Drones Startups Raise $450m In 2015.

 

Drones startups raised just over $450 million in equity financing across 74 deals in 2015, according to data provider CB Insights. This was a 300 percent increase on 2014 levels.

 

Not all of these drones companies will have implications in agriculture — look out for AgFunder’s upcoming 2015 investment report for those figures — but 2015 did see the world’s largest drones company move into agriculture. China’s DJI, which contributed the year’s largest deal with its $75 million Series B, launched its first drone specifically designed for agriculture in November.

 

 

 

The DJI Agras MG-1 is a smart crop-spraying drone, which is dust-proof, water-resistant, and made of anti-corrosive materials that can be folded up. DJI is not the first company to debut a crop dusting aerial device. In May 2015, the FAA authorized the use of Yamaha’s 207-pound remotely-piloted RMAX spraying helicopter, which had already been used by Japanese rice farmers.

 

While DJI’s ag drone launched to great fanfare in global media, there have been some question marks around its efficacy for larger scale farms. This is due to the drone’s limited fly time and carrying capacity: it can only fly for 12 minutes and carry 10 kg of liquid, according to DJI. This means around 60 acres can be covered per hour, a spokesperson told AgFunderNews. With an average farm size of 418 acres in the US, according to the 2012 USDA Census of Agriculture, this doesn’t make the Agras MG-1 of much use to most US farms. 

 

The DJI spokesperson said that the UAV was built to target small and medium-sized farms only, starting with those in China, and that the Agras MG-1 was not targeting large-scale farms.

 

“The low capacity payload and minimal coverage per flight preclude this from being useful at our scale,” said Tyler Scheid, project manager at Scheid Vineyards, a 4,200-acre operation in Salinas Valley.

 

Scheid goes further to argue that a crop spraying drone would be more interesting to his business if it could identify, early and accurately enough, areas in need of spot treatments, instead of a broad-based application. “But we’re still a long way off from that level of systems intelligence,” he argued.

 

Through the mist of hype around drones in agriculture — doubtlessly encouraged by their exciting, sci-fi characteristics — these limitations do open up the wider question: how effective are drones really for agriculture today? 

 

While some farmers argue that drones are only of interest to them for doing physical tasks like spraying, DJI’s Argas MG-1 is an outlier as the majority of drones in ag are used for taking images of farmland and crops. And this application has been called into question in recent months where battery life is a limiting factor, along with regulations, costs to deploy, return on investment, and image and data processing.

 

“We’ve been using UAVs for ag since 2008, and we have realized that they have their limitations,” said Young Kim, CEO of Digital Harvest, a precision agriculture technology provider, and consultant, who initially launched a pure drones business called BOSH Precision Agriculture. “I think others will come to a similar conclusion. We now use UAVs for specific purposes, but we couldn’t build a business only using UAVs. They require too many people to deploy and can only do a few hundred acres at a time which doesn’t scale when you have several thousands of acres.”

 

The primary benefit of drones for imaging is their low-altitude flight capacity that can capture high-resolution data. Planes, and especially satellites, don’t quite have the same level of detail or constant imaging capacity due to weather, which is critical for determining field-level specifics. 

 

But there is still no set standard for the kind of imagery that’s useful for agriculture, argues James Hunt, managing of business development and strategy at AgTech Insight, the consultancy company.

 

“NDVI, infrared, and temperature are some of the variables that are possible to track, but there are still a multitude of proposals and inferences about which kind of imaging is useful and how to incorporate it into a meaningful software platform that generates actionable insights,” he said.

 

And that’s just the problem for UK arable farmer Andrew Williamson, who argues that it’s too much of a process to get value out of the multispectral images, which can provide information on crop health. First, they have to be analysed by a software or analytics company to discover what issues there might be on the land and then sent to a farmer’s smartphone or tablet in a consumable format.

 

“I then have to ground truth the data and check that they are actually looking at what they think they are looking at,” he said. This is all takes time, and some argue it’s much more work that it’s worth.

 

“The real value would be if you could send up a drone every day or two to scouts and assess a plot of land, identify trends, and send back data on nitrogen, weeds and diseases levels, without any interaction from me,” he added.

 

The guys at AgTech Insight can imagine the automatic tracking and GPS guided flight — used to follow snowboarders down a mountain — developing into automatic scanning and image recognition technology. This could enable the “spot check” type solution that Scheid suggested, without the need to manually run the image past agronomists or a software platform.

 

“Quick reactions to pest outbreaks, irrigation leaks, or other such cost-incurring mishaps would be of tremendous value and currently are time sensitive and arduous problems for growers,” said Hunt.

 

But identifying which data are meaningful and weaving them into an algorithm remains a big challenge for ag software companies, argues Hunt.

 

Regulations in the industry are also limiting as drones must always be flown in the line of sight, putting the kibosh on Williamson’s plan for drone scouts without supervision.

 

So at the moment, drones can really only supplement other imaging technology, consisting of satellites and airplanes, argues Digital Harvest’s Kim, who now uses a variety of data capture tools to help farmers solve specific problems.