What Automated Estrus Detection Systems Can and Cannot Do

What Automated Estrus Detection
Systems Can and Cannot Do
Dr. Jeffrey Bewley

Changing the Way We Breed
• Efforts have increased
dramatically
• Positive experiences
• Only catches cows in heat
GEA
Rescounter II
AFI
Pedometer +
SCR HR
Tag/AI24
DairyMaster
MooMonitor/
SelectDetect
Track a CowBouMatic
HeatSeeker II
DeLaval
Activity
Monitor
Anemon
Estrus
Monitoring

Heat Detection Aids
 Records
 Heat Expectancy chart
 Breeding Wheel
 Computer Action Lists
 Prostaglandins
 Ovsynch
 Pre-Synch
 Mount Detection Aids
 Kamar Detectors
 Estrotect
 Tail head Marking
 Videotape
 Heat Detector Animals
 Androgynous Female
 Altered Male
 Precision Technologies
 Activity
 Rumination
 Temperatures
 Standing Behavior
 Progesterone Biosensors
 Mount Detectors
 Heart rate
 Feed intake
 Milk yield
 Vaginal conductivity

Visual Detection of Estrus
Disadvantages
 Subjective
 Time allocation
 Herd size
 Duration of estrus
 Inconsistent
 Facilities
 Labor costs
 Efficiency declines during
busy seasons
Advantages
 Cow time
 Less initial costs

Automated Detection of Estrus
Disadvantages
 Investment cost
 Learning curve
 System requirements
Advantages
 Continuous monitoring
 Prediction of ovulation or
insemination times
 Individual animal history
 Alerts on mobile devices
 Comparable to timed AI
 No hormone injections

Estrus Detection Methods
NAHMS 2007
7.3
93
40.3
34.7
14.4
5.7
1.4
0 20 40 60 80 100
Other
Visual observation
Bulls
Tail chalk/paint
Pressure devices
HeatWatch
Pedometers
Percent
Method

Activity Changes
0
10
20
30
40
50
60
70
80
90
100
0
6
12
18
24
30
36
42
48
54
60
66
72
78
84
90
96
102
108
114
120
Activity
Time in Hours
Estrus

IceTag™ Activity Monitor
Changes on Day of Estrus (11/1/06) for #624
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
# Steps
('000)
Hours
Active
Hours Lying # Lying
Bouts
Longest
Standing
Bout
(hours)
Milk (10 lbs)
10/28/2006
10/29/2006
10/30/2006
10/31/2006
11/1/2006
11/2/2006
Acknowledgement: Dr. Oliver Lewis, Chloe Capewell, and Robert Boyce, IceRobotics, Ltd.

Secondary Signs
0
10
20
30
40
50
60
70
80
90
100 0
6
12
18
24
30
36
42
48
54
60
66
72
78
84
90
96
102
108
114
120
Rumination
Time in Hours
ACTIVITY
RUMINATION Estrus

Milk measurements
• Progesterone
– Heat detection
– Pregnancy detection
• LDH enzyme
– Early mastitis detection
• BHBA
– Indicator of subclinical ketosis
• Urea
– Protein status

Variable Changes
• Estrus-6 hours before and after first observed standing event
• Non-estrus-14 hours before estrus
Variable monitored n Estrus Non-estrus P-value
DVM bolus reticulorumen temperature (°C) 18 39.29 ± 0.21 38.86 ± 0.18 < 0.01
CowManager SensOor ear surface
temperature (°C)
18 24.17 ± 1.20 22.97 ± 0.83 0.20
HR Tag neck activity (units/2 h) 18 61.62 ± 2.04 28.20 ± 0.78 < 0.01
IceQube number of steps (per h) 17 300.82 ± 10.92 79.07 ± 4.13 < 0.01
CowManager SensOor high ear activity
(min/h)
18 17.40 ± 0.66 4.25 ± 0.39 < 0.01
Track a Cow leg activity (units/h) 18 321.14 ± 11.87 95.17 ± 7.16 < 0.01
HR Tag rumination (min/2 h) 18 20.47 ± 2.68 32.96 ± 0.54 < 0.01
CowManager SensOor rumination time
(min/h)
18 12.90 ± 1.07 22.96 ± 0.57 < 0.01
CowManager SensOor feeding time (min/h) 18 16.93 ± 0.99 8.93 ± 0.65 < 0.01
IceQube lying bouts (per h) 17 0.35 ± 0.09 0.72 ± 0.07 < 0.01
IceQube lying time (min/h) 17 10.19 ± 1.91 24.82 ± 0.95 < 0.01
Track a Cow lying time (min/h) 14 6.56 ± 2.55 18.18 ± 1.81 < 0.01

How Many Cows With Condition Do We Find?
Example: 100 estrus events
80 Estrus Events Identified by Technology
20 Estrus Events
Missed by Technology

How Many Alerts Coincide with an Actual Event?
Example: 100 estrus alerts
90 Alerts for Cows Actually in Heat
10 Alerts for Cows Not
in Heat

Machine Learning
Technique Technology Sensitivity Specificity Accuracy
Random
forest
CowManager
SensOor
100 99 99
HR Tag 60 99 98
IceQube 80 99 99
Track a Cow 100 97 97
Linear
discriminant
analysis
CowManager
SensOor
100 100 100
HR Tag 100 98 98
IceQube 100 98 98
Neural
network
CowManager
SensOor
100 99 99
HR Tag 100 96 97
IceQube 100 100 100

Treatment
Variable TAI AAM
Time to first service (d past the VWP) 6.0 ± 0.2a 17.0 ± 1.2b
Probability of pregnancy to first AI (%) 40.4 ± 3.1 41.5 ± 3.3
Probability of pregnancy to repeat AI (%) 41.1 ± 4.1 42.0 ± 4.4
Service interval (d) 42.0 ± 0.1a 24.5 ± 1.2b
Pregnancy loss (%) 12.1 ± 2.4 8.2 ± 2.1
Time to pregnancy (d past the VWP) 50.0 ± 2.3 50.0 ± 2.0
Proportion of cows pregnant at 90 d past the VWP (%) 64.9 ± 3.1 66.7 ± 3.1
Automated Activity
Monitoring vs. Timed AI

• 109 lactating Holstein cows at the
University of Kentucky Coldstream
Dairy
• Modified G7G-Ovsynch used for
synchronization at 45-85 DIM
• Estrus gold standard was verification
of luteal regression and ovulation
using temporal progesterone patterns
and ultrasonography
• Visual observation 4X a day for 30min
each for 4 days
• All cows equipped with 9
commercially available precision dairy
technologies
Multiple Technology Efficacy
Mayo et al., 2015

Methods
 109 lactating Holstein cows at the University of
Kentucky Coldstream Dairy
 January 2014 to March 2015
 Cows were enrolled in the protocol 45 to 85 DIM in
groups of 6 to 10 cows
 Observed for estrous behaviors for 30 min, 4X per
day, for 4 days
 Estrous behavioral scoring system (van Eerdenburg
et al.,1996; Roelofs, 2005 )

Activity Changes
-50%
0%
50%
100%
150%
200%
250%
-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7
PercentChange
Days Periestrous
Device 1 Daily Steps Device 2 Daily Steps
Device 3 Motion Index Device 3 Daily Steps
Device 4 Daily Activity Device 5 Daily Activity
Device 5 Daily High Activity Device 6 Daily Steps

Temperature Changes
-50%
0%
50%
100%
150%
200%
250%
-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7
PercentChange(%)
Days Periestrous
Reticulorumen Temperature Max Vaginal Temperature
Ear Skin Temperature

Feeding Behaviors
-50%
0%
50%
100%
150%
200%
250%
-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7
PercentChange
Days Periestrous
Device 4 Rumination Device 5 Rumination
Device 6 Eating Time Device 6 Daily Time at Feedbunk
Device 6 Daily Feedbunk visits

Lying and Active Times
-50%
0%
50%
100%
150%
200%
250%
-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9
PercentChange
Day Periestrous
Device 1 Daily Lying Time Device 3 Daily Lying time
Device 5 Time not active Device 6 Daily Lying Time

Lying Bouts
-50%
0%
50%
100%
150%
200%
250%
-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7
PercentChange
Day Periestrous
Device 1 Daily Lying Bouts Device 3 Daily Lying Bouts
Device 3 Daily Avg. Bout Duration Device 6 Daily Lying Bouts

Percent Changes
-50% 0% 50% 100% 150% 200%
Lying Time
Lying Bout Duration
Rumination Time
Milk Yield
Reticulorumen Temperature
Vaginal Temperature
Ear Skin Temperature
Lying Bouts
Eating Time
Feedbunk Visits
Daily Steps
Percent Change at Estrus
ParameterMeasured

Sensitivity and Specificty
Estrus detection
Method
True
Positives
False
Positives
True
Negatives
False
Negatives
Total
Cows
(n) Sensitivity Specificity
A 76 2 13 18 109 80.9% 86.7%
B 72 0 14 21 107 77.4% 100.0%
C 45 2 10 34 91 57.0% 83.3%
D 33 1 11 46 91 41.8% 91.7%
E 51 0 8 6 65 89.5% 100.0%
F 35 1 10 15 61 70.0% 90.9%
Standing 51 0 15 43 109 54.3% 100.0%
Behavioral score 62 0 15 32 109 66.0% 100.0%

Ketosis Effect
-50%
0%
50%
100%
150%
200%
Steps per day Motion Index Lying Time Rumination
Time
Milk Yield
PercentChange
Parameter
Effects of Subclinical Ketosis on Expression of Estrus
Subclinical Ketosis No Subclinical Ketosis P > 0.05

Heat Stress
0
10
20
30
40
50
60
70
80
90
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
MaxTHIatEstrus
PercentofCowsStanding
Group Date
Effect of Max THI on standing behavior at estrus
%stood Max THI

Tabs organize information
Description
and
instructions
for user
www2.ca.uky.edu/afsdairy/HeatDetectionTechnologies Karmella Dolecheck et al.

Hover buttons
explain inputs
and results
Inputs
adjustable in
multiple ways

Compare up to 3 different
technologies

Technology
names
appear here
Net present
value shown
visibly as
either good
(green) or
bad (red)
Black box
and “Best
Option”
indicate the
highest net
present
value

Example Analysis
$58,582
$63,582
$64,188
$69,188
$94,300
$99,300
$99,906
$104,906
$0 $40,000 $80,000 $120,000
High-100-70
Low-100-70
High-50-70
Low-50-70
High-100-90
Low-100-90
High-50-90
Low-50-90
Net Present Value
TechnologyExample Low: $5,000 initial investment
High: $10,000 initial investment
50: $50 unit price
100: $100 unit price
70: 70% estrus detection rate
90: 90% estrus detection rateInvestment-Unit Price-EDR
Karmella Dolecheck et al.

• Likely dangerous
• Balanced combination of hormonal
intervention plus estrus detection
• Identify non-cycling cows and
intervene?
–When to start intervention?
–Full synchronization?
• Economic and labor considerations of
managing both systems?
No Hormones?

• System costs tend to follow razor model (cheap
infrastructure, expense in tags)
• Initial systems all read in within parlor, but all have
moved to continuous download
• Small herds likely benefit more from activity systems
• Most systems require tags on at least one week before
event of interest
• Most farmers choose to keep tags on all cows all the
time
Other Considerations

• Be careful with early stage technologies
• Need a few months to learn how to use data

4. What is the policy
for upgrading to new
versions of devices?
5. What are full costs
(hardware, devices,
maintenance, data
storage)?
6. What protocols are
available for handling
alerts?
6 Questions To Ask

Cautious Optimism
• Critics say it is too
technical or challenging
• We are just beginning
• Precision Dairy won’t
change cows or people
• Will change how they
work together
• Improve farmer and cow
well-being

Path to Success
• Continue this rapid innovation
• Maintain realistic expectations
• Respond to farmer questions and
feedback
• Never lose sight of the cow
• Educate, communicate, and collaborate

Future Vision
• New era in dairy management
• Exciting technologies
• New ways of monitoring and improving
animal health, well-being, and reproduction
• Analytics as competitive advantage
• Economics and human factors are key

Questions?
Jeffrey Bewley, PhD, PAS
jbewley@bovisync.com
jbewley@cowfocused.com

What Automated Estrus Detection Systems Can and Cannot Do

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