Modelling in the SDF projectCase: improve heat detection by combining sensor data

Claudia Kamphuis, Wageningen UniversityKirsten Huijps, CRVPieter Hogewerf, Wageningen Livestock Research

Content

- The Why and What of Smart Dairy Farming

- Fertility and heat detection

- Where to from here

SDF: Why & What

Improve a cow’s productive lifetime by putting the famer and the cow in the

centre

Three processes that are difficult to manage but that will increase

productive lifetime

Collaboration between commercial companies, research centres,

universities and FARMERS

Develop decision support models, management tools and advisory products that contribute to an increased productive lifetime

SDF: Fertility Project

- Importance of fertility- A cow needs a calf to produce milk- Goal to get cows pregnant fast- Key drivers: detection and insemination

-Current challenges- Time consuming - Recording- Increased herd sizes

SDF: Fertility Project

- Automated heat detection: a success story- Automated heat detection: a success story...when it all works

SDF: Fertility Project GOAL

Improve automated heat detection by using all available dataProvide insemination advice (bull information, timing)Generate follow-up listsGenerate calving attentions

Data collection in the fieldTwo commercial farms in ‘Friesland’

• 250 cows• 2.5 fte

• 450 cows• 4.5 fte

820-8-2015

Farm 1Yield, Weight, Feed intakeevery milking (24/7)

Activity (alerts), Rumination every 2h

Collection since June 2013- Manual recording of heat observations- Continuous automatic recording of sensor data

Activity (alerts) every hour

Yield every day

Activity, Eating, Feeding,Ruminating, every hour

Lactation, calving dates, every 4wks

Difficulties in data collection

Action Farm 1 Farm 2Combining sensor data streams (2h blocks)

617,000 788,000

Adding observed heat events 398 events203 cows

477 events236 cows

Develop predictive variables from all raw sensor data

60 105

Develop Logitboost model 398 events398 GS+

20000 GS-

121 events441 GS+

11,032 GS-

Validate model using April 2014 63 events63 GS+

111,186 GS-

24 events72 GS+

22,371 GS-

Mining a predictive model

Preliminary results

Model GS positive Sensitivity (%)

False positives per day

One sensor 63 44 2.5

Combined 63 75 2.8

Model GS positive Sensitivity (%)

False positives per day

One sensor 24 92 2.2

Combined 24 96 1.1

Heat tab

List of cows that were detected as ‘in heat’

Where to from here?

From modelling to near real-time 4 times a day

Per individual cowbest insemination timebull advicetime left for insemination

Where to from here

Near real-time on Farm 2Fine-tune current models

200 farmers across The Netherlands in 2015X different combinations of sensing systemsX number of new detection models

Scaling up

-Smart Dairy Farming: why and what

-Importance of (automated) heat detection- Improve detection by combining sensor data- SDF-Model appears to have potential- SDF-Model is running near real-time ‘as-we-speak’

-Future work- Near real-time Farm 2- Fine-tuning models- Scaling up

Where to from here