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Sensors in the milking parlour
replacing or complementing human senses to monitor cow health and productivity
What can you expect
Claudia Kamphuis
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
Take home message
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
Take home message
8
2004: Graduated, Preventive Animal Heath and Welfare, Wageningen University
2006: PhD, Utrecht University
2010: Defended successfully PhD, Utrecht University
2004: Graduated, Preventive Animal Heath and Welfare, Wageningen University
2006: PhD, Utrecht University
2010: Defended successfully PhD, Utrecht University
2011: Scientist role at DairyNZ, New Zealand
2004: Graduated, Preventive Animal Heath and Welfare, Wageningen University
2006: PhD, Utrecht University
2010: Defended successfully PhD, Utrecht University
2011: Scientist role at DairyNZ, New Zealand
2013: Post-Doc, Business EconomicsWageningen University
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
Take home message
Initiated by cow identification systems in 1970s
Recording of individual milk yieldAllocating feed/concentrates to individual cows
Boosted by development of automatic milking systems in 1990s
6 main brands
Boosted by development of automatic milking systems in 1990s
6 main brands
1992 first commercial farm in NL (Bottema, 1992)
>10,000 farms globally (Rodenburg, 2013)
5,586 (19.5%) Dutch farms (Stichting KOM, 2015)
Boosted by development of automatic milking systems in 1990s
6 main brands
1992 first farm in NL (Bottema, 1992)
>10,000 farms globally 2013 (Rodenburg, 2013)
5,586 (19.5%) Dutch farms (Stichting KOM, 2015)
Forced to replace human senses
Boosted by development of automatic milking systems in 1990s
Cheap technology
Low in maintenance costs
Udder or quarter level
Most used to detect abnormal milk or mastitis
Limited performance for mastitis detection (Rutten et al., 2013)
Electrical Conductivity
handheldIn-line
Other (more sophisticated and expensive) sensor technologies were introduced to monitor cow health and productivity
Udder Health- Electrical Conductivity- Milk yield- Somatic Cell Count- (Milk) Temperature- Colour
Other (more sophisticated and expensive) sensor technologies were introduced to monitor cow health and productivity
Udder Health- Electrical Conductivity- Milk yield- Somatic Cell Count- (Milk) Temperature- Colour
Milk Composition- Milk yield- Fat and protein content- Lactose content- Somatic cell count
Other (more sophisticated and expensive) sensor technologies were introduced to monitor cow health and productivity
Fertility- Progesterone- Activity- Rumination
Milk Composition- Milk yield- Fat and protein content- Lactose content- Somatic cell count
Other (more sophisticated and expensive) sensor technologies were introduced to monitor cow health and productivity
Fertility- Progesterone- Activity- Rumination
Cow ‘Composition’- Weight- Body Condition Score
Metabolic disorders- Activity- Rumination- Milk yield- SCC- pH
Other (more sophisticated and expensive) sensor technologies were introduced to monitor cow health and productivity
Cow ‘Composition’- Weight- Body Condition Score
Other (more sophisticated and expensive) sensor technologies were introduced to monitor cow health and productivity
Metabolic disorders- Activity- Rumination- Milk yield- SCC- pH
Cow Mobility- Weight- Activity- Rumination - Milk yield
There are A LOT of sensor technologies
25
With A LOT of benefits
Improve health, welfare
Increase productivity
Increase efficiency
Improve product quality
Objective monitoring
Improve social lifestyle
Sensor technologies in use (%)(Steeneveld and Hogeveen, 2015)
27
Sensor AMS (n = 121)
CMS (n = 81)
Colour 60 1Electrical Conductivity 93 35Milk temperature 50 6Weighing platform 27 5Fat and protein 20 0Somatic cell count 17 1Activity meters/pedometers dairy cows 41 70Activity meters/pedometers young stock 12 28Temperature 6 14Rumination 9 12Lactate dehydrogenase (LDH) 2 1Progesterone 2 1
Sensor technologies in use (%)(Steeneveld and Hogeveen, 2015)
28
Sensor AMS (n = 121)
CMS (n = 81)
Colour 60 1Electrical Conductivity 93 35Milk temperature 50 6Weighing platform 27 5Fat and protein 20 0Somatic cell count 17 1Activity meters/pedometers dairy cows 41 70Activity meters/pedometers young stock 12 28Temperature 6 14Rumination 9 12Lactate dehydrogenase (LDH) 2 1Progesterone 2 1
Sensor technologies in use (%)(Steeneveld and Hogeveen, 2015)
29
Sensor AMS (n = 121)
CMS (n = 81)
Colour 60 1Electrical Conductivity 93 35Milk temperature 50 6Weighing platform 27 5Fat and protein 20 0Somatic cell count 17 1Activity meters/pedometers dairy cows 41 70Activity meters/pedometers young stock 12 28Temperature 6 14Rumination 9 12Lactate dehydrogenase (LDH) 2 1Progesterone 2 1
Then why are adoption rates limited
1,672 farms approached512 farmers replied202 indicated to have sensors(Steeneveld and Hogeveen, 2015)
12%
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
Take home message
Sensors are state-of-the-art pieces of technology that develop and improve rapidly
Sensors are state-of-the-art pieces of technology that develop and improve rapidly
It’s all about monitoring parameters associated with events of interest, but sensors
May not accurately or precisely monitor these parameters
It’s all about monitoring parameters associated with events of interest, but sensors
May not accurately monitor these parameters
Monitor a proxy for these parameters
viscosity measurements;Whyte et al., 2004
It’s all about monitoring parameters associated with events of interest, but sensors
May not accurately monitor these parameters
Monitor a proxy for these parameters
Monitor parameters that are not unique for the event
It’s all about monitoring parameters associated with events of interest, but sensors
May not accurately monitor these parameters
Monitor a proxy for these parameters
Monitor parameters that are not unique for the event
Monitor one single aspect of a complex event
Always a trade-of between
SensitivityHow many events do you
detect (true positive alerts) and how many do you
miss (false negative alerts)
SpecificityHow many healthy cows do
not receive an alert (true negative alert)
and how many do receive an alert falsely
(false positive alert)
Trade-off dependants
Event being monitored
Dairying system in which sensor is implemented
Economic consequences of decision-making based on inaccurate sensor information
Farmer’s preference (risk attitude)
Example automated mastitis detection
High SN
no additional labour for checking alerts
High SP
nuisance of fetching cows and checking alerts
Willing to accept mildly infected cows remain undetected(Mollenhorst et al., 2012;
Hogeveen and Steeneveld, 2013)
Example automated oestrus detection with 70% sensitivity
Year-round calving might be OK
But what about seasonal calving?6wks time to get all cows pregnantEconomic losses in case oestrus events are missed
Farmers’ attitude
Being in control Letting-go
Farmers’ attitude
Eager to understand and learn the system Not having the time or skills
Sensors are not about ‘one size fits all’
Waiting for ‘improved’ systems(Borchers and Bewley, 2015; Steeneveld and Hogeveen, 2015; Russell and Bewley, 2013)
44
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
Take home message
Use of sensor information is limited
Sensor AMS (%) CMS (%)
Never/ sometimes
Daily Never/ sometimes
Daily
Colour (n=72 / 1) 49 32 100 0
Fat and protein sensor (n = 24) 63 17
Electrical conductivity (n = 112 / 28) 5 77 25 21
Weighing platform (n = 33 / 4) 39 21 25 50
Activity meters/pedometers dairy cows (n = 50 / 57)
6 74 6 74
Use of sensor information is limited
5% of generated mastitis alerts are visually checked
Use of sensor information is limited
5% of generated mastitis alert lists are visually checked
Reasons not to check alerts included:
No deviation in yield (19%)No flakes on filter (28%) Repeatedly on list (10%)
Too busy (10%)Malfunctioning (4%) No EC increase (5%)
Use of sensor information is limited
5% of generated mastitis alert lists are visually checked
Reasons not to check alerts
Consequence: 75% of detected mastitis is not ‘seen’ (Hogeveen and Steeneveld, 2013)
Use of sensor information is limited
22% of farm owners indicated that expectations did not match performance reality
24% of farm owners indicatedthat learning support was not as expected (Eastwood et al., 2015)
Too much information without knowing what to do with it (Russell and Bewley, 2013)
51
What can you expect
Claudia Kamphuis
Sensor technologies in the milking parlour
Performance of sensor technologies
Working with sensor technologies
Take home message
Sensors are exciting, high-tech and have potential
But we need their information combined with
To complement our management decisions on cow health and productivity
Thank you for your attention
www.slideshare.net/claudiakamphuis ckamphuis
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