Simcha Shore is a man on a mission — not merely to promote the services of his precision agriculture startup, AgroScout — but to help small farmers worldwide increase their crop quality and yield by minimizing disease and pests. He says manual, sample-based scouting — inspecting a crop by walking in a field — can be done far more efficiently with tech available to ordinary farmers, starting with a smartphone, but especially with an off-the-shelf c-drone. We met at Commercial UAV Expo Europe in Amsterdam on April 10, where he made a presentation about the challenges facing small farmers in an increasingly hungry world.
Q: With Simcha Shore from Israel at the Commercial UAV Expo in Amsterdam. Thanks for sitting down with us. Perhaps you could tell us a little bit about your company, what you’re doing now, what your plans are?
Simcha Shore: Well, I spent the past 20 years developing technologies for defense for the Israeli Defense Forces. And since I retired two years ago, I tried to see what I can take from this to agriculture. I had done a lot of work with remote sensing, from satellites and planes, in computer vision, all those kinds of things. And I found that it’s not advanced at all in agriculture. So I founded a company called AgroScout to revolutionize the way that we do scouting, the way agronomists collect information in the field so they can treat them. And what we do is early detection of disease and pests, which is a gigantic global problem. According to the UN, we lose more than 20% a year of the yield to diseases and pests. So this is a way to reduce that and increase the yield and reduce the amount of chemicals that we’re getting in our crops.
Q: Now when I saw your presentation yesterday, I was really impressed because you were like, you can start off with a small drone, with an inexpensive drone. No need to start right away with a fancy drone; start with your cellphone if you need to. In other words, I can see power on the software side to get started and to be able to move up. This must be very interesting for small growers.
Simcha Shore: Yes. So when I started to learn the problems and the challenges in field crops, I learned that more than 80% of the 2 billion acres of the world are actually grown by very small growers, in Asia and all over the world. A few acres to 50 acres. That’s most of the agriculture in the world. Most of the solutions in precision agriculture and helping the growers are for bigger fields and bigger crops. And that’s not going to help us grow more, 80% of all of our crops are just not getting any solution, any agronomy which will help us grow more. And we can see by the figures, we see that in the US we grow twice as much potatoes an acre than in China. And part of that is due to more agronomy here and more efficiency here and less of that for the small grower in China.
Q: Now, I’ve heard you say a couple of times to people you’ve been speaking with that you can get excellent results if your images are up close. And I think you also said this has to do with what part of the season that you’re actually taking images. It seems you already have some data sets for certain kinds of crops.
Simcha Shore: Yes. So we started with potatoes, which is the fourth most important crop, and a global crop, after wheat, rice and corn. And it has very visual problems that if you don’t treat them, then you’ll lose the entire crop. Which happened in the 1840s in Ireland as you know, the blight which caused unfortunately a lot of people to die from hunger and a lot of Irish people to go over to the US; this is the same disease. It’s a global disease affecting and stopping the increase of growing of potatoes in the world. And so we’ve done several seasons of potatoes, we’re actually having our first commercial season, in North America this season for potatoes and we’re working on the data set for other crops. So now we’re looking at soybean and wheat and other major crops. We have to collect enough data from close with problems so we can train the algorithm to do it by itself.
Q: Now, what’s your business model like? I think you said that you have an app, but you also have an enterprise interface. What’s going on there?
Simcha Shore: Our business model is working with those providers that provide to the small and medium size grower. So it can be a consultant, agronomy consultant, can be chemicals, people that are selling to the small grower. And it can be also a drone provider that’s getting the imagery. So those are our clients, they’re going to have to go fly the drone, and they’re going to be paying a set amount of money a year. For the enterprise it can be a few thousand dollars; for a small grower, it can be $10 a month. So the pricing is relative to the user and how much data he is putting up. We are focused on the small grower. So the pricing is aimed for the small grower, because he’s the only going to be able to afford a few dollars an acre to put out for this.
Q: OK. Now, as I understood it, you deal mostly with RGB [red/green/blue] images, with classic photos. And do you work with other kinds of images or is RGB just the starting point?
Simcha Shore: Yes. So first of all, there are many companies using hyperspectral and multispectral sensors. They have been around for years now in satellites and planes and now also in drones. Here at the conference there are several companies. The challenge with that is that it’s hardware that’s expensive usually, and it mainly gives you information or insights on problems of irrigation and fertilization. It doesn’t have the capability to show you that there was a disease or pest. And that’s why we use the very close RGB. We fly just two meters (6 feet) above the canopy. And the second thing is the global accessibility. If I want a grower that has a hectare or 10 acres of soybean in India, then he needs to have a solution that’s simple. He’s not going to buy a drone with the multispectral or satellite and order that. But we do partner with Planet Labs and companies like that that do give us the near-infrared and the NDVI [Normalized Difference Vegetation Index] so we can give that to our clients. But for them it’s just the app. They don’t have to work with all these other people.
Q: And how do you see, drones in agriculture, precision ag, developing in the years to come?
Simcha Shore: I think the main vector is the autonomous vector. So now already the drone itself is a robot, it’s autonomous. With our solution, you just put it in a corner of the field, make a polygon, it flies around by itself. But what I want to see, and we already see this in the more defense kind of areas, we see box drones like Airobotics. It costs a lot of money, it’s relevant for a strategic asset. But if we want to see it in a farm, it needs to be a box for the small DJI drone. So I am sure we’ll see that. And once that happens we’ll have a full autonomous solution in the field. We already have a pivot that’s turning around there, that has electricity and Internet. Then once that’s there, we actually have an agronomist that lives in the field — and I’m not taking away the people, the agronomists, they’ll just be empowered to do a less statistic or field-level kind of process to an almost plant-level scouting, which will allow us to move to a plant-level treatment. That’s the real value. That’s where we can increase the yield and reduce the chemicals. Because today it’s ridiculous. They put their chemicals on the entire field regardless where the disease is.
Q: All right, Sim, thank you so much for sitting down with me today.
Simcha Shore: Thank you. It was a pleasure meeting you.