 North Dakota breeding programs are very important for the state. A lot of material is tested on an annual basis. Breeders are now trying to utilize technology like remote sensing, robots and drones in order to speed up the breeding program. We have this project, it's kind of an internal project within NDSU. We have all this effort known as Precision Act, right, within NDSU. There was a group of breeders that got together and some of us have been doing this for a little bit. Some others are still kind of in initial steps. But the idea is how we can use Precision Act to make us more efficient. So in terms of potato production and potato research, the interest in the utilization of drones or other new technologies such as robots in assessing traits has kind of come to the forefront of interest. As you know, a breeder has to evaluate thousands of plots. So how we can use this new technology, let's say drones, robo-carts, anything that makes possible to measure thousands of traits and thousands of lines that we have in the field and measure each one of those traits in a very accurate and fast manner rather than just going with a fieldbook and counting, counting or taking scores. Hopefully just one fly or two flights with the drones or with two passes with the robo-carts would allow us to measure some of those traits very easily, right? Much more easier than what we're doing normally. In our potato breeding project the last couple of years, we have worked with Dr. Palo Flores on utilizing both drones as well as a small earth-sense robot in our screening efforts for herbicide tolerance specifically to the potato herbicide metribuzin. A couple of examples I can give you. This plant, for example, right now in the leaves, it's dealing with an issue called common bacterial blood. This is a bacterial disease and we usually come and take a score, a visual score, plot by plot. What if we had a drone that could fly around this field and have a reading for each one of those things automatically? And the traits that we are targeting today is the common bacteria blight and all of these plots here, they have been screened for this trait visually. Perhaps utilizing a drone or utilizing a robot, we would be able to determine stand and stem counts for a potato that's very important in determining yield potential. Having the ability to do some under-canopy plant temperatures when we're considering potato diseases such as verticillium wilt, we may be able to identify specific selections or named cultivars that have a cooler under-canopy temperature. What if we had a robo-cart that was driving through here and counting pots and kind of using that information as a proxy for yield potential for this specific variety versus this one and this one, right? We can start making comparisons. Different maturity rates. As you can see in this field, we have some lines that are still green, some others are drying down, some others are almost ready to harvest. What if we can estimate those differences in maturity just using better technology and still being accurate? Findings of this research also will have implications for large-scale farming. We can think of remote sensing as another tool to predict yield, stand but also to make management decisions regarding diseases in the field. However, a lot of work has to go into developing the algorithms and many research plots with small combines to get an appropriate yield will be needed to get to the final product of prediction tools for farming community in North Dakota.