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We’re currently going through our 3rd crowdfunding campaign, part of a wider investment round. I’ve been writing quite a few updates, and talking to a lot of people about our business, our tech and where it’s all going… here’s a few of my thoughts and plans!

An arable farming ecosystem is incredibly complex, with many variables. This makes it hard for farmers to truly optimise the way they farm at a high level. Automation and AI can and are helping to simplify some of this, to allow farmers to optimise the way they grow crops like never before.

In order to explain our vision, and where we see ourselves in 5 years, it’s important to cover, briefly, the stages Agriculture has been through, bear with us!

Agtech is the 4th Agricultural revolution, or the 5th – it really depends on where you are in the world:

Ag 1.0 – Lasted for 10,000+ years – Man or Women or Horse, pulled a plow themselves, they used tools, but not machines.

Ag 2.0 – From the 1800s mechanisation started to take food production to a new level. The age of the tractor had arrived.

Ag 3.0 – After WW1, chemistry again revolutionised the way we grow food, we could now apply substances to crops, to help them grow, or to kill things that restrict yield.

Ag 4.0 – Here things get a little open to interpretation… In North America (and some other countries), biotechnology allowed plant breeders to take what they’d done in the past (search for better characteristics in crops to help deal with abiotic and biotic stress) to a new level – gene editing. This allowed those countries to use much less chemicals, relying on those enhanced plant characteristics to better protect themselves instead. But many countries banned the use of biotechnology, this means that even now, many countries (most of Europe for example) still use mainly chemicals – they are still in Ag 3.0.

This doesn’t mean countries that use biotech do not use any chemicals, but they do have better options. For example there is a bio-engineered strain of Oilseed/Canola that is resistant to Glyphosate (typically a chemical that kills all plants – it is not a ‘selective’ herbicide), this means that farmers growing this crop can use only Glyphosate to kill all weeds in that crop, in one go, in much less quantities than it would require with other chemicals. Farmers without access to this technology have to use multiple chemicals, in multiple passes to even get close to this level of weed control, resulting in the use of more chemicals, at more cost, more CO2 emissions and more soil compaction.

So where do we, and our technology come in?

Ag 4.0 / 5.0 – Agtech: Smartphones, data management, RTK GPS, Drones… AI? (some may argue that true AI will result in Ag 6.0… or 5.0 – it’s getting confusing!). Anyway, we’re here, this is the Agtech revolution, and we’re just getting started.

Let’s start with the glyphosate example above; farmers with or without access to that special strain of Oilseed will still benefit from knowing more about their crop, knowing how severe the weed pressure is and where the weeds are. Skippy Scout helps them to control weeds more selectively, both spatially and temporally.

The farmer with the special, glyphosate resistant strain, can use Skippy Scout to quickly measure the severity of weeds in the field, there might be none, or very few, in which case, why spray at all? Save the cost, chemical and time in-field… It might not be worth the cost, vs the small potential yield loss.

The farmer without access to that biotech can use Skippy to again tell them if there is an issue to deal with or not, and measure it. It can also tell them where weed patches are, and allow them to identify what type of weed is present, this allows them to target smaller areas or the crop, with specific herbicides, reducing waste, chemicals, and time in-field.

There are lots of examples like this, where different farms have access to different levels of technology/chemistry/biotechnology/(and even some that don’t have access to mechanisation yet). In all cases, simple, easy-to-use, time saving drone technology (with a low barrier to entry), can help. There are farmers in Africa that were using horses, and manual labour until recently – they are now using drone technology to monitor and spray their crops – they completely skipped Ag 2.0, no tractors on their farms.

Ag 1.0-5.0 – All this leads us toward infinitely sustainable agriculture – the “end goal”; this incorporates net zero, producing more food with less resources and a whole lot more to describe a type of farming where everything is in balance, which will allow us to feed the world population forever, in a wholly sustainable manner.

So finally, we get to ‘Our Vision’

For us, it’s all about providing and interpreting data at as many levels as possible (or makes sense at least), in an automated, efficient manner. Then making sure that output gets the right place to take targeted, efficient and effective action, where needed.

Our technology won’t take us to infinitely sustainable agriculture alone, but it will help, and integrate with all the technologies, combined, that will.

How? Well you can already see our plan starting to take shape, in what we’ve done so far, what we’re currently doing, and what we’re planning to do with your help and funding…

The ‘levels’

Let’s start at the bottom and work up, and across a crop’s growth cycle…

  1. Soil. As you can read in a previous update, next year we’re going to build an automated, drone-based soil sampling system. This will allow fast and efficient soil analysis, telling the farmer what is in their soil before they plant the next crop. Understanding the solid nutrient status before planting, allows optimal nutrient application to the crop during growth – farmers don’t want to give the crop more nitrogen than needed – so they need to know how much there is available in the soil.
  2. Planting. Soil maps tell part of the story about how many seeds should be planted in a given location, combine this with zoned crop data from the previous season, and terrain data, to create an optimal variable rate seeding map. Robots could plant seeds instead of tractors, reducing soil compaction and increasing accuracy. For some crops, drone spreading systems could broadcast seed instead of planting it.
  3. Emergence monitoring. As plants emerge from the ground, Skippy’s hi-res imagery and AI models count plants per square meter. This is used to make early decisions on re-plants, early yield predictions and helps to optimise next year’s seeding plans. Early yield knowledge helps farmers plan for contractual obligations and negotiate new pre-harvest deals.
  4. Early growth. Crops are monitored for signs of pests that might damage the crops and their yield potential, insect damage and weeds in particular. Skippy can see insect bites on a leaf, and count them. We can measure severity and then zone areas of concern, allowing for guided application of pesticides as and when needed. Here, ground robots or drone-based spraying systems are able to target specific areas (or even specific plants), with little to no ground impact. It’s all about using the right machine for the job – lots of weeds – a tractor is probably most efficient, a few patches – use a drone, individual weeds? – robot! There could be a future with no tramlines in a crop!
  5. Mid growth. Control of pests continues. Green Area Index (GAI) is also measured as an indicator of crop nutrient status, then combined with soil nutrient status, to create an optimal, variable rate, nitrogen application plan, putting only what N the crop needs, where it needs it. Nitrogen is heavy, drone spreaders could do this job, but a few would need to work together to be effective – in many cases a tractor would be a more efficient choice – we’ll find out more next year!
  6. Late growth. Depending on the crop, Skippy will measure flowering% or count ears, grains etc, in order to help with late crop treatment timings, and to predict potential yield. The timing for application of late-season treatments is critical, and getting an accurate estimate of yield is crucial for farmers to understand their position and make the best business decisions possible.
  7. Harvest. Scout Spheres and Skippy’s AI reports show the farmer how a crop is dying-off or ripening, where that’s happening more/less, and what stage this is at, and helps to make decisions about desiccation timings. Ideally a crop will die-off naturally and all be ready for harvest at once, in the real-world this rarely happens, so crops usually need to be ‘sprayed off’, so they can all be harvested efficiently, at the same time.

The ‘Automation’

Imagine all this being done by drones (and robots) that deploy automatically from base-stations when needed. Of course this will happen in steps:

  1. We’ve started this now – a drone automatically flies around a field, collecting images that are then interpreted by AI models, providing easy to understand, actionable information to the farmer. We also start sending data to machinery for application.
  2. Next, we move to recommendations, to tell a user when and where they should scout with the drone, based on various 3rd party API inputs (i.e. weather) and previous scout results.
  3. Then we move to base stations (Skippy Nest) where the drone is deployed when needed, by the user, or us, but the user does not need to be on-site. Say hello to Alexa (or Siri etc. etc.) here: ‘Hey Siri, please tell Skippy to scout my wheat fields’
  4. Then, 2 & 3 can be combined for drone deployment to be triggered autonomously, when conditions have been met that warrant a scout. Here the app, or Alexa, will simply inform the farmer that a flight is scheduled, or has taken place, and what the results are: ‘Alexa, ask Skippy for the status of my wheat fields’ … ‘Skippy says your wheat fields were scouted yesterday, three are showing signs of disease and all have an average of five percent weeds, check the app for more details’
  5. Automated deployment, analysis dissemination and, when required, the Skippy platform will send relevant, correctly formatted prescription data to the best tool/machine to carry out the required task. This could be a drone spraying system, a tractor, or a robot on the ground.

drones agriculture

In only 5 years?!

Yes – most of the tech mentioned here is already available in some form or another (we have the basis of what we need), we just need to continue building on the overall platform, integrate, optimise and help to get appropriate legislation in place; via advanced demo and R&D programs, potentially government funded through grants.

We have a proven platform, and a great base to build upon. The next 5 years are going to revolutionise Agriculture, again.


Jack – Founder and CEO at Drone Ag

Interested in Drone Ag? You can invest through our Crowdfunding round right now, take a look at:

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