Cropin’s Post

Transcript

Actually, businesses. Is basically management of life. And a crop is a life. Managing and modeling a life, for example, requires a lot of understanding, which our agronomists and the entire global ecosystem of agronomists really bring on that kind of expertise where they're just able to understand what's happening in a field just by looking at it, right? But there are a lot of variables that are at play. Take for example, the seed that goes in, the nature of the soil, the environmental conditions. During that season, we're all seeing what is happening with the rains this time with the kind of drop light situations in the very, very nearby pricings while the others are having a lot of rain, for example. So really being able to remain dynamic to ensure to mitigate risks is is one of the key aspects that I think everybody within the season really strikes spot. So given the. Variabilities that happen on the field with regards to whether with regards to pests, diseases that happen during the season, There are various strategies that you can kind of look at in terms of incorporating. The first one, of course, is a risk mitigation strategy where you can look at getting a clearer view of what's happening on the field and then. Putting into place mitigation strategies that can help. Really avoid or limit the impact of those risks that happen on the field. And the second of course, is a completely different way of looking at things, which is the risk avoidance part of it. So what if I were to tell you that given a farm, we could start looking at predictive analytics in terms of what could be potential diseases that could come for that variety and location given what is the forecasted weather in the next seven days. So that becomes information where we can look at even avoidance. Of those risks through preemptive actions that could happen. So typically we'd all boils down into how can we get information and insights about a farm that is being calculated continuously computed based on the behavioral patterns of a specific variety within a specific location. And if you are able to then kind of call out all of these insights and, and, and bring out those insights against every farm. Where then targeted actions could be taken to either completely avoid the risk in terms of let's say an early warning of a disease that is not yet manifested, but that it has a potential likelihood of occurrence in the next seven days. And that's information that could be used to really look at even avoiding those lists and of course minimizing impacts of any potential risks that could be that could be seen on the farms through again the the remote sensing computes. That happen at every farm level. So the crop and intelligence layer really brings out all of these it is able to surface out information about what a stage of a crop what what's what's the current stage of a crop given every any take. So it's computed every day again hyper tuned for every variety in location. We have the health parameters that come out, which is again hyper tuned for every variety in location, which means looking at all the remote sensing signals get that gets gathered. For a specific piece of land and then taking out the interpretation to see that if the crop is doing well or not, if it requires nitrogen specifically if there are issues on water stresses in in different parts of the farm. And all of these again become tool sets and information where agronomists are the farmers could to take actions to be able to mitigate them. And of course with the disease early warning system that we have, which is completely predictive analytics on the potentiality of an occurrence of a disease could serve multiple. Purposes one, in terms of completely avoiding the risk in case it is foreseen that it is slightly to for a certain disease to occur given the stage of the crop that it is at in the next seven days. We don't see it physically on the farm, but we do know that it's going to occur or where there is no potentiality of a disease to occur, then why you wouldn't do the normal spring. So that would probably also kind of lead to reduction in costs of operations because wherever spraying is not required. It's not done unless there is a certain established likelihood for any given disease to occur in the next couple of. Smart sampling specifically on on multiple grounds. So again, if we need to identify, let's say the spread of a pest infestation or a spread of a disease infestation once has already occurred, this again provides the tool set for the for the anonymous to be able to identify which of those regions in the farm are not looking as good as they should be based on the computers and the analysis that is overlaid by the cropping systems. Available on the mobile application of the farmer when they are standing on the farm. So they would be able to therefore really estimate what's the spread of this and therefore what's the impact on the overall either yield of the production that would come out or quality of production that would come out. And of course in all also boiling down to figuring out what would be the net impact of any of these kind of vagaries that could happen on the ground to the overall yield that is coming out. One of the critical things also that that is pertinent to mention is around climate smart advisory, right? So because a lot of vagaries that happen on the farm today are related to weather. There are crops, there are seasons that have that are predicted or supposed to have a certain weather pattern and the entire sowing and the production cycles are done based on the assumptions of all those weather patterns are going to look like but. We see a lot of these changes in weather and climate changes for real. And to be able to really call out and the ability to look at the forecasted weather and continuously monitor these changes and therefore the potential impacts of what's likely to happen as a part of the weather forecast on the crop at hand also is very, very pertinent information to the agronomist. Because these are things that are not as on today, but these are again predictive in nature. And therefore, preemptive actions could be taken to be able to mitigate some of these risks or even avoid many of these risks even before they occur.