10 Bold Predictions For Precision Agriculture

Corn Field SunsetThe future of technology in agriculture has never looked brighter, or more confusing than it does in 2016. We at PrecisionAg magazine have been at this for almost 20 years now, and we’ve seen the booms and busts, the game-changing technologies, the wild successes and the monumental collapses.

The only certain is uncertainty, and the only predictable trend is unpredictability, to quote virtually every futurist’s hedge on his or her road to making bold predictions. Knowing all we know, we shouldn’t dare to make any bold predictions about the future. Except for the fact that we can’t help ourselves.

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So, let’s go ahead and indulge. Over the next 10 pages are our best shot at 10 “BOLD” predictions for the precision agriculture market over the next 24 months.

1. Bayer-Monsanto combo will have ripple effects.

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Photo credit: Market Watch photo Illustration.

Photo credit: Market Watch photo Illustration.

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The Bayer-Monsanto deal, assuming it comes to fruition as expected, brings together two leading basic manufacturers of seed and crop protection with hearty commitments to precision agriculture. Monsanto’s acquisitions and overtures about the importance it puts on improving agronomic decisions are well-documented. But Bayer has been quietly working on its own Digital Farming strategy over the past couple of years, and is fully committed to turning data into recommendations that impact use of its products. And Bayer has the desire and capacity to take these initiatives around the world.

Ag Weather Service2. Weather data still struggles to find its place.

When Monsanto purchased Climate Corp., the rush to bring weather information to growers heated up virutally overnight. Several companies now provide weather information from yesterday’s rainfall to full-on predictive modeling, but growers we talk to are flummoxed as to how to fully extract value from the data they receive. Few programs have lived up to the deliverables that have been promised, and it will likely be some time before growers get a fully functional and usable weather tool beyond the basics.

3. UAVs provide value, but it is frustratingly limited.

Ag Drone

Farmers who’ve tested out UAVs (no names please, FAA is watching) have found some great one-off uses for them. From bare-soil imagery to assessing pest and weed infestation to weather-damaged crops and more, the drone is delivering some value. But many machine and software manufacturers are counting on the development of a business model by a service provider to the farmer, and that has proven elusive so far. For ag retailers and consultants who provide services beyond crop scouting, UAVs field scouting and imagery services present a daunting challenge as a bolt-on offering. The cost of maintaining the machines, the trained labor to fly the machines, the interpretation of data, and the integration of it into other services provided (not to mention liability insurance) all will continue to dog the market’s efforts to build a business from UAV service.

Big Data4. Consolidation moves big data forward.

The recent downturn in the domestic ag economy, combined with increasing regulatory pressure is driving more consolidation among independent ag retailers and cooperatives. More territory under fewer organizations should lead to more consolidated data management initiatives, and many of the best-of-breed data management programs currently gaining traction feature the retailer and the cooperative at the center.

Subsurface Drip Irrigation5. Drip irrigation grows significantly, especially in row crop regions.

Regulatory focus on water quality and conservation as well as nutrient optimization is not going away anytime soon. One answer, while expensive, is the installation of drip irrigation onto fields that not only delivers water, but nutrients directly into the root zone of plants. Drip irrigation is installed using high end GPS, so it’s not an inexpensive proposition. But as regulations increase along with the cost of not complying, drip irrigation will become an increasingly practical water management proposition.

6. A clearer path to robotics emerges.

Blue River Lettuce Thinning Machine

Mainstream autonomy in the form of assisted steering is essentially a decade old now, marked by the release of Outback Guidance’s price-breaking auto-guidance system in the early-mid 2000s. Straight-up unmanned robotics is making strides as well, as companies like Blue River Technology continue to find commercial hooks for its robot technology, among others. Over the next 24 months, technological capability improvements, reliable availability of wireless connectivity, and a wider realization of the real yield cost of soil compaction by massive field equipment will spur more interest and investment in smaller equipment that is more manageably controlled via robotics.

NDSU IoT7. Internet of Things (IoT) gets mainstreamed.

When everything from sensors to gauges to field equipment has the ability to report data back to a central location wirelessly, the possibilities for better management of crop production, as well as the entire farm operation, is almost endless. Big companies like John Deere and many startups are working on devices that collect and report data automatically for maximum accuracy and usability. In two years, leaders in IoT will be emerging and demonstrating clear benefit to agriculture.

Farmer and laptop8. Technology allows the average farmer to get bigger, but not too big.

As the digitization of the farm moves forward, farmers will be able to effectively manage more acreage on average. Based on research conducted by the PrecisionAg Institute, the current “sweet spot” for farmers finding benefits to technology is in the 2000 to 4000 acre range, which over the next two years we see emerging as the most common range for row crop farmers. The complexity of farming and the benefits of technology will allow farmers to stay viable and competitive without needing to scale up to the level of “megafarm.”

Sustainable agriculture9. Sustainability increasingly drives technology use.

Food manufacturers and retailers continue to be aggressive in their pursuit of sustainable sourcing. Programs like Field To Market, while not perfect, are allowing the food production players to test their current production approaches and establish some baseline standards against which they can establish continuous improvement. Over the next 24 months, many more companies will be engaged in sustainability programs, and a clearer path to sustainable production in many crops will have emerged.

10. A game changing yield assessment tool emerges.

Ag Leader - incab

We write this as more of a challenge than a prediction. While yield monitors are ubiquitous on row crop harvesting machinery, only a fraction — as few as 1 in 10 — are calibrated and linked up with a GPS system to provide truly accurate data that can be compared year over year. Farmers need a simpler yield measurement tool that they will actually use.

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Avatar for Rodger Rodger says:

Many think drones will be the future, but they are not the answer. Best management practices will get you through the rough times. good eye contact with the crop by actual walking is still the best when it comes to crop management.

Avatar for Rodger Rodger says:

It is not going to happen on a large scale. Not in corn and bean country.

Avatar for Rodger Rodger says:

Too high of a cost for the average farmer

Avatar for yojp yojp says:

Self-calibrating sensors on field equipment is indeed a challenge that needs to be addressed. Without consistent data at the input, trying to do any automated (or manual) analytics downstream is fruitless (pun intended, as poor as it is).

Avatar for JZ JZ says:

So what do you think the fruitful products in Precison Ag would be/are?

Avatar for yojp yojp says:

I think the high resolution, variable rate (VR) delivery implements (seeding, inputs, pest/herbicides) are only as effective as the data feeding the VR prescriptions. The data that can drive good VR prescriptions include prior yields, soil moisture, soil type, weather (historical, current, forecasted), imagery (whatever sources) etc. The quality and consistency of the sensed sources has to be high before any prescriptions can be derived. Then there is a reasonable chance of optimizing yields/profits/revenue while even being somewhat gentle on the environment. THEN, analytics can be created to do some interesting things and the challenge shifts to automating and presenting recommendations in a simple, non taxing way.

Avatar for JZ JZ says:

Honestly, I cannot agree more on your points which exactly explained why only guidance products are popular in China. I was thinking the data captured by the tech devices are precisely, consistently serving you many years ago.
The resolution of drone now is high up to sub-inch GSD(ground sample distance). The images are so inconsistent?
Maybe the precise data is like a secret that is veiled by now☺

Avatar for andrew andrew says:

1. Business model by service provider (yes a problem for now) (2) cost to maintain is very low other than if you crash (3) interpretation of data – Software as a solution ? 4. Cost of camera and processing are barriers (4) You will need to plug the data into analytical software 5. liability will come down as the ag “uav” market grows 6. you forgot to mention vc money coming into this .

Avatar for Noel MAGNIN Noel MAGNIN says:

Precision agriculture can be efficient if multiple data are correctly collected and integrated. No drone company is actually able to do so as far as I know.
Imagery is required, only drones can give the best resolution (ground and time) and provide several vegetation indices. Integration of imagery data and soil data (chemicals not physical) is a first step. Field observations (ground truthing) are necessary too … then you can see that no software can do the prescription job.
Precision agriculture actual inefficiency originates in the fact that marketers want a simple solution for a quick sale.
The precision agriculture consultant can be efficient if he asks the good questions, collects the good data and takes the best possible decision, not if he collects basic NDVI and uses it simply for fertiliser prescriptions. Cheap and simple solutions just do not work.

Avatar for Bob Wheeler Bob Wheeler says:

I think you indulged well! Over the past 2 decades we have continued to find more ways to gather more data to provide a greater magnitude of information to digest and hopefully finding our limiting factor(s). The problem is we really haven’t found a good ‘digester’ of all this information (overload). Weather data, both local and regional, has been around a long time with many models being built, but this has yet to become a part of our daily lives to solve questions. Yield data has been collected to the nth degree, yet quick and dirty processing to provide some sort of answer still seems to elude us to some extent. The UAV hype as we waited to hear from the FAA seems to have faded as satellites now provide daily returns. Change detection without having to task satellites to gather a single image per month is a thing of the past. The resolution of these satellites are ‘good enough’ to accomplish PAg tasks even though some think we need to be at the UAV resolution. Farms flooded with wireless technology has it’s pockets of success, but still doesn’t seem to be the norm so we can connect everything without a dozen repeaters to get data back to where it needs to be. Enough of the doom and gloom. PAg over the past 20 years has taken on new technology and made great strides in improving yield and quality. We’ve done it one technology at a time. Find the new technology – consume, digest, and regurgitate all the information to provide solutions to the never ending question of “What are my limiting factors?”. We just need to start combining all the technologies to continue to find the best solution(s)!

Avatar for Noel MAGNIN Noel MAGNIN says:

Well Bob, you write “We just need to start combining all the technologies to continue to find the best solution(s)!”
What if you do not have relevant data ? You can combine whatever you have and find no solution at all ! This is where we actually stand. And this is the reason why we do not get good enough results in PAg.
The most important data has to be collected on the plant because it is the plant that gives the yield/quality.
Then you have to know how plants work to find out which data to collect (vegetation indices) … and then integrate/combine with other data (soil, weather …). It will work if done correctly, not “quick and dirty processing” as you mention.

Avatar for Bob Wheeler Bob Wheeler says:

Noel – collecting irrelevant data won’t ever help us find a solution. Knowing the tractor’s air filter is getting clogged doesn’t help me grow a better crop. I agree with that, but collecting and combining data before the plant is in the ground is a good place to start. I can definitely come up with relevant information to assist the seed placed into the ground that gives it a better opportunity. Once the plant is established it obviously becomes the best indicator of things going right/wrong. So I agree with you, but would discern that there is plenty we can do long before the seed gets put into the ground.

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