The behind the scenes of today’s satellite imagery technology and what it can do for your farm. Leander Campbell, AAFC Ottawa, Chris Olbach, Corteva Agriscience and Alex Whitley, Taranis

1. ARTIFICIAL INTELLIGENCE:
Weeds
Emergence/Plant Population
Disease
Insects
Eastern Ontario Crop Conference

2. 1.
TRADITIONAL SCOUTING X TARANIS AI 2
99 POINTS
55 H 23 MIN
2349 Points
01H 40MIN

3. How Does it work
Emergence
RISK DETECTED:
5 BUSHELS PER ACRE!
RISK DETECTED:
3 BUSHELS PER ACRE!
RISK DETECTED:
12 BUSHELS PER ACRE!

4. 1.
Emergence
The combination of 8cm UHR and leaf-level imagery is the most efficient
and profitable way to monitor your fields. Ground truth virtually, and easily
convert your dataset into the most accurate zones and prescriptions in the
industry.
Begin by
comparing
NDVI to the
Visible layer.

5. 1.
Emergence
Zoom into poor emergence and good emergence areas to further validate
the spectrum.
Note:
the consistent
rows and
biomass
abundance
indicates a
healthy
emergence.

6. 1.
Emergence
Zoom into poor emergence and good emergence area to further validate
the spectrum.
Note:
the amount of
bare soil and
consistency of
low biomass
indicates a weak
emergence.

7. 1.
Emergence
Virtual scouting is the most efficient and cost effective way to ground truth.
Next step, use 8cm UHR to build zones and prescriptions that are accurate
down to the plant level.
Emergence VR Zone

8. 1.
Emergence

9. 1.
Emergence
We quantify emergence from the earliest of stages all the way until
the whirl can no longer be identified singularly.

10. 1.
Emergence
Population Heat Maps are produced for each field and can be exported
from an entire territory level for meaningful and efficient reporting.

11. 2.
Weeds
Even hard-to-see weeds lurking below the canopy are easily spotted by
our AI.

12. 2.
Weeds
Several types of weeds being automatically detected

13. 2.
Weeds
Plant population, weeds, and volunteer corn marked as weeds!

14. 2.
Weeds
Plant population, weeds, and volunteer corn marked as weeds!

15. 2.
Weeds
Yes, we can quantify flood damage and plant population, but our AI is
so advanced, it will identify weeds even when their submerged!

16. 2.
Weeds
Regular flights of AI2 will capture weed pressure from the earliest of stages.
All weeds tagged in every image will be categorized, searchable, and can be
combined for ultra-specific filtering of your entire territory.
Note: the images that
have been tagged with
the specific threat being
filtered will appear blue.
The images that did not
contain the threat being
filtered turn white and
aren’t selectable. Makes
for mistake free,
lightning quick, virtual
scouting.

17. Weeds
Filter by specific weed or weeds in general. Notice our analytics quantify how many
images out of the total imaging event have the specific threat. Understanding
quantities and densities of weed species will help determine product and application
method.
2.

18. Disease
Identifying diseases is important. Here we can see leaf blight, grey leaf
spot, and the ever-present weeds.
3.

19. Disease
Northern leaf blight is trouble, but AI2 continues to identify it at early
stages giving you the chance to prescribe a treatment and protect
yield.
3.

20. Disease
Finding grey leaf spot is key for more than just treatment. Hybrid
choices can be made based on spotting tolerances
3.

21. Disease
Finding grey leaf spot is key for more than just treatment. Hybrid
choices can be made based on spotting tolerances
3.

22. Insects
Identify the migration of an insect threat throughout a geography,
track back to the source field, and identify the specific insect down to
the leaf level.
Source field
4.

23. Insects
Ai finds each insects and categorizes it accordingly. Best practice is to spot
check different areas in the field, then neighboring fields, then the furthest
field with the same determined threat.
4.

24. Insects
Identify, Classify, and Prescribe in seconds. Go to the field armed with the
solution (machine ready for application) rather than going to the field to
figure out what is wrong.
4.

25. Insects
Identify, Classify, and Prescribe in seconds. Go to the field armed with the
solution (machine ready for application) rather than going to the field to
figure out what is wrong.
4.

26. 2. Corn
In-Season, General Monitoring Program
satellite
whole field UHR
leaf - level imagery
Planting Harvesting
Emergence - V2
Stand count / replant
V7 - V10
Tissue sampling for micronutrients /
Y drops / side dress / validating early
season side dressing / agronomic
validation / drainage issues
V3 - V6
Nutrient deficiencies /
weeds / side dress / tissue &
nitrate sampling / replant /
agronomic validation /
drainage issues
Maturity
Yield estimation / early
market planning
V11 - R1
VR nitrate sampling / Y
drop / insecticide Rx /
fungicide Rx / foliar
feeding / agronomic
validation
R6
Monitoring dry-down /
monitoring maturity / final
agronomic validation /
potential insurance claims
(wind, hail, freeze, snap)
Presentation 1
Deeper dive into specific threat examples in Maize and Cotton

27. 2. Soybean
In-Season, General Monitoring Program
satellite
whole field UHR
leaf - level imageryPresentation 1
Deeper dive into specific threat examples in Maize and Cotton
Planting Harvesting
VE - V3
Emergence / stand
establishment / early
insect & weed
identification
V6 - R1
Micro-nutrient
applications / fungicide
treatments / insecticides
treatments
R2 - Maturity
Disease pressure /
foliar applications /
late weed infestation /
fungicide
V3 - V6
Weed detection /
tissue sampling /
drainage issues /
water management
Determine Growth Stage
White mold / SDS / brown stem rot /
micro - nutrient applications /
fungicide & insecticide treatments

28. ARTIFICIAL INTELLIGENCE:
Weeds
Emergence/Plant Population
Disease
Insects
Eastern Ontario Crop Conference