10 AgTech products/services we aren’t ready for yet

Nathan Faleide Strategic Initiatives Manager for AgIntegrated
10 AgTech products/services we aren t ready for yet
10 AgTech products/services we aren t ready for yet

As I sit here and ponder what are all the great things that are being created for the agriculture industry I also have to take pause to push myself down into reality so that I don’t dig myself down into a rabbit whole. You see, this is a constant issue for someone like myself who deals constantly with future planning and strategic initiatives.

There is always some new cool thing or company being created these days, especially in Ag. As of late I feel many have got swept up in the hype and illusions of what some of these things promise.

Everyone is to blame to a point, we are all trying to do our jobs or make money but with all this being said I figured I’d put together a list of what I feel we just aren’t ready for yet and basically why.

This isn’t to poo poo anyone’s dreams or realities or even look down on any group but just a “hey, that’s cool but it’s just not very practical right now for most growers.” So here we go and in no particular order…

1: Small field robots

This might be the most obvious of them all and while they are cool, the logistics to manage, maintain, and transport such robots on a grand scale isn’t there. Beyond that, the public perception and impacts to local rural economies haven’t even been understood yet.

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The logistics to manage, maintain, and transport small field robots on a grand scale isn’t there, says Nathan Faleide.

The logistics to manage, maintain, and transport small field robots on a grand scale isn’t there, says Nathan Faleide.


This is a tough one since there are groups having success at using some of these processes to accomplish real needs for real products. Unfortunately, many are also using it for hype marketing and the ag industry hasn’t really done a great job at weeding out the real men from the boys yet.

To add, there are so many variables in Ag that need to be learned but yet most of these processes likely haven’t had enough input yet to fully reach their potential.

3: Auto grain carts

This is definitely one of the latest cool things to come out that shows some real utility and practicality. Probably the biggest issue though is the cost of such a product and really just the trust of utilising it on a 200-400k machine someone owns.

Added to that is having to tell grandpa you‘re not good enough to drive it. I’m not sure how insurance handles this either and how its setup to dump a load or what happens with wet conditions. All in all, cool but needs more time to scale to reality.

4: Drones beyond line of sight

This has been talked about for awhile and while technically achievable it still has issues with the FAA and likely insurance. Lately the drone craze has definitely gotten a dose of reality but this one while needed eventually is still becoming tough to get to the next level beyond testing or special waivers.

Now that may be more in the States (although Nort Dakota where I live has exceptions) but it comes down to perception and safety still and those haven’t been fully addressed yet.

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Lately the drone craze has definitely gotten a dose of reality. - Photo: AFP

Lately the drone craze has definitely gotten a dose of reality. – Photo: AFP

5: Daily high resolution imagery

This one is more near and dear to me and one that I’ve dreamed about for a long time. While not alone in this, the cost and logistics to have data at sub 1 meter resolution daily is daunting to say the least.

Now, there are a few planned constellations going up in the next 5 years that say they’ll accomplish this but until they are up in space and working we won’t have it. Someday

6: Yield predictions

This is actually a fairly old process when you look at governments trying to understand yield of their country throughout the season. The thing is though its never been that accurate and there is not a good way of verifying it.

With more added datasets it makes it more possible but the idea is to do this at scale and within a few % tolerance. You’re going to need number 2 and 5 above first to get here on that level plus a few others like 7 and 9.

7: Automated agronomy

Everyone has heard of some of these tools as automated pest, weed, nitrogen detection or amounts. You know, stuff a person usually would do through scouting and testing. While some of these processes can give you an idea there are just too many variables to make it accurate and mainly a trusted data solution. It sounds great and easy but we are not ready to farm only based on what a computer tells us.

8: Full online ag retail

Now this one may be the most realistic and doable one on the list and to an extent is currently successful. The issue is I don’t see it penetrating the market much past 5% for awhile. Not because those groups don’t do a good job but more because people in Ag just really like to have physical places to get stuff.

This is changing and while buying may happen more online, it won’t trump the entire experience that comes with other products and services Ag retail provides, like Agronomy. The “Amazon” of Ag isn’t likely possible.

9: Scalable hyperspectral imagery data

This dataset has been around for some time and is used a lot in research currently for crops. Its a great data source and will be needed to accomplish many of the goals talked about and that are on this list.

The problem though is we don’t have even close enough research understanding what all the different spectral bands relate to in many of the different growing situations and practices. If we could figure those things out its going to change how we look and act upon every decision in Ag.

That’s just the first part, the next is getting scalable data and the satellites with this capability are not quite there yet either. Hopefully sooner than later though.

10: Fully transparent sustainability data

This one is a little different from the others but I added it since many talk about the want and need for sustainability in Ag. Well to do that you need data but good data and data that makes general sense. After that you need data that doesn’t scare people due to lack of education.

If we run away from the real inherent issue we just end up making things worse

We’ve all seen people get worried about this and that in their food because it has a long scientific name. How do we fight consumer perception while still supporting the general product even if it was raised correctly or friendlier?

We are not there yet and hence why it’s almost easier to sell a product with a “blind” standpoint. We need more public education for this to work and that is probably the toughest thing to do in this whole list.

Fixing the challenges

As with any list, I’m sure this one has its flaws and problems. Once again, this list I hope doesn’t deter anyone away from fixing these challenges and working towards making them better or even possible.

I think talking about issues in this agtech/precision ag industry is what is needed more if anything. If we run away from the real inherent issue we just end up making things worse so take this all in perspective and lets try to reduce this list for the betterment of agriculture.

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