Willa Leong of Royse Law Firm presentation at AgTech18 conference presented by NC Tech Connection, Nevada City, CA. February 8, 2018

1. AgTech
WILLA LEONG– ROYSE LAW

2. s of Agricultural
ogy Innovation
• Information Age
• AgTech Revolution

3. curity:
d for AgTech
: 9 billion
production needed to meet demand (UNFAO)
rom higher yields on existing farmland
s

4. ption

5. merism
ming
ging
• Sustainability
- Water, precision
• GMO and gene editing
• Environmental
• Animals and protein
• Growing middle class
• China

6. e of Farm Labor
back-breaking work
grants coming to the US
orkforce
sed cost

7. ory Effects on
ustry
by 2022)
crop production due
Overtime regulations
• Gov. Jerry Brown signed bill in
2016 to be implemented by 2
Immigration
• 2015 glitch in seasonal worke
arrival of legal farm laborers
• Competition with other secto

8. ory Effects on

9. :
ure Economy
a is a
business
dustry is a
ry
• In 2012, 70% of all farms had inte
ge of innovation within the agriculture sector, from water use

10. AgTech
eed stage
als (2012)
ls (2015)
ls (2016)
ls in first half of 2017

11. ent Sources
• Accelerators/incubators
• Universities
• Government
• SBIR
• USDA

12. ent Sources

13. ovations in
y
• Farm management
• Supply chain
• Mobile
• Social media

14. n Agriculture
when, where, and
me level of accuracy.
ss
to analyze
nformation
Today, precision ag provides:
• Satellite navigation and gu

15. g Tech: Gathering
lays crop yields from
GPS)
of crops
id soil sampling),
d longitude on a
• Determines health and vigo
• Provides better agricultural
manual sampling
Geographic information system
• Maps data and analyzes rel
factors (Soil types, fertilizat
etc.) in user-friendly way

16. a, Analytics, and
recision Ag
a
ologies to analyze
ation on land and crops
cisions
important topic
Report times
• Batch
• Monthly
• Weekly
• Daily

17. anagement,
, and IT

18. Media
munity is:

19. Only (and
)
mobile is greater than
et apps

20. ending
ogies
• eCommerce &subscription
delivery
• Farm to business marketplace
& platforms
• Infrastructure
• Community building
• Regulator guidance
• Soi
• Ani
• Pro
• Cel
• Pla
• UAV

21. ch Examples
omated?
t, sort, grade,
more dangerous or
rrent labor supply
ions.

22. r:
anagement
e
Granular’s mobile app
schedule and task list.
everyone is on a map, a
completed.

23. onnect:
anagement Softwa
work from your mobile device or clock in a crew of
nd hours worked. Generates a digital timecard that can
ager instantly.
Food Safety inspections, check for pests, add severity,

24. sion Works: Sorti
chine Learning
s that help with grading produce in
texture ripeness,
direct labor cost with Date Sorting

25. botics: Delicate
e Gripper
project I’ve worked on in my career,” says
of Taylor Farms Pacific.
gers can handle delicate produce such as
wberries without damaging them.
million

26. ver Technology: S
ay Machines
g computer vision, then machine learning
or kill it.
)

27. wnership and
mpanies collecting data
or their own commercial
eseen by farmers
consider data ownership
n the cloud
• With more data in the clo
information for them to re
• In 2012, the EPA released
farmers following a FOIA
Data can be sensitive; farme
information kept private (e.g

28. Ownership,
& Use
ndard EULA
rowser, Click Wrap
nd who owns it?
use, enjoy, exclude,
• How can growers access t
• Is the data accurate and p
way?
• Trade secret protection (U
- Information
- Independent economic

29. arming and Cyber
rial Control Systems (ICS)
hcare and public health sector
to farmers prioritizing usability for security
orks vulnerable to cyber attacks
data or steal analyzed data
urces and market trends
files & render them unreadable until ransom is paid

30. curity Standards
d Security’s FA Sector-Specific Plan
als to assess all-hazards, including cybersecurity a
s to adopt the National Institute of Standards and
k
sector members who implement ICS
nt & Risk Management Approach
t of cyber risks to broader sector & best practices

31. actices
nagement companies use & protect data
security features implemented in precision agric
gins that occur outside of normal business hours
ntication for employee logins, especially remote
formation Technology e-mail account for emplo
ng to remind & inform employees about current
especially over non-standard ports
a, & be willing to block unknown IP addresses

32. ng Notice
ing suspicious or criminal activity to local FBI
itted should include:

33. AgTech Data
ds
I’s) and open source software libraries, March 2014
AFBF) Privacy and Security Principles of Farm Data
April 1, 2016
rm Data Principles Agriculture Data Coalition
lders focused on building a “farmer-centric data repository where farmers c
ay in the fields by their tractors, harvesters, aerial imaging and other device
Startup

34. e Standards?
rs, but not always workable
e to negotiate terms
it or leave it” position
me ATPs is the collection and presentation of data (subscri
to let farmers take this data with them when they no long
cated due to the multiple agreements in place

35. m: Lack of Formal
ent
culture is a handshake industry
ctions, not formal agreements
ick the tires” for on-farm products
like field trials (including university trials), are done withou
ferent laws are implicated that these parties never anticipa
de secret disclosure, ownership of IP (patents, data, “results

36. ure Drones
ltural
94 million

37. ure Drones
nd weather damage
use of drones
e concern with
and crashes
• Use problems
- Cost of entry
- Battery life
- Connectivity
- Presentation of data

38. es for Commercia

39. aw Firm
ice

40. Us
rroyselaw.cooyseAgtech.com