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Precision dairy farming overseas Experiences and developments from the Netherlands Henk Hogeveen and Wilma Steeneveld
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Page 1: 2015 06-24 precision dairy farming

Precision dairy farming overseasExperiences and developments from the Netherlands

Henk Hogeveen and Wilma Steeneveld

Page 3: 2015 06-24 precision dairy farming

Cattle through the last 14 years (* 1,000)Now: ~1.3 bln kg milk

1999 2002 2005 2008 2011 20143650000

3700000

3750000

3800000

3850000

3900000

3950000

4000000

4050000

4100000

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Grass-based system

Summer

●Fresh grass + corn silage + concentrates

Winter

●Grass silage + corn silage + concentrates

●Half mixed ratio

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Dutch dairy sector

Increasing farm seizes

Mostly own (family) labour

Half grass-based system

●Grazing under pressure (farm management)

●Stimulated (societal preference)

Volatile milk prices

More challenges on management

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and …..

Animal health is becoming more and more important

Stimulated by dairy industry

●Improvement of udder health

●Improvement of claw health

●Improvement of longevity

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Automatic milking

1970’s: Individual animal identification

1980’s: Sensor development

1990’s: Automatic milking

Five systems, different brands

First commercial farms: 1992

19% of Dutch dairy farms

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Automatic milking is not an issue anymore

They function

Service and maintenance (infrastructure) is good

Reasons pro

●Labour savings, quality of labour

●More milkings per cow

Reasons against

●Price (investment)

●Flexibility of expansion

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Sensor system

SensorData

AlertAlgorithm

SOPDecision support

Decision

Otherdata

Rutten et al., 2013, J. Dairy Sci.

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Use of sensor systems in the Netherlands

Questionnaire study: 1,672 Dutch dairy farmers (Accon-AVM)

512 (31%) responded

●212 had sensor systems (41 %)

Permission to use MPR data: 414 (37 % with sensors)

Available accountancy data: 217 farms

Steeneveld et al., 2015, J. Dairy Sci.Steeneveld & Hogeveen, 2015, J. Dairy Sci

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Sensor systems in use (%; n=152)

103 AMS farms 49 CMS farms

Electrical conductivity sensor 98 41

Colour sensor 62 2

Somatic cell count sensor 15 0

Lactate dehydrogenase (LDH) sensor 2 2

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Sensor systems in use (%; n=152)

103 AMS farms 49 CMS farms

Electrical conductivity sensor 98 41

Colour sensor 62 2

Somatic cell count sensor 15 0

Lactate dehydrogenase (LDH) sensor 2 2

Activity meters or pedometers for dairy cows 46 94

Progesterone sensor 1 2

Milk temperature sensor 50 6

Weighing platform 31 6

Fat and protein sensor 22 0

Rumination activity sensor 11 20

Temperature sensor 6 18

Beta-hydroxybutyrate (BHB) sensor 2 2

Urea sensor 1 2

Other sensor systems 4 8

Activity meters or pedometers for young stock 13 35

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Year of investment (CMS farms)

2004 2005 2006 2007 2008 2009 2010 2011 2012 20130

2

4

6

8

10

12

14

Mastitis Rumination Estrus

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Reasons to invest (CMS farms; %)

Rumination (10) Activity (57) Temperature (4)

Reduce labor 30 39 6

Improve health 70 81 25

Insight in health 60 46 0

Not a concise decision

10 4 50

Improve profitability

30 47 0

Other 10 5 25

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Udder health sensors

  Farms AMS farms CMS farms  No sensors Before sensors After sensors Before sensors After sensors

Number of cows  

% growth in size 

Milk production (lbs/cow/year)

86 

3.5 

18,354(8,343)

82  

2.6 

18,476(8,398)

97 

4.2 

18,828(8,558)

 

127 

6.0 

18,416(8,371)

 

159 

9.7 

17,994(8,179)

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Effects on udder health

No sensor system AMS farms before investment

AMS farms after investment

CMS farms before investment

CMS farms after investment

190

195

200

205

210

215

220

225

230

Som

ati

c c

ell c

ount

(*1,0

00 c

ells/m

l)

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Estrus detection sensors

  Farms AMS farms CMS farms  No sensors Before sensors After sensors Before sensors After sensors

Number of cows  

% growth in size 

Milk production (lbs/cow/year)

85 

3.5 

18,352(8,342)

86  

2.8 

18,641(8,473)

102 

5.3 

18,990 (8,632)

 

104 

4.0 

18,139(8,245)

 

131 

6.1 

17,989(8,177)

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Effects on reproduction

No sensor system AMS farms before investment

AMS farms after investment

CMS farms before investment

CMS farms after investment

70

75

80

85

90

95

100

105

Days t

o fi

rst

serv

ice

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Theoretic calculations estrus detection

Advantages twofold

●Labour savings

●Better estrus detection rates -> preg rates

Clear management (decision support) associated with information

Visual SN 50%, SP 100% Sensor SN 80%, SP 95%

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Titelstijl van model bewerken• Klik om de tekststijl van het model

te bewerken– Tweede niveau

• Derde niveau– Vierde niveau

» Vijfde niveau

Investment analysis

Cash flow($/year)

Internal Rate of Return(%)

Pay back period(Years)

Average 3,259 11% 7

Rutten et al., 2014 J. Dairy Sci.

$US = € 0.89

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Reality ($/100 lbs milk)

  No sensor AMS CMS  Before After Before After

Capital costs   5.74 5.34a 7.68b 6.09c 6.28c

 

Labour costs  

6.30 5.95a

 5.75a 5.75c

 5.31c

Variable costs 

9.44 9.11a 9.5a 8.85c 9.29c

Revenues  

23.56 22.36a 23.61b 23.30c 24.01c

 Profit 2.07 1.97a 0.66b 2.60c 3.14c

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aantallen NL noeme

n

FIRST STEP: 2011 – 2014

Co-operation project3 large co-operatieons7 companies5 research organisations7 farmers

Goal:Support dairy farmers in caring for individual animalsGood health, longer life and longer production time of cows

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32

The cow central

Farmer rules

Real time models of different parties

Sensors of different companies

Other data sources

InfoBroker: Open platform for sensor data

Work instructions

Dit project is mogelijk gemaakt door:

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Current demands to dairy industry

Animal well-being

Consumer demands

Environment

Labor

Economics

We have to reduce the use of scarce resources

So: explore the full potential of each individual dairy cow

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Go back to the individual cow

One size does not fit all!!

We are throwing away a part of the potential of our dairy cows!!!!

Dutch farmers do not fully utilize potential

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Thank you for your attention

I wish you a great conference

@henkhogeveen

animal-health-management.blogspot.com

www.slideshare.net/henkhogeveen

Thank you for your attention

Welcome in Leeuwarden 2016