terms of statistics, we looked at the main effects and also the possible interactions two-way and three-way. And the rating scale since 2020, we changed it a little bit. We use now zero to 10. With each one point rating is like about 10% of the root rot on the surface of the roots. Again, monthly rainfall in Austin talked about a little bit. We lost about 50 to 40% of the rainfall until June compared to 10-year average. Extremely dry in July, just about 10% of the regular 10-year average. Finally, we got some moisture. And because of this, there's very little disease development early on, and you can see the impact here. So we didn't see much interaction among different factors. So I'm only showing the data for the main effects. The 3.8 and 4.8, as you can see, it took almost about three weeks, three to four weeks to get the good stands from all the time from the planting. But between two varieties, the susceptible one had slightly higher stands, but statistically, these are not significantly different. So it's not any better. For the ad planting treatments, follow this black line. It's actually mixed with other colors too. This is my untreated. There is nothing on the seed. Number of plants for 100 foot of row on the y-axis and the days after planting here. Again, really all the three seed treatments are here. Sorry, this is the ad planting one here. The Sistiva, Sistiva and Quadris are untreated plus Quadris. You can see Sistiva is slightly higher. But again, in terms of statistics, everything is very similar. So we barely got about 165 plants for 100 foot of row. Typically, we have anywhere from 199 to 200. You can see the impact of dry weather on emergence there. And for the post emergence, like I said, there was no post or Quadris applied at four leaf or eight leaf stage. For this, again, there is no significant difference whether it's a four or eight leaf application of Quadris and one more or less 165 plants for 100 foot of row. But only interaction that we saw here was actually for recoverable sucrose per acre. There was a variety by post, which means they behave differently. If you look at the resistant variety actually, even with no post or four or eight leaf, there's a slight bit of increase in RSA, whereas a susceptible variety, which is 4.8, we got about 500 pounds per acre increase just with this four or eight leaf application. But this data is also averaged across all the eggplanting treatments here. So you just have to keep that in mind. And the next one that I'm going to show you is this is just purely, we use a 4.8 variety, which is very susceptible to rhizoctonia, where we evaluated all the available seed treatments and also infrared sites. This is almost like apples to apples comparison in one trial here. This was done in Princeton again. We inoculated this plot spray to plant in. So this is my untreated control. You can see again, it took a few weeks to get the emergence all the way up to 150. Then we started losing a little bit of stands here, but this more or less stable because again, the dry conditions are not very favorable for rhizoctonia disease development. And once I start adding the seed treatments, so that's my C-stevaline here and then cabina and vibrance. Exactly, they're exactly similar. My message has been, no matter what you pick, all of the labor seed treatments for rhizoctonia, they work very well. So don't worry about which one you're getting. And the one new compound that got labeled in 2021, it's called Zaltera. It's inbill flow of the psalm, the S-D-H-I class. And then it did very well in 2021. So the number of plants were slightly higher compared to the seed treatments, the other previous ones, but in terms of statistics, it is pretty similar. And one common thing that we see whenever we use infrared sites, especially when it's a drier and cooler conditions, they can hurt the stands. But in 2021, we only had dry conditions and it was fairly warm with lack of moisture. But it's the same line that I showed you earlier for my untreated control. And then that is actually quadriceps at 9.5 fluid ounce. You can see the stand was reduced right from the emergence at two weeks, all the way to six weeks. And then I have preaxter here. And then that's elitist. It's a combination of quadriceps and S-D-H-I. And this is actually asteroid. It looked a little bit better compared to quadriceps. And then I have propols. And then this is actually xantheoninferoi. This is a combination of headline and a biological. I know it was there in the market until last year, but it's not available anymore. But we just try to combine the headline component and the biological one and then try to see how it's doing. And then the last one is actually proline, which it will okay. But again, you just have to keep in mind, it's not really high disease pressure situation in 2021. But again, like I said, the seed treatments and the infrared, I'm comparing them as two groups here, both of them, you can see the, with inforose, we got anywhere from, you know, 10 to 12 plants less per 100 foot of road compared to seed treatments. But by the time we go to harvest, there's not much difference between the seed treatments and infrared ones, 131 versus 126. And most of the yield and other parameters are not significantly different between seed treatments and infrared funding sites. The only difference we saw for are equal to close per ton and also person sugar. But when you come to RSA, it was more or less similar. And the third trial that I'm going to use some data is from, it's a only post-emergent treatments here. So we use the same idea that with the 4.8 waiting for isochronia, and then we applied several different post-emergent treatments. But the only difference here is we inoculated these plots on June 23rd, you know, we use a gandy applicator and we put this barley in oculum. And then next day, we applied the funnicide treatments. So we got about six tenths of the rain on June 23rd. And also once we apply the inoculum, we actually rake some soil into the crowns just to make sure that, you know, it's protected. So we got a pretty good disease development in this particular trial. So the non-treated control with the bottom portion here, we lost about from the June 24th until harvest, we lost about 52% of the plants. And we ended up with only 4,400 RSA. And the ingredient that we have one in Excalia, it's the same gender or seed treatment. But as opposed to application, it did pretty good about 9,700 pounds RSA and very less root rot and 13%. And most of the products that have azoxystrobenin as a progress or asteroid, they all did pretty good in 2021 as a post application. Now statistically, these are all very similar. And I'm going to share this presentation on the SBIRUB website, so you can actually get these numbers. And the other thing I have is the TopGuard EQ, it's azoxystrobenin in combination. And also elates, it's azoxystrobenin, then SDHI, it did very well too. I'm almost done Joe here. And then, you know, some of the less commonly used products for RSA, Tonya, the Baxter and Proline, again, you know, 2021 was not like, you know, very high disease severity. So these products did well too. The only thing really did do that much was, you know, propols in 2021. Like in the real world, if you use any one of those products all the way from Excalier to propols, I think you would have gotten some, you know, good benefit in protecting bees from rhizoctonia. So to summarize, you know, the varieties, those are pretty good, but as you know, resistant varieties, they may not make any difference, you know, in a normal year. The seed treatments are pretty good. They offer protection early on for four to five weeks. And in for a fungicides, they do very good. But if you have cooler and drier conditions, you know, you can hurt some stents, but by the end of the harvest, it's okay. And for the post emergency application, you know, between four and eight, that's from the first week of June to third week of June, I think pretty good, you know, timeframe for you to get them on. So the good rhizoctonia package, I would say, and a good seed treatment followed by a post in a normal field. But if you have a really severe field for rhizoctonia, I think you should also think about it for a full season control. So with that, I would like to thank the R&D board, you know, the sheer co-ops and then the companies for all the products. And last but not the least, with all the COVID restrictions, the, you know, hardworking crew in the lab and the field. Thank you so much. Thank you, Dr. Jamal, for the presentation and your work. Our next speaker will be talking about evaluating the addition of adjuvants to fungicides to reduce the disease severity caused by some cosmogonicola and increasing surgery, the old kind of equality presented by Mr. Niyan. Good afternoon, everyone. Today, I'll be talking about do adjuvants improve the efficacy of fungicide in controlling sarcosperitis, but of sugar So sugar beet is an important sugar-eating crop next to sugarcane produce more than 130 countries of the world, especially produced for sugar. So as a byproduct, you also get molasses and pulse. It has a versatile uses in our day-to-day life, even we cannot think a single day without sugar. So it seems how sugar beet is important to our day-to-day life. So sugar beet can be used in alcoholic beverages, NGIC products include communication in some warmer states of the United States. It's becoming very popular in some Asian countries, animal poultry and fish feed industries and it has great economic importance in industry, the uredine and the betten chemicals. Sugar beet produces in many countries of the world, especially in the temperate countries as a summer crop. So Russia ranked first among sugar beet producing countries of the world, followed by France. US ranked third, it produced approximately 33 million tons sugar beet annually, followed by Germany and Turkey. Three giant sugar beet cooperatives, American Christian Sugar Company, Mid-Deck Farmers Cooperative and Southern Minnesota Beet Sugar Cooperative Company contributed approximately 57% of total US sugar production, which is almost about $5 billion dollar economic activities. In the United States, Minnesota and North Dakota are two leading sugar beet producing states where Minnesota produce about 11.336 million tons whereas North Dakota produce half of that amount that Minnesota produce. Sugar beet production is influenced by many factors, among them, sarcosperally spot, it's considered to be one of the most destructive foliar fungal disease caused by sarcosperabetic cola. So it's hemibiotropic fungus, polycyclic in nature during the green season. So it produced two non-host selective toxins, sarcosperin and vetically and other enzyme that represent the visible symptoms on the leaf of sugar beet. It has significant impact. The loss estimated up to 40% or even more in severe conditions. It reduced sugar quality and that indicates how huge the monitored losses and also decreases the storability in the piles. Typically the symptoms on the sugar beet leaves are small, tiny, early in the seasons that is grazed with graze centers surrounded by 10 or brown color merging and then with advancement of time that it become very blight and that the all feel completely represent a blighted field and even due to high disease pressure or delayed harvesting it's showing that really generation of new leaves that already start consuming the stored sugar in the sugar beet that ultimately at the mean represents the large recoverable sugar in the sugar beet. Though the typical feature it has the effective structures conidia and mycelia that causes infection. Each and every lesions contains pseudostroma. This is the over-wintering structure of sarcospera viticola. Every lesions has numerous pseudostroma and in the conducive environment it regenerates conidio 4, conidia and then that continues its life cycle in the green season. Currently the growers are highly recommended to use tolerant varieties, sufficient varieties if available and sanitation practices to reduce the initial amount of inoculum in the field and deep tillage operations and crop protection with non-host at least three years are highly recommended and as a last resort timely spraying of fungicide could be a better option for controlling sarcospera viticola. But development of widespread resistance to sarcospera viticola is a major concern that is the sarcospera viticola is highly resistant to qf on this side typhoon of methyl stops in and it reduces sensitivity to triazole and tpd h fungicide and even cross resistance to four major motivation of fungicide. So what happens it has that results complete sometime complete management failure and even economic losses in as the statistics in 1998 when CLS epidemic first appeared it American Christian sugar reported about 130 million economic losses during that year and recently in 2016 about 200 million dollars losses due to sarcospera leaf spot of sugar beet and even sensitivity of sarcospera viticola to triazole of imminent inspire and proline and proviso and since and the mutation g 143 mutation in those isolates this in this graph indicating since 2012 to 2019. So and even efficacy of fungicide is highly influenced by many environmental factors wind heat solar radiation and rainfall and rainfall could be one of the most important of even that plays important role in reducing the efficacy of fungicide that wash off and has redistribution impact even deposit and has residual activity and also major concern for environmental pollutions too. So with the view to keep retain the fungicide and efficacy or retention of fungicide longer time so we plan to add adjuvants onto fungicide tank mix to increase the efficacy or even the retention period as immediate after the fungicide spray if rainfall happened it may wash off the fungicide. So we wanted to see how adjuvants impact on efficacy of fungicide generally it's very popular the adjuvants on harby side but we added these fungicide adjuvants to see how the commonly used fungicide improve the efficacy of fungicide that are generally used for controlling circus probability color. Adjuvants are thus any substance added to spray spray tank that other than fungicide formulation it's supposed to improve the performance or efficacy of fungicide. It started since in back 1950 to 60 currently it has around 155 spray adjuvants which are of different natures about 25 categories most commons are surfactant, sprayer, sticker, penetrant, emulsifier and oil based and so on. So when if we consider the water droplets on the leaf surface because of poor weighting and higher surface tension so it has very less coverage on the surface of the leaf if added with adjuvants the picture right on the bottom that indicates that because of lower surface tension it provided better surface coverage on the sprayed surface. So with the view to see how the adjuvants work when it's added to fungicide how it improve either improve the efficacy of fungicide or not for controlling circus probability color of CLS. So we had this study in Foxham Minnesota for 2019, 2020 and 2021 three years that we use a variety that is more susceptible to circus probability spot. We use different mode of action of fungicide and even different types of adjuvants. We evaluated the DZC CLS severity and sugar bill in loss spawn per acre. So we used fungicide triazole fungicide in sparax to recommended dose of all fungicide evdc. From evdc group we use panko jab and from copper fungicide we use badge SC. We use three different adjuvants which are complex, transfix, preference and elite. We use the recommended dose from the manufacturers. There's some important feature of those adjuvants complex. The most important feature is the spreader. It has great contact activity, better penetration, increased adhesion and reduced surface tension. Ceramic light is a well-known penetrant. It's non volatile, prevents diffusion of spray, increased penetration and better spray coverages. So transfix is an excellent resin-based sticker and it facilitates leaf coverages. Preference is an activator, improves spray droplets, reduce surface tension and it has important feature like better protection against UV ultraviolet. So you use one-to-ten DZC severity scale of John and Wendell's 1991. So we use a special nozzle that has two 110 degree flat finish spray. We compare with it with a conventional flat finish spray that has 60 degree back and forward so that ensures better coverage and uniform distribution of the droplets. So if you see in the picture left, on your left, right, that conventional flat finish spray has this less wider spray coverages and compared to conventional turbo twinjet has wider spray droplets. So and even we use syngenta spot card, droplet spot card to see the number of droplets and even their distribution, we found it provided better best coverage and uniform distribution of the left. Even in fungicide, when you use only fungicide, although some fungicide has some adjuvant properties, but when we sprayed on the leaf, you see most of the spots are individual and distinctive, but when added with adjuvants, it indicating that fungicide spread it and ensure better coverage of the droplets on the surface of the leaves. So in for about three years, we had 17 treatments in Foxum for CLS trial, CLS fungicide adjuvant trials. So including untreated inoculated checks, we use fungicide adjuvants, fungicide alone, fungicide mixed with adjuvants. We did CLS severity and we had yield data that's found recoverable recoverable sugar and we did statistical analysis and nonparametric to relative effect of the treatment. So from in the field, we use 17 gallon per acre for tank mix, speed we maintain for MPH nozzle that I mentioned are between jet and we spray fungicide at 14 days interval. So after spraying fungicide, you see the droplets on the leaf surface on CLS infected sugar with leaves. So we also keep track on the fungicide rainfall event at Foxum. So generally rainfall has four categories, trace to heavy rainfall, this intensity calculated per hour. So trace is 0.1 and heavy rainfall is under category of 1.74 to 3.5 inches per hour. So average monthly precipitation in 2020 is maximum in June 17, 3.7 and like from May 2 of July, the rainfall event was higher and even daily chances of precipitation was more than approximately 41%. In 2019 rainfall in the green season like from June to late September, it was more than like about three or around three. In 2021, more rainfall event was in during the mid of June 3.43 inches on the time. So what we found from CLS adjuvant and fungicide trial in Foxum. So in from three years in 2020, we didn't see any treatment effect on fungicide in adjuvant because of heavy rainfall and wet condition on that specific year. So from 2020 the because of high heavy rainfall. So we didn't see any significant effect of the treatments compared to inoculated check in recoverable sugar in 2020. So we didn't see even any significant impact of the treatments either from this side added to fungicide or fungicide used alone. So in 2019 and 2021, so first when you use fungicide alone, it indicates though inspire didn't provide it better control compared to other but they are not significantly different from each other. Penkojet provided comparatively better control compared to badge and inspire and when added this fungicide added with an adjuvant CE, that's cerium allied, it's showing there is no significant difference in the similar trend either added adjuvants with fungicide or not. But rotation of fungicide mixture of fungicide in rotation program that indicate are that it's showing little bit reduced severity, but they are not statistically different even are that means rotation of fungicide and even are plus CE that in that means fun adjuvants added with rotation of fungicide mixture in rotation. So now no significant differences among relative effect of the treatments in controlling circuits, but and even and even when other adjuvants, its CE indicates complex that also show the similar trends, no significant difference among the treatment when fungicide use alone either alone or mixtures in rotation program. So in recoverable sugar yield data in both 2019 and 2021, so in 2021 only complex it's provided better provided higher yield compared to other adjuvants, so they are not statistically different and except provided highest higher recoverable sugar in when complex mixed with inspire, but only except in transfix and added with badge comparatively lower yield and even in 2021, if you look at on the transfix table, there's lower recoverable sugar, but they are not statistically different compared to other adjuvants. So the field trial at FOXOM in 2019, it's a non-treated check. So PENCOJAP when used alone and PENCOJAP with complex and PENCOJAP plus transcript and visually it's it's indicating there are not much differences either fungicide added or fun added with adjuvants or fungicide is spread alone. So badge first picture is badge and badge plus complex, badge plus transfix and inspire. So the similar trend for this DMI fungicide 2 and in 2021 the stone treated checks that because of high disease pressure and complete lighting of the leaves and PENCOJAP in 2021 with alone with ceramic light and transfix, it's showing visually no differences for controlling sarcosperol is thought in sugar bed. So badge is the same trend. So either they use alone or mixed with adjuvants and for inspire this year, the inspire didn't provide it better control compared to other and fungicide mixtures in rotation, this indicates it's showing better control compared to other, but when added ceramic light, not much significant differences when used alone or added with fungicide adjuvants. So in 2020 because of heavy rainfall and wet condition on the top corner as no fungicide or even fungicide mixed with adjuvants provided any significant effect of the treatment. So we can conclude that sarcosperobiticola causes significant reduction in recoverable sugar of sucrose of sugar beet, if not managed properly and the fungicide evaluated provided fair to good control of sarcosperol is thought in dry condition, especially fungicide mixtures in a rotation program. So edition of one adjuvants complex was effective at improving efficacy of inspire trizol and resulted in higher recoverable sugar only in 2019. And under heavy rainfall condition, none of the adjuvants improve efficacy of the fungicide at controlling sarcosperol is thought. So I would like to thank my research advisor, Dr. Muhammad Khan for his continuous mentoring and support for doing the research and my PhD committee member and Peter Hague, who did a lot of great help for my research during the growing season and summer intern and the free and she knew and first day. And I would like to give a cordial thanks to sugar beet research and education board and then pathology department for accepting me as a grad students and thank you all for your patience here and I would love would love to have any questions. All right, next speaker topic is single pass delivery of insecticide, fungicide and feral adjuvants. It impacts a related control yield. Let's take a break and we'll be presenting them. Afternoon everyone. I want to discuss what we did. This study was replicated. We did in two sites in 2021, but the St. Thomas site actually what I'm going to present to you is a two year data set. Let's see the plot sizes there were our traditional size of 35 feet long, six row plots with the center four roles treated and then in a randomized complete design and no, no, there's no significant treatment by year interaction. So it's a it's a pretty good solid data set. And then the other location was at Prosper, North Dakota. This was our no pest site to see we're trying to assess efficacy of these chemical treatments. And this was planted a little bit later than traditionally in the valley. Just because we had to plant St. Thomas first. Those are two row plots at 30 feet long with four roles. So it'd be two row treatment side by side. And also that was another randomized complete block design replicated four times. The performance assessments that we did on all trials were done with stand counts. And just at the St. Thomas location, we assessed root maggot feeding injury. We took 10 plants from from two rows. And again, that was only done in St. Thomas where the pest was prevalent. And then we also did recovery super close yield. We harvested two center roles at Prosper. It would have been 60 feet total. And then that St. Thomas is at 70 feet total. And then all the data was analyzed using the SAS program and with an alpha value of 5%. And here, like I said, I'm just gonna reiterate this a two year data set for feeding injury. We had some pretty significant maggot pressure of both years heavily emphasized on the fertilizer check and also the regular check. The scale goes up to nine, but I had to kind of zoom in to get it all to fit. We did two rates of counter for good visual difference or comparatives. And then we also had two rates of counter, the same two rates of counter applied with DIF or dribbled in and for 1034O. And then we did two treatments of Yuma4E, which would be your copyrifos. We did that with one point rate and a two point rate that was all mixed in with a 10 and fluid ounces rate of quadrice. And those were banded on with 10-inch bands. And then also we did a 10-inch quadrice alone band with thymet on top of that. And then also a regular thymet with nothing else except for the high rate of counter as well. And down below here are the counter rates. And I'd like to point out too that we had some pretty good control with the double combinations of insecticide with the copyrifos or with the thymet with the high rates of counter. They actually were statistically different than the just the base rates of counter. As you can see on the left, it's significantly different than the checks. Here was a stand count data here. This is at St. Thomas just for a year 2020, we didn't combine the stand counts. And I just want to point out here that the stand counts are grouped in by the same color. And then the letter on top of that would correspond to this column here. So it's just the same color columns stating the similarities and the differences. The checks pretty stand out pretty well. They got hammered pretty good. And then the insecticide, single treatments of insecticides that hold up pretty good. And then also the dual insecticide applications did see a little bit of a difference with the stand count, but it really jumped up later at a date. And then, oh, I suppose I should have mentioned that orange would be 49 day DAP, which is days after planting. And then also a 62 day count after that. And then these were applied one day before pre peak as well, the Yuma and the Thymets with the Quadrus as well. This would be 2021. We're able to get four counts in with this, starting with 27 days after planting and ranged all the way up to the 48 days or 49 days after planting. I just want to kind of point out that we're seeing kind of a slant going from high to the right, or from the left to the right. And we're seeing a decrease in population. And that's due to maggot feeding and injury. As you can see on the far right, the checks from the fertilizer check, they really got significantly hammered. It was an amazing year in terms of mega pressure. Oh, and this would be at the prosper site with no pest. And you may notice that there, you won't see any letters on top of these columns because there were no significant differences in between on these stand counts. It kind of held statistically true for each treatment in terms of stands. And here would be a 2021 St. Thomas pictures on the upper left would be the check. Like I said, it was a very good year for maggots. They were pretty high in our St. Thomas location. And below that would just be the base rate of the high labeled rate of counter. And even there you can see that they got reduced. You can visually see the roles in between. And another thing I'd like to point out too, with the more healthier treatments here in the center and then the right, the border roles are completely untreated with insecticide. And you can see how those just disappeared due to mega feeding. But I guess I would like to point out on the center treatments in the right, both top and bottom, doing insecticide combinations are still working pretty well. At least above ground, you can see that they were pretty good for control. And here for recovery sucrose in St. Thomas, it did show that we are still having some pretty good control with doing insecticides. In terms of comparing it to just one base rate of insecticide. And even those are even separated out with the checks too. So we're still getting some pretty good control with granular insecticides. And then also with the UMAs. And this was with the two year data set. These were applied on an adjuvant of three days. Prepeak, not ideal. I want to try to get that a little bit sooner. I'm still supplied some pretty good control. And then here with the recovery sucrose yield at Prosper of this year. All pretty good. But we are seeing a little bit of a negative here with the combinations of Yuma and Quadris. Don't know 100% what's going on there, but we think that it was a very hot summer as everyone is aware. These were applied in late June that we might be seeing some kind of correlation there with the heat. And we did notice too at Prosper and also at St. Thomas with the combination of Quadris with insecticide. We are noticing a little bit of curling along leaf margins on the outside and they curl up. We noticed that and yeah, just the Quadris affected, or how should I say affected, Quadris treated plots. And I think that was around six to eight leaf stage when we took those photos. But as the data shows that they grew out of that. So we still had some good yield. And then here would be those combinations of thiamet with plus Quadris and then also Yuma at the high rate of two pint with Quadris. We still see some of that leaf curling, especially in the newer leaves. And here's your return or your gain over compared to the check base, which is 585. Just on this one, I would like to show that you're getting a lot more return with those dual insecticide treatments. You're still getting a good return on those compared to your single insecticide treatments. And then at Prosper, unfortunately, kind of cuts off right after those first two treatments there. And then we can start throwing in more chemistry if we're seeing a reduction in profit. So based on what you're seeing, out in the field, it might not be, that's just kind of emphasizes the need for scouting and trying to make a determination if you need to put that much input in there. But as it illustrates on here, it's not needed or wasn't needed in Prosper. But then conclude, we did, like I said, we said, saw some negative symptoms there with that curling. And I was just with the Yuma applied with Quadris and also with thiamet, I should put that in there. But like I said, they came out of it, might be somewhat maybe related to with the heat units that we're seeing in June. At the St. Thomas Magus site, we didn't have any detectable deal loss between the tank mixing of Quadris and Yuma. And then also with applying Quadris concurrently with the thiamet application, right before the thiamet on. We're still seeing some good return on yield and with revenue on dual side applications even still under high mega pressure. But at Prosper with no pest present, the combination of the Yuma and the Quadris, especially the Yuma at the high rate of two points per acre, we're seeing a significant sucrose loss. And then there was 10.6%. And then that's also about $175 per acre of a loss. Just because of that hit. And as many are aware, we lost the pyrophos, which Mark will touch on right after me a little bit more in detail. But with that, we have, I think we should repeat this research, looking at different alternatives. Registered alternatives, probably the pro-rethroids, probably with Mustang or Sana, and see if we have any interactions there. With that, I'd like to thank the shared group of research and education board, AgAge industry for chemicals and seed. Our cooperator, Daryl Collette, he was great to work with. My research colleagues at NDSU and also Crookston. And then also my summer assistants, they did a great job this year, gathering all the data that we needed to present to you today. All right, very good. As Jake alluded to, I'm going to try and address the loss of pyrophos. As far as I know, it's gone. I know there's some rumwings about lawsuits and that kind of thing, but I think we have to also think about the future and pursue aggressively, pursue other tools. And my talk, I always apologize for it because I, but I think it's what some people at least want to hear, too, is what we're expecting for the root-mate forecast in the upcoming growing season. Because those two are very much related. For those of you that are not familiar with the root maggot, especially our online audience, if there are any of the European friends, the root maggot doesn't tunnel into the root to cause its damage. It actually has a pair of oral hooks that it feeds with, and it does a rasping type of injury to the plant and then consumes the exudate from the root. And under severe, especially growl-thick conditions, as Jake's photographs really showed well, is that if that injury occurs early enough and is severe enough, and if it's dry, it can kill the plants. The root-mate killed a lot of plants at St. Thomas and Dr. Chu can attest to that as well for his plots. So yeah, it's a very significant economic past. It's more than just stand-loss, too. We see significant yield losses. And so when we run our trials, we do rate all the plots on the zero to nine scale of Campbell at all, because we need to validate that what's going on is actually the product of root-meget feeding injury. My methods are very similar to Jake's, so I won't go into that too much. I just want to point out that in those combined analyses in both Jake's presentation and mine, I really, I'm pretty OCD about my stats. And when I make recommendations, I want to make sure that I have the, I guess, the teeth and the data, the robustness in the data to make those recommendations and then be reliable. So with that, so anytime you see a combined analysis, it has been tested and quite vigorously. This first slide is the results of an ongoing trial that we've had actually for quite a few years, but these are common treatments that we had the last couple of years. And I chose 2020 and 21 because that's where some of the, a little bit of optimism came out of those runs of the trial. You know, the treatments are kind of changing from year to year, but these are common to those two years. As the one thing to point out is the, quite obvious, but the red oval. And by the way, one thing to point out on this particular slide is that these are all single application treatments. So they're either an at-plant band, usually, yeah, either if it's a granular, it's just a conventional band. If it's a liquid, it's a three inch T-band over the open seed furl. And so we've got granulars, conventional granulars at the top, the highest labeled rate of counter followed by 7.5 pounds, which is what we kind of consider a moderate rate. And so when I run trials like this where we're looking at new products, I'm really beating the bushes, hoping that we can have something that is at least kind of in the ballpark of the way that we know counter manages the root magging. And so the good news in this slide is that within that blue rectangle, those four treatments were all not statistically different from each other. So the, the, and it's not really, Asana is not really an experimental, it is registered for use in beats. But many of the other products are experimental. But what we found, and this is a trend we've seen now for two years, is that when we add exponent, which is a synergist to Asana XL, we tend to either get numerically or significantly significant increase in control and in yield benefits as well. It's not always significant, but what it does is it improves that the performance of Asana enough that it's, it performs at a level that's comparable to any of the standards, a single application of the standard. So that's one good take home from here. On the far right, similar to what Jake's slides showed, I like to take the untreated control. So a grower or an ag advisor can look at that and say, okay, how did the treatments perform compared to doing nothing? What was the benefit? It's not truly a net benefit, because I'm not taking into account the cost of, of the control measure, because that is so it's such a moving target. But as you can see, we got very good returns out of all of these treatment or all of those top four treatments. Unfortunately, we didn't get very good performance out of Diabrome. It's, I would say one that's maybe we need to look further at and that give up on. I was very disappointed in this two year analysis on Vid8, though, because we've seen better control out of it in the past, but obviously it did not shake out too well. Just a few pictures. This happens to be the plots, what the plots looked like in 2020. So it's not quite as dramatic as what the photos that Jake was showing, but it does show fairly well the contrast between Asana, the upper left, and then the center one, where we added the synergist. And so I think that that illustrates that pretty well. On the far right, top row, top right, we have Endigo ZCX. That was not in the previous slide because we were initially looking at it as a T-band. And I'm told that the company that manufactures that is probably going to be going with a broadcast recommendation. So in 2021, we did test it. It's just that it was used as a broadcast. And we've gotten encouraging results out of both years, just different placements. This next one is kind of a busy one. So I color coded it for you a little bit to break it down. Basically, we're kind of looking at MiDAC and then BiFender as well as alternatives for Ruben Control. And MiDAC does have a label for use. It should be BiFender, is not registered at this time. So essentially, this is kind of an experimental trial as well. But we got a very good performance out of combining Ponchal Beta and some of these, as you'll see, they include a 1034 old starter fertilizer as well. MiDAC is known for being a pretty good paint mix or friendly mix partner with 1034 old. And that top treatment did very well, as you can see, comparable to the highest labeled rate of counter with regard to reading tree ratings and then yield and revenue also. Another trend that we observed was this three inch T-band of BiFender. That actually was statistically superior to the dribble in furrow, which is, I know if you're a grower, that's kind of probably a disappointed finding because you'd much rather maintain micro tubes on your planter than a nozzle system. But I've seen that before with pyrethroid materials. We've seen it with Mustang on springtails. Those materials seem to work better when they're applied as a T-band. Next, this is a two year combined analysis. We're wanting to look at Mustang. We have a lot more data on Mustang. I just don't have time to show you everything today. What this entailed was the single and then double applications of either Yuma4E, which Jake had mentioned, is for para-foss formulation, essentially the same as Lord's Band 4E. Unfortunately, in this two year combined analysis, the combining Yuma, as you can see, the counter is the common base treatment for everything in there other than the entry to check. But the contrast there is the Yuma applications that worked very, very well. But I think Mustang may have a role. It's just that we may have to apply it more than twice or we may need to throw something else in there or use one of those more aggressive at plant program. This next one took me a long time to analyze. It's seven years worth of data, which is a pretty sweet spot to have and no pun intended there. So it's a very strong data set indicating that the good old combination of the high rate of counter and this is under pretty significant group mega pressure. I included 2021 in their same location as the plots that Jake presented to you, the St. Thomas location. And so we had good pressure throughout this study and we got excellent performance out of these combinations. As you can see, that revenue gain above the entry to check. So compared to doing nothing grossing, you know, a differential of $438 is pretty darn good. Let's see. And another thing to point out is that in addition to counter at the high rate being well, it was not out, did not outperform comparable programs that included poncho beta at planting with either counter at plant or as a post emergency material. And that's something we've been looking at for a few years now. We're getting very good performance out of counter as a post material. The grower just needs to know they can only apply that counter once. So it just depends on what how they're set up for applications. So to summarize the insecticide stuff by Fender FC, I think it's interesting and I'd sure like to keep looking at that. And we've seen a pattern of performance where the T band tends to work better. We've looked at post emergence as well. And I think we still have to figure out kind of isolate the best time to apply it. And indigo ZCX as I mentioned, I didn't show you data on it, but we it's looking somewhat promising. We just need to understand how well it's going to work as a post emergence broadcast. And interestingly, also the year that we ran it as a T band, it was comparable to counter at both the high and the moderate rate. Ekazine plus modest potential with that material. And I couldn't show you that data either because it wasn't common across those two years, but it's something I could dig back into and probably study more. But I think it's something that we should be looking at further because we're kind of running out of tools. As you saw a sauna perform better when we added that synergist, and that is a synergist that is quite specific to improving the efficacy of pyrethroid materials. So I'd also like to look at exponent with things like, like bifender and Mustang as well, maybe get a little more bang out of them. Counter 20 G continues to work well as a root megatool. Mydac, both dribble inferral and the the three inch T band over the years has over the last few years has looked okay, at least in the in the ballpark of the moderate rate of counter. So there's certainly good potential there. We just need to understand it a little better and research it more. Mustang max is that one chart showed it's it's not quite as is effective as a chlorphera fos, but I think it's it's certainly going to be a tool we're going to have to get used to using and know how to use it best. And then time at 20 G, as the granular slide showed you is also a very good performing tool. And as I've iterated many times, it's very the timing of application can be very flexible as a post emergence tool. So just a couple of slides about the root megat forecast and population trends. Unfortunately, I mean, I guess it's nice to be winning, but the the magnet I think is the one that's winning, but I wasn't really looking forward to having another increase in the overall root megat fly activity. But this this is valley wide. And 2021 what actually represented the highest root megat populations. And this is valley a valley wide average in the last 15 years. So we've got work to do this next slide transitions, you've seen this one before of just it'll skip every other year. So 2018. This is what our forecast looked like. Oops. 20. I'll go back 2018 2020. And this is what we're expecting for 2022. Not necessarily a whole lot more of the intense high pressure, but it's spreading out a little bit. And then the moderate pressure areas, moderate risk areas have expanded. So I'll skim through this this will be presented at the grower meetings and on the websites as well. So, but we've got a lot of high risk areas, and even more moderate risk areas as I mentioned. So with that, I'll wrap it up. Just want to make sure I thank the army board. We really appreciate the funding support you provide. We believe we put to good use. And we work really hard to hopefully provide your the growers you represent with good returns. I want to thank the cooperators, Darrell Collette this year and Wayne and Austin Lissard for several years and probably more in the future. American Crystal ag staff, seeing our ventures out of St. Thomas, North Dakota, Germain C technology, the crop and the pest management companies and seed companies as well and our fabulous summer crew that we had last year and then partial funding is also provided by USDA and FF. So with that, I will be around until closing time. So thank you.


Navy Recruiting Command launched a new social media initiative May 1st. Project Archituthis gives you a look into the career opportunities in the Information Dominance Core. The online cryptology game runs for 18 days and gives players daily puzzles to solve to save your shipmates. Information about the cryptology career field may be hard to find, and the goal is to generate awareness and educate the public about the Information Dominance Core. Navy cryptologists analyze encrypted communications, decipher foreign languages, jam the enemy radar, and maintain the equipment and networks necessary for classified intelligence. To see if you have what it takes to solve the puzzles and save your shipmates, visit the Project Archituthis Facebook page. From the Defense Media Activity, I'm Petty Officer Jen Blake.


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So, good morning everybody to our talk, GRAS-GS in the sky. GRAS-GS is a high performance remote sensing toolbox. I'm Markus Nittler, part of the GRAS development team, together with Moritz Leonard and Markus Mitz. We are presenting here, latest and greatest, with the focus on remote sensing. GRAS is an OSGO project, by the way, exactly today. It's the 12th birthday of OSGO, in case you didn't know. So, 12 years ago we founded OSGO in Chicago over a long weekend, and then it all evolved in what you know with more than 30,000 unique subscribed people in the various mailing lists and conferences every month somewhere in the world. Well, so here we focus on GRAS-GIS. In this very first slide, I just want to show the last roughly 35 years in one slide. You can imagine that the history is tremendous and GRAS has come a long way, developed since 1984, since 99 under GNU-GPL license available, and we try to renew the project continuously. And, of course, it's an open development community. What you can see here are all the various links to different software packages. I don't want to mention them all. Since GRAS 7.2 there, or 7.0, basically, 7.2, there is time series processing, raster vector and volumetric data available, and you can do a lot of things like also looking at time series, even reconstruct them on the fourth. This is the graphical user interface. You can process LiDAR data. You can process 3D water flows. In the morning we had something about this, and naturally vector topological vector processing engine is there, and we have also Docker file, if you are on Docker, for example, we are using it in HPC, and we will see something more about it later on. Just to tell you GRAS comes naturally with a Python interface. This Python interface has been simplified recently, something called GRAS Session. You can use just to initiate your session, which means in a few lines, like with GRAS Session and so on, you can create it and then you can just go ahead and do your analysis. So nothing complicated, and like other software projects, you can go through, load your data set. It is internally using, as before, the GRAS GIS database, but if you work like this, you do not really have to think too much about it. What you do have to know is, of course, what the projection is and other stuff like that, but the session manager is doing it all for you. Recently, which means a few days ago, we published GRAS 47, 47.0 actually, which means, sorry, 7.4 of course. Okay, so many numbers. 7.4, thank you. It comes with a lot of features, which I cannot list here. There is the web page up there. You can check, the presentation has been uploaded just to highlight a few things in case you are already using GRAS GIS. This is an example here, processing Sentinel data in terms of wildfire. This is a wildfire somewhere in Australia. You see the RGB composite there, which is basically showing smoke, and there you can see more or less where it is burning. This is a feature of Sentinel, of course, but you have all the possibilities to process multispectral data here. If you start GRAS, if you are new to it, you can now just download a demo dataset. One we are using for a long time. This you can with a click download and then go through all the examples in the manual. We have been working on auto rectification. It used to be in GRAS 6, and it took us a few years to bring it also to GRAS 7 because of different updated concepts there. So that's back. R in GDAR, R external are the possibilities to use or even just register data in GRAS database. Register means you just tell it where the original geotip or whatever file is, and then you can use it in the session itself. So no need to duplicate data. We fixed some handling with data which exceed the 90, 180, 180 degree definition which happens with global data, which is quite essential if you work with such data. By the way, cloud optimized geotip you can also read because it is based on GDAR, so that's fairly easy. Export improved, clipping for vector data made easy, and then tons of other fixes which are there. Just to now drive you more to the topic here, which means remote sensing. We have been adding more satellites to the atmospheric correction. It is based on 6S. 6S is also used elsewhere, like an Arc-C for example. And we have been adding a tool in order to process more decentralized data more easily. More decentralized data come with additional layers of quality. So in each pixel you get information about the qualities that is extremely useful, but it can be a bit tricky to process these bit patterns. And so you have a tool here which is helping you with that. So I switch to Moritz, who will now present on remote sensing and grass GIS a long history. So just go ahead, have a seat if you want to come in. So yes, as Markus said, we're kind of zooming in now into the main topic which is remote sensing. Before then, Markus Metz goes on to show you the example of how to do this in a high performance computing environment. So grass GIS as such has a very long history, and the remote sensing in grass GIS is almost just as long in terms of history. You already had first sub-modules available in 1986 for grass 1.1, and then from grass 3.0 in 1988, you had a whole suite of modules integrated into the core grass, which are the I dot something modules, so the whole imagery family. Ever since we've had steady improvements and additions really constantly, there's been constant evolution also following obviously the changes in types of satellite data that we can use. And we've moved from what you can see at the top, very simple text-based console in the 1980s to a much more complex and modern GUI system to handle all that data. What is quite important, I think, to understand also and somewhat of a product also of the long history of grass and the fact that when grass was written at the beginning, computers did not have the same capacities as they do now. A lot of the grass internal libraries and grass modules are very memory efficient. So you can work with a lot of very heavy data and then we'll go back to that in the high-performance computing. So what can you do in terms of remote sensing with grass? And the motivation for this talk also came from a colleague who when they told me, oh, I've known about grass GIS for a long time, but I thought it was a GIS and didn't even know it can do any remote sensing. So here's an overview of a series of pixel-based techniques that we have from pre-processing where you can do atmospheric correction, punch-happening whole series of different techniques. You have transformation, very different modules that allow you to do principal command analysis, wavelet transformations. You can calculate a whole series of indices, vegetation indices. Edge detection modules. So a whole series of transformation possibilities and indexes you can create. You have a whole classification, pixel-based classification suite where you can do maximum likelihood, but also the ISMAP module, which is probably one of the first, let's say, hierarchical segmentation-based classification modules, even though the output is pixels. It is based on very different levels of hierarchical segmentation. You have access to modern machine learning techniques where we normally don't kind of develop them, redevelop the wheel in grass, but we use outside tools, either sci-pi or R tools that exist. We also have a whole host of specialized modules which look at specific topics. You have a whole suite of modules looking at evaporate transpiration. You have energy balance modules that use satellite data to calculate energy balance information, biomass. We have a module that works on gravity measures, even one which uses data from a moon mission so you can do even extraterrestrial planetary science can be done with grass. So a whole series of modules available on pixel-based, maybe just as an addition to say that there's obviously a series of, let's say, generic raster tools which are very useful for remote sensing as well. So we do have a map calculator as well which allows a very, very wide range of operations. There's, as Marcus said, time series management and you can do a whole series of types of analysis of these time series, so these are all available. The second part, which is, let's say, more recent is the object-based image analysis techniques that have been developed, also known as OBEA. We've developed a module which does segmentation which divides your image into objects and there's a whole tool chain that has been developed to go from the automatic, let's say, segmentation parameter optimization all the way to machine learning base classification of the resulting objects. So you now have the full pipeline available in grass with wherever possible the idea to parallelize and so to make it possible to work on very, very large images in this pipeline. Very recently as well there was a creation of a module to create super pixels which has been kind of a fashion last year as well which then allows you to kind of reduce the complexity of an image by grouping pixels in a certain way as well. And we're not stopping, so many more elements are being constantly developed. There's a whole suite of LiDAR tools as well that allows you to import LiDAR to treat LiDAR. Marcus already mentioned the suite for the creation of orthophotos and there's current developments going on. We have several students working on neural networks and integration of neural network techniques into grass currently. There's work going on trying to create what we call semantical cut lines which is very helpful when you do tiling in order to be able to parallel process your images. One of the problems when you use classical straight lines is that you have edge effects so what we're trying to create is cut lines that allow you to go through the image and cut your tiles, irregular tiles according to, let's say, characteristics of the image where you say this is a good place to cut a long road or things like that. There's a whole host of extensions so a few years ago, especially with the Python API evolving, there's been more and more extensions being created by researchers all over the world by contributors and there's a whole host of extensions in remote sensing as well being created constantly. And there's permanent work on ongoing trying to obviously increase the performance. We had the debate not too long ago because we reached some issues where we got above two billion objects being created in segmentation so we're really, really large images and so these are issues that we're faced with now that we're trying to work with. So I will give the floor now to Markus Metz, who will give you an example of high-performance commuting with grass. Okay. So I will continue to provide an example how to use grass with high-performance computing. First of all, I want to explain why grass is particularly suitable to use for HPC processing. First of all, all the grass modules and the libraries they have a very low memory footprint. They never load the whole dataset into memory. They always only load that part into memory that is actually currently processed. So even if you work with a raster map that's a few 50 gigabyte or something like this large the actual memory footprint can be as low as one megabyte, for example. That makes it particularly suitable to run, to parallelize it heavily and run it on a high-performance computing system. Second, grass is not a single application you can rather regard it as a toolbox and grass provides a few hundred tools that can use independently of each other or also as a processing environment. The example here is analysis of reconstruction of NDVI values that's from MODIS. This I did globally just to show an example in South America and northern parts in the Amazon rainforest. There are lots of gaps and I want to fill them. Here I use harmonic analysis of time series, just as an example. That's a short example for how this looks in time here on the lower right.  So I want to reconstruct in space and in time. With this harmonic analysis of time series the whole processing is actually done only in time so I'm not doing any special interpolation or something like this. So my understanding of high-performance computing or as I have used it in this example is I have a master node that can also be a compute node and any number of compute nodes. So compute nodes are facultative, can be zero compute nodes or thousand compute nodes depending on what you have. The components then are, we have this master with a job or queue manager. There are lots of different job and queue managers, job schedulers out there. Therefore I will not go into detail just to mention a few common examples that you find on university clusters or something like this are talk and slurm. There are also talks on the other deaf room session on HPC computing that go into more detail about this. Considerations when you're running graphs on a high-performance computing system are the actual hardware resources available for each compute node. This is needed to like tailor and design your workflow, how much load you can actually put on each compute node otherwise you will get all sorts of problems I'll come to these problems later on shortly. So the general idea here of parallelization is that we are running several graphs commands or graphs modules at the same time on the same compute node or on different compute nodes. Before we actually start we need to create chunks for parallel processing. One option is to create temporal chunks and the other option is to create spatial chunks that depends a little bit on if we are doing temporal processing or spatial processing. In the example here you see the solid arrows show the temporal slice that I want to process like I create two slices, one and two and here I actually add a little bit of overlap to avoid spatial temporal discontinuities and the overlapping part of one I throw away and the overlapping part of two I throw away of the dotted lines and only keep the solid lines to have a seamless reconstructed time stack. You can also create spatial chunks that has also been quickly mentioned previously with G-dial for example. You can create virtual raster data sets that are chopping up a large raster into tiles. An important concept in graphs here is the computational region which is defined by the extent of south, west and east and the number of rows and columns. Considering these you can chop up a raster in any number of desired tiles. You can also create predefined regions instead of chopping up the raster physically you simply pre-define these computational regions. For spatial processing that is when I want to do some spatial interpolation or creaking or something like this I recommend to use each time step as one chunk for the parallel processing because the spatial chunks might suffer from spatial discontinuities which are very difficult to fix later on. Now a little bit of the inner workings of how this high HPC workflow would work. First I create a script with actual grass commands that do the actual processing within a given grass session. This I can run by hand on a laptop just to figure out an optimized workflow then I create a second script that creates a unique grass session. Marcus has mentioned this before. This can also be done for example of the new Python interface for our session. Here I prefer to do this manually more or less manually because I'm fine tuning the settings a little bit for HPC processing. So this script number two is then actually running script number one copying the results to a final destination and cleans up everything. Script number three is highly dependent on may not exist at all. It depends on your job schedule that you're using to manage the different jobs on your HPC system. The grass session is divided into two components. First we have to set up the grass installation, some environmental variables and also paths like we are the grass libraries and the grass executables and so on. This is all done automatically on import and then the actual session which means we have to define where the spatial data are located. A little bit more into the inner workings but I won't go into too much detail. So we have a special file called JSRC for the settings of the grass session and the most important component for HPC computing with grass is that we need temporary like environments sandbox the whole computation so that the different compute nodes are not interfering with each other and in this case it's a temporary map set that I'm creating. I do all the processing and at the end I copy everything back. Cleaning up can be as simple as RM minus RF, blah, that folder, gone. And done. More information is of course also on our Wiki page about how to set up a grass session more or less automatically or for batch processing. There are also a few more examples. The important part of that job manager that we are using here is we must have a queue, something like this where I designed, I started eight jobs four jobs are running for the next four jobs there are no hardware resources available so they are in the queue and they will start when the first four jobs are finished. Now comes the problem that we have experienced or I have experienced in the past so let's assume we have a number of jobs they all do their processing independently finally I want to keep all the results somewhere on a final destination and every job is writing to a final destination storage and that's the situation the time when the whole system is going down and crashing. Yeah, so it depends on you can put HPC systems to the limits and it depends on how they are set up it's worth to try out their limits first. Another example also what we did recently is land surface temperature processing we have in this case a time series of about 30,000 maps which we processed with HPC methods and yeah, so essentially we want to get from gaps in space and time on the left-hand side to the fully reconstructed map on the right-hand side and we want to do this 30,000 times in parallel something like this. The most important when you do HPC processing you need to have a good admin that fixes the system after you broke it and just for clarification I'm the one who's breaking it I'm not the one who's fixing it. Thank you for your attention. Disk space, maybe not so disk space is usually fixed the only solution is to buy more disk space. It's easier to buy more memory so if you want one terabyte more disk space this is easy to buy but one terabyte of memory is a little bit more of a problem. Another solution maybe is to run less drops in parallel and then use some external storage where you have enough disk space for the final results then you can avoid the high disk consumption for intermediate data. I'm actually never running using the HPC system on full power like on full CPU power because the bottleneck is reading and writing the data. Usually we do not create any temporary files but a workflow, more complicated workflow like for land surface temperature reconstruction consists not only of one single processing step but of 15, 20 steps and we have to monitor each step each step is producing output which is then becoming input for the next step depending on the processing you cannot simply pipe it through memory to the next step because memory would explode and we also need sometimes to keep intermediate results in order to figure out what went wrong. If everything went fine we simply delete the power command rm-rf everything and we have our disk space back for the next drop. Yes, so yeah, that's part of the optimization of course you don't want to create too many intermediate products or intermediate data but depending on the complexity of the workflow and for NDVI reconstruction this is straightforward actually we do not have any intermediate data because this hunts procedure is immediately producing the final output for land surface temperature I have 30 intermediate products because the workflow is complicated I have to check that the results are correct that I want to use as input for the next step so this is... or you can't do it