agtech report mid-year 2016

SaloméHEMMO–Mid-year2016

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Agtech report

Executive summary

The past two years were very exciting years for Agtech. Farming is going through a rapid evolution with the integration of innovative technologies that significantly increase productivity on farm operations. Technology offers great opportunities to the agriculture landscape, especially on the data and cloud computing aspects. This is the best time for disruptive acceleration in agriculture innovation, one that can empower new players in the supply chain to participate, benefit and significantly enhance crop performance. Therefore, a growing number of startups have taken this opportunity to transform agricultural processes and create value for farmers.

Today, the Agtech space is fragmented. There are no clear standards in place, and technologies are generally addressing a unique need. Yet, consolidation is expected in the coming years. Large industry players such as Monsanto are showing a growing appetite to acquire new technologies. This consolidation will increase the need for a systematic technology, a foundational layer that allows increasingly large enterprises to develop new solutions in an efficient way.

This report looks at the current dynamics of the Agtech ecosystem and identifies emerging technologies which support innovation in the industry

Market overview

A. Definitions

Agtech is commonly defined as the convergence of technology and agriculture.

Over the past 30 years, Agtech mainly consisted of agricultural machinery. The 'First Wave' of modern Agtech was the rapid and widespread adoption of biotech seed in the 1990s which was mainly driven by yield boost. The 'Second Wave' expressed an even faster adoption of GPS steering which was driven by cost savings. Other technologies, like irrigation hardware, were typically bundled with Clean-tech and so were not considered part of Agtech.

Today, technology has given us the means to change the dynamics of the agricultural sector and tackle issues that were earlier thought to be inevitable. Increased accuracy in weather prediction along with timely availability of production and crop data has transformed the way agriculture is practiced in developed countries.

In this report, we will focus on three Technology Clusters (referred to as “Tech clusters”):


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1. Decision Support Tech, which encompasses predictive data analytics (including weather forecasting, pest and disease monitoring), satellite data and imagery analytics, farm management softwares, ERPs, collaborative data platforms and cloud ag biology.

2. Smart equipment and Hardware, which includes soil sensors, IoT and precision irrigation.

3. Drones and Robotics, with harvest automation robots and agricultural UAVs.

These Tech clusters represented 25% of the broader number of Agtech deals in 2015. Their business potential was estimated at $1.4b, which accounts for about 30% of the total investment in Agtech.

B. Why now?

Various stakeholders actively participate in the Agtech ecosystem, as shown in the graph below.

Figure 1: Impact of new technologies at each step of the agribusiness value chain

Today, advancements in big data, cloud computing, machine learning and computer vision enable new players throughout the supply chain to participate, benefit and significantly enhance crop performance. Our ability to generate, collect, and analyze large amounts of data - along with the scalable access to computing provided by cloud computing services - allows farmers to leverage their complex data sets in an affordable and easy manner. Therein lies an opportunity to disrupt a legacy value chain that is now becoming obsolete. Traditional agricultural processes are not relevant anymore and must be reinvented to meet a growing global production demand.

C. Challenges and Opportunities

We are talking about a multi-trillion dollar global market that is ripe for improvement, with new agricultural needs developing at all levels. Innovative technologies are emerging, which lets small players have a space in the field.


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The modern generation of farmers is looking for ways to be profitable, productive, and environmentally sustainable, despite falling farm-gate prices. Farmers need to gather and extract relevant data about their production in a cost-effective manner to understand what affects the crop in relation to the yield. Data on weather patterns, fertilizer regime, crop disease is necessary for daily survival. Yet, one of the biggest obstacles that companies in the Agtech space need to overcome is the opposition from farmers who are set in their ways, and often skeptical of technology. The adoption rate of new technology by farmers is indeed notoriously slow: self-steering tractors and combines, for example, are less than 20 percent adopted after a decade of effort. Thus, adoption is one of the key challenges facing these Agtech companies, new and old alike. To be a viable digital ag disruptor, companies need to ease the mounting burdens on today’s farmers by helping them make better use of their time while driving better performance on their farms. Moreover, the lack of wireless connectivity in many rural areas is still a big drag on digitizing agriculture. The greatest potential may be in the developing world where tapping into global communications networks and bringing big data to the world’s most information-poor regions may have a significant impact on the crop yields.

D. Emerging Technologies

New technologies take part of a global trend toward increasingly data-driven agriculture, which is mainly driven by precision agriculture technologies. The latter refers to technologies that make it easier for farmers to observe, measure and respond to field variability in crops. Below are some examples of how such emerging technologies are used today.

Drones with advanced sensors and imaging capabilities are giving farmers new ways to increase yields and reduce crop damage by observing and mapping the agricultural land. Drones provide farmers with a low-cost aerial camera platform that is controlled by a software on the ground, which can plan the flight path (“autopilot”), take aerial shots and translate them into a high-resolution maps. The low-altitude view gives a perspective that farmers have rarely had before. Compared with satellite imagery, these UAVs are much cheaper and offer higher resolution. Most importantly, maps can reveal patterns of irrigation problems, soil variation, pest and fungal infestations that are not apparent at eye level. They can also create a view of the crop that highlights differences between healthy and distressed plants over time, revealing trouble spots and opportunities for better crop management.

Agricultural robots and smart machinery are designed to grow more food with less labor, which allows farmers to automate part of the planting and harvesting processes. Tractors can now autonomously plant seeds with a high accuracy level, while GPS-guided harvester robots reap the crops. On top of reducing the human resources required for production, these robots can navigate plant rows and send relevant data to farmers to optimize the seed breeding or pesticide dosage.

Soil sensors change the way water and irrigation processes are managed in farms. These sensors can be self-installed and calibrated, as well as buried below ground to keep track of what is going on in the soil. They connect to intelligent adaptive algorithms that customize irrigation prescriptions on existing drip hardware. Indeed, the sensor’s data is sent instantly via the cloud and it allows to calculate the amount of water necessary to produce the maximum yield in each irrigation zone. The computer passes


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back the results to the farm’s irrigation system to adapt the level of irrigation, and prevent over-watering. Such adaptive irrigation has the potential to save billions of gallons of water each year while driving better outcomes for farmers. Many of these companies are also introducing a business model that is new to agriculture - adopting a SaaS solution to allow farmers to pay on a subscription basis instead of upfront hardware purchases.

Decision support technologies assist farmers in understanding the data they collect in their farm, and using it to drive performance. Weather prediction technologies for example allow farmers to optimize their crop yields in a significant way. Indeed, weather heavily influences the decisions made around fertilizing, crops maintenance, fields irrigation, harvesting and transportation. If farmers know they will have heavy rain the next day, they may decide not to put down fertilizer since it would get washed away. During the harvesting phase, the soil needs to be dry enough in order to support the weight of the harvesting equipment - if it is humid and the soil is wet, the equipment can destroy the crop. What is more, when this weather data is coupled with satellite imagery maps that show crop maturity over time, farmers can easily make proactive decisions and increase their yields based on accurate simulations. To complete the picture, the generated data about crop yields is now collected not only on individual farms, but as an aggregate from farm operations with similar climates and soil types. Thanks to collaborative platforms that process data from various farms in real time, growers can perform benchmarks and make better decisions with regard to planting, fertilizing and harvesting crops.

Figure 2: Mapping of emerging technologies in Agtech

Overall, such new technologies target a wide array of issues for farmers and therefore impact the complete farming lifecycle - from pre-planting and planting to farm management, post-harvesting and processing. The appendix provides a list of specific companies in each category.

D. Agtech startups overview

The capital invested in agriculture Tech clusters has quadrupled each year since 2013, reaching $1.5 billion in 2015 invested across 132 companies, as shown in the graph below.


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Figure 3: Number of deals (left axis) and capital invested (right axis) in Tech clusters, 2013-2015

Ever since the acquisition of the first “Ag Unicorn” (Climate Corp. by Monsanto), a flood of new digital agriculture startups has been trying to turn investor interest into market traction.

The United States received the majority of Agtech investments during Q1 and Q2 2015 roughly $1B. Israel came in second with about $500 million - mainly due to a large boost from Netafim’s funding.

Figure 4: Top 10 countries receiving Agtech funding ($ millions), first half of 2015

The following chapters provide an overview of the most interesting startups that operate in this field.

Imagery technologies for agricultural purposes are expanding with major players in geospatial, UAV and sensor-based imagery / analytics services. They fall into four categories:

• Satellite imaging services: the most significant player in this category is Planet Labs, a Data Collective and AME Cloud Ventures backed company that raised $158 million in equity funding.

• Satellite imagery analytics tools: Orbital Insights (backed by Sequoia Capital, $28 million total equity funding), or A.I. company Descartes Labs ($8 million, backed by Data Collective)


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• End-to-end services including drone/satellite imagery capture, imagery analytics, and business intelligence for farmers: major players include Precision Hawk ($29 million, backed by Intel Capital and Verizon Ventures), Sentera ($8 million series A), DroneView Technologies ($2 million seed), Mavrx Imaging (undisclosed series A), Cropio or Skycatch.

• Ag sensor-based imagery analytics such as Resson (Monsanto-backed, $13 million) or Prospera ($7 million series A led by Bessemer Venture Partners)

Other decision support tech include farm management software such as Farmers Edge Laboratories ($44 million capital funding - provides various agronomic services like farmland optimization, field agronomy, farm laboratory, yield analysis); Granular ($24 million, Andreessen Horowitz-backed - helps farmers using less water and less fertilizer); Taranis ($2 million seed, a precision agriculture intelligence platform including satellite imagery, weather forecasts, and farm management); or Farmlogs ($15 million - forecast and measure farm profits, track farming expenses, and manage risk). This category also encompasses farmers network platforms and benchmarking tools like Farmers Business Network (GV backed, $43 million,) or Farmlink ($64 million, an independent yield benchmarking tool). Weather prediction tools include Understory Weather ($9.5 million, backed by Monsanto), Booster Agtech (seed), and awhere ($14.4 million). Food tracking and compliance software include Conservis ($12 million) or Lotpath (seed). Regarding BioAg cloud platforms, TraceGenomics ($4 million, Refactor Capital) uses artificial intelligence to predict agricultural diseases. In addition, an interesting farm assets management startup is Filament ($7 million) - an IoT device that connects existing machinery, equipment, and assets to a wireless sensor network and monitors them.

Drone technologies are split between:

5) Autonomous drones: 3DRobotics ($126 million funding), Airobotics ($28 million), DJI, Ehang, CyPhyWorks ($22 million, BVP)

6) Operating systems for commercial drones: Airware ($70 million), Skyward, Drone Deploy ($9 million, backed by Data Collective)

7) Drone guidance tools: Swift navigation (precision & accuracy for aerial surveying, device guidance & autonomous vehicle) or Trimble navigation

Accel Partners partnered with China’s DJI to launch Skyfund, a $10 million fund that aims at investing into early-stage around drone, robotics, machine intelligence, computer vision and navigation. Specifically, this fund focused on backing developers that build software and hardware using DJI’s development kit. It is therefore relevant for ag imagery and field mapping startups. Similarly, Airware announced a new Commercial Drone Fund to invest in early stage startups from the enterprise drone ecosystem.

Automation & robotics are mainly computer vision systems that integrate with ag machinery. The goal is to automate the harvesting process and reduce human resources needed in the farm. Such companies include BlueRiver Technologies ($30 million, backed by Monsanto and DataCollective); Harvest Automation ($25 million); FFFrobotics (robotic arm on board of a Clearpath Robotics robot - Together, the robot autonomously navigates apple orchards and picks fruit from trees). Include also novel fruit gripping technologies like Soft robotics (a Harvard spin-off, $5 million).

Soil sensors include CropX ($10 million backed by Innovation Endeavors), an ag-analytics company that develops a cloud based software integrated with wireless sensors to boosts crops yields; Arable Labs ($5.5 million in seed round) which provides a solar-powered IoT device with advanced sensors to handle in-field crop monitoring; Aquaspy ($6.5 million), a sensor and web-based software that help growers become more efficient with water, fertilizer and energy; FarmDog (seed), advanced sensors for pest and disease detection; Saturas ($1m seed), miniature stem water sensors embedded in the trunks of trees, vines, and plants to optimize irrigation and increase production.


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Smart Irrigation technologies include Netafim, a leading player in drip and micro-irrigation solutions, and Hortau ($21.5 million, backed by BDC Capital), a wireless and web-based irrigation management system.

4) General insights about Agtech startups activity

When looking at the bigger picture, startups form the Tech clusters raised $333 million during the first half of 2016, slightly more than half of what was raised during all of 2015 ($661m). There was a slight shift in the make up of this segment in Q1 and Q2 2016 compared to 2015: drones represented a smaller portion of the precision ag segment (34% vs 49%) while investors continued to favor decision support tech. Indeed, decision support software startups represented 28% of precision ag funding compared to 11% during 2015. Hardware and sensors startups also grabbed a larger size of the pie raising from 3% to 8%. Satellite imagery went down from 27% to 17%, while weather prediction analytics tools grew from 1% to 2%. So far, major investors and venture capital firms enabled a strong M&A activity in the AgTech field. According to AgFunder 2016 report, the number of investors coming into Agtech climbed 52% between 2015 and 2016, suggesting that investors are getting more comfortable with the sector. This strong M&A activity spurred entrepreneurial activity and gave entrepreneurs the startup funding and support they need to bring new technologies to light.

F. Potential exit routes and current state of IPOs

So far, the best exits are those that have had corporate investors. The most exciting exits have been strategic trade sales, namely Monsanto’s acquisition of The Climate Corporation in 2013 for $1 billion, followed by acquisitions by “the Big 4” bio-space players (BASF, Bayer CropScience, Dupont, Dow Chemical Company, and Syngenta). The major ag players view the ability to offer new products and services to fill their pipeline as the key to their future growth. That said, with growing numbers of complementary technologies, and even more consolidation opportunities, private equity firms will have an important role to play to contribute to the dynamics of the industry.

E. Benchmark of large Tech players

General Tech corporations are more and more involved in the Agtech industry. These major corporations include Microsoft, IBM, Google, Amazon, Cisco, Intel, Oracle, GE, SAP, HP, Verizon, AT&T, Orange, Telefonica. Here are the key findings:

1) Boom in Agtech collaboration between general Tech players. Microsoft recently announced a partnership with Monsanto in a bid to invest in Brazilian agricultural technology startups. Earlier this year, Intel and AT&T agreed to work together to improve the performance of the LTE networks for drones in high-altitude, with a focus on Agtech applications. A few months later, IBM signed a deal with Cisco to bring Watson IoT technology into Cisco’s architecture, providing analytics services for networks of UAV’s remote control. On a larger scale, Google is developing the Farm 2050 project - a cross-industry collaboration with companies ranging from fertilizer producer Dupont to supply chain management software company Flextronics, in order to increase farm production by 70 percent by 2050. On the telecom side, Telefonica has partnered with Israeli IoT


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company Bacsoft’s to provide remote field monitoring and control for all critical data such as temperature, humidity and irrigation flow.

2) Expansion of Agtech research projects. Given the huge potential for research and development in the agricultural sector, corporate partnerships are likely to gather momentum in the coming years. New startups will gain from this momentum, as corporate partnerships will back new startups in this particular sector. Research projects include Deep Thunder by IBM, an initiative which aims to improve short-term local weather forecasts through the use of high-performance computing. Another research project includes Intel’s work with the University of California and the World Food Center, a collaboration which tackles California’s water problems by applying big data and satellite imagery techniques to precision farming. Orange Silicon Valley, the Bay Area innovation division of French telecommunications company Orange, also launched the Agstudio initiative to research needs of Californian farmers, and support innovations.

3) Launch of specific solutions for Agtech. Verizon plans to launch an AgTech IoT software platform in Q3 2016 to improve the connectivity of sensors - and other data-capturing devices - on the farm, helping farmers to turn this data into actionable insights. AT&T has already introduced M2X, which provides data services for smart agriculture IoT, farm sensors, driverless tractors, and farm info management. On supply chain software side, SAP launched a Digital Farming Machinery Insights Solutions and Vistex Farm Management to support the full life cycle of farm operations. Oracle offers JD Edwards EnterpriseOne application for “Food & Beverage Producers”, providing growers with real-time information that covers the entire crop-to-product, block-to-bottle cycle. Finally, Google partnered with Basecamp Networks to build Intelliscout, an AR farming app for Google Glass.

4) Emerging local Agtech centers. Microsoft and Monsanto partnered together to invest in agricultural technology startups in Brazil to help foster new startups in the agricultural sector in Latin America. Cisco invested $15 million in a new “Internet of Everything” center in Sydney, aiming at making Australia the epicenter for IoT R&D in agriculture. GE initiated new projects in the Japanese agriculture sector by launching an indoor farm at Miyagi Fukko Park - one of the world's largest plant factories which uses LED lighting throughout.

5) Active role of tech players in Agtech investment & acquisition scene. Google led two major investments: $18.7m in Granular, and $15m in the Farmers Business Network. IBM acquired the Weather Company and runs them on IBM cloud data centers. Verizon invested in PrecisionHawk, Filament, and Skyward.

6) Support by major Cloud platforms of open agricultural data projects. CGIAR, a consortium of international agricultural research centers, made its data accessible and available for addressing critical food security challenges using the Amazon Web Services Cloud. Microsoft launched an innovation challenge with the U.S. Department of Agriculture, by providing contestants with USDA open data sets (hosted on Microsoft Azure) to develop online tools that help make the American food supply more resilient in the face of climate change.


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Appendix: Agtech market map US and Israel, mid-year 2016

agtech report mid-year 2016

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