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Monitoring of the dairy cow for optimizing health and production - energy and protein status i Klaus Lnne Ingvartsen Department of Animal Science, Aarhus University, Tjele, Denmark AU-FOULUM AU AARHUS KLAUS LNNE INGVARTSEN UNIVERSITY

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25 AUGUST 2015 HEAD OF DEPARTMENT KLAUS LØNNE INGVARTSEN

AARHUS UNIVERSITY

DEPARTMENT OF ANIMAL SCIENCE

AU

Monitoring of the dairy cow for

  • ptimizing health and production
  • energy and protein status

Klaus Lønne Ingvartsen Department of Animal Science, Aarhus University, Tjele, Denmark

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AU-FOULUM

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Outline

  • Introduction
  • Physiological imbalance – what is it?
  • Need for surveillance and automated precision management

systems

  • Should we focus on herd, group or individual cow level?
  • Biomarkers and sensors for energy status
  • Biomarkers and sensors for energy protein / AA status
  • Conclusion

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

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Average herd milk yield close to 10,000 kg / cow

Consequences of a 1.5% increase in milk yield / year?

IMPROVED: Breeding Feeding Management Environment/ Housing OUTPUT:

  •  Health?

 Reproduction  Milk yield  Efficiency

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Disease incidence relative to days from calving

(Ingvartsen et al., 2003)

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Production diseases are multifactorial

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Nutrition Management

  • Prod. system

Genotype Risk of disease Clinical Subclinical Immuno- logical Physiological

Status

Stress Rumen/

  • rgan

Better to prevent than to treat!

Production and reproduction

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Changes around calving

GH

 NEFA 

IGF-I

 ketone bodies 

insulin

 glucose 

leptin

 glutamine  cortisol

 other AA

progesterone  immune

 estrogen

proteins Environment

  • nutrition
  • management
  • stress
  • infection

pressure Genotype

Peripheral tissue  milk yield  mobilisation of body tissue Liver  fat infiltration  collectin secretion  acute phase proteins  synthesis of other proteins

 Risk of infections

Immune system

 hematopoesis

 chemotaxis  migration  immune proteins  opsonisation  phagocytosis  oxidative “kill”  Ig production

Physiological – immunological interactions and risk

  • f infections (mod. from Ingvartsen et al. 2003; Ingvartsen & Moyes, 2012, 2015)
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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

g ksten ), brug ‘Forøg listeniveau’ kst g ‘Formindsk listeniveau’ i en

Day 250 of pregnancy:

  • Foetus weight = 35; energy req. = 2.3 Mcal NEl/day or 1.2 FE/day (35-40%

glucose, 55% amino acids, 5-10% acetate)

  • + development of mammary tissue etc.

Early lactation, nutrients for 50 kg milk:

  • 2000 g milk fat
  • 1600 g milk protein
  • 2500 g lactose
  • 65 g Ca, 50 g P, 8 g Mg

From dry to late pregnancy and early lactation

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

g ksten ), brug ‘Forøg listeniveau’ kst g ‘Formindsk listeniveau’ i en

Is it milk yield or acceleration in milk yield that is a risk factor (Ingvartsen et al., 2003, Hansen et al. 2006

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› Cause of increased disease risk: › Probably not yield per se. › Rate of increase in daily milk yield (acceleration) → Adaptational problems. Physiological imbalance?

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

g ksten ), brug ‘Forøg listeniveau’ kst g ‘Formindsk listeniveau’ i en

  • Hypothesis: Immune function and health can be improved by

reducing the PI in cows, and at the same time it will improve production and reproduction (Ingvartsen et al., 2003, 2006; Ingvartsen and Moyes, 2012)

  • Definition of PI: cows whose parameters (e.g. glucose, BHBA,

NEFA) deviate from the normal, and who consequently have an increased risk of developing diseases (clinical or subclinical) and reduced reproduction and/or production (Ingvartsen, 2006)

Physiological Imbalance (PI)

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Surveillance is essential for prevention

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  • Manual surveillance is important – but has its limitations
  • Surveillance at feeding and milking has changed
  • Large herds
  • Subclinical problems
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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

g ksten ), brug ‘Forøg listeniveau’ kst g ‘Formindsk listeniveau’ i en

Early identification is key to reduced disease incidence and secures optimal production

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Biomarkers in relation to state: Production: Health:

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Efficient management calls for:

  • Early identification of “risk cows”
  • Manage animal status & risk by
  • changing “input” to “risk cows”

Calls for real-time on-farm solutions based on:

  • Efficient biomarkers
  • Automated sampling / analysis (sensors)
  • Biological and biometric models
  • Ability to describe animal status
  • Methods to describe risk (e.g. for a disease)
  • (Autom.) change of “input” for prevention
  • Optimization at cow and herd level

Proactive management Cost effective

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Need for automated precision management systems

There is a need for cost effective automated precision management systems where equipment combines advanced sensors, technologies and biological knowledge to obtain:

  • low disease incidence and severity,
  • animal welfare,
  • low impact on the environment,
  • requested product quality,
  • optimal production and reproduction,
  • profitability for the producer.

Individual cow monitoring cow as its own control

  • ptimization
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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

Weeks around calving

Herd/group vs. individual

Effect of parity and TMR energy density on plasma [BOHB]

mM 1,49 1,22 1,00 0,82 0,67 0,55

13.6 MJ DE

  • pr. kg DM

Parity: ∆ ∆ = 1.; ౦ ౦ = 2.; □ □ = 3.

Weeks around calving 12.9 MJ DE

  • pr. kg DM
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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Large between cow differences

Days around calving 0 42 84 128 168 210 Days around calving

Total var. Genetic var. Between cows var. Residual Weeks around calving

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

Glucose

Periparturient changes in NEFA, BHBA and glucose

  • the “text book cow”, high yielding and healthy

NEFA BHBA

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

Glucose NEFA BHBA

Periparturient changes in NEFA, BHBA and glucose – the mobilizing healthy but low performance cow

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

Glucose NEFA BHBA

Periparturient changes in NEFA, BHBA and glucose – the mobilizing high yielding risk cow

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Problem and challenge

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  • EB, blod/urine variables and PI based on blood are not

possible/cost effective at commercial settings!

  • Our objectives are therefore:
  • Identify potential biomarkers in milk for degree of PI that allow automation
  • Automated system (like we did in e.g. the “Herd Navigator” system)
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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

“Off feed” challenge – Cows, design, sampling

  • 29 healthy Holstein cows:
  • early lactation (n = 14; 22-86 DIM)
  • mid-lactation (n = 15; 100-217 DIM)
  • Daily registrations: Feed intake, milk yield and components
  • Blood collection for analysis of NEFA, BHBA, and glucose
  • Milk for detailed analysis
  • Liver samples collected for:
  • 1. Chemical analysis
  • 2. iTRAQ-based quantitative profiling using LC-MS/MS (proteomics)

Nutrient Restriction: 40% NEL requirements

96 24 48 72

  • 24
  • 72
  • 48
  • 96

Hours

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

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Change in energy density caused marked changes in DMI and milk yield

Bjerre-Hapøth et al., 2012 Time relative to restriction, h Time relative to restriction, h Milk Yield, kg/d DMI, Kg/d

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

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EB was reduced by reduced energy density

Time relative to restriction, h EB, Mcal/d Bjerre-Hapøth et al., 2012

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

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Changes in milk parameters during nutrient restriction – early and mid-lactation

Early lact.

Time relative to nutrient restriction (0-96 h)

Mid lact.

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

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Are requirements for metabolizable protein fulfilled in early lactation?

Larsen et al. 2014 Bell et al., 2000

Metabolisable protein supply

Days relative to calving

  • 15
  • 10
  • 5

5 10 15 20 25 30 g/d 500 1000 1500 2000 2500 3000

Casein Control F677-1; n = 4

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

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Are control animals experiencing imbalance?

Milk yield

Days relative to calving

  • 15
  • 10
  • 5

5 10 15 20 25 30 Milk yield, kg/d 10 20 30 40 50 60

Casein Control Ptrt = < 0.01; PDIM < 0.01, Ptrt x DIM = 0.86 F677-1; n = 4

Arterial essential AA Days relative to calving

  • 14

4 15 29

  • 14

4 15 29 µmol/L 400 500 600 700 800 900 1000 1100 1200

Control Casein

Ptrans x trt < 0.01 Ptrt = 0.22, PDIM = 0.20, Ptrt x DIM = 0.02 F677-1; n = 4

Mogens Larsen, pers. comm.

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Treatments – abomasal infusion of protein or water

Foulum exp., 4 cows Canadian exp., 5 cows

Infusion af frie aminosyrer

Dage efter kælvning 5 10 15 20 25 30 Aminosyrer, g/d 100 200 300 400 500 600 700 800

n = 5

Infusion af kasein

Dage efter kælvning 5 10 15 20 25 30 Kasein, g/d 100 200 300 400 500 600 700 800

n = 4

Basal ration: 15.9 % crude prot.

Larsen et al. 2014 Larsen et al. 2015

Basal ration: 16.4 % crude prot.

Infusion of casein Infusion of amino acids Days after calving Days after calving

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Milk yield increased by 7 to 8 kg/d/cow

Mælkeydelse

Dage efter kælvning

  • 15
  • 10
  • 5

5 10 15 20 25 30 kg/d 10 20 30 40 50 60

AAT Kontrol Ptrt < 0.01; PDIM < 0.01

Mælkeydelse

Dage efter kælvning

  • 15
  • 10
  • 5

5 10 15 20 25 30 kg/d 10 20 30 40 50 60

AAT Kontrol Ptrt < 0.01, PDIM < 0.01

46.0 ± 0.8 38.2 ± 0.9

Larsen et al. 2014 Larsen et al. 2015

Foulum experiment Canadian experiment

Days around calving Days around calving

Are control animals experiencing imbalance?

Milk yield Milk´yield

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

High utilization of extra protein

Udnyttelse af ekstra AAT til mælkeprotein Dage efter kælvning 4 15 29 4 15 29 g/d 200 400 600 1200 1400 1600 1800

Mælkeprotein CTRL Mælkeprotein AAT Infunderet protein

n = 4 65% udnyttelse 43% udnyttelse 60% udnyttelse

Udnyttelse af ekstra AAT til mælkeprotein Dage efter kælvning 5 15 29 5 15 29 g/d 200 400 600 1200 1400 1600 1800

Mælkeprotein CTRL Mælkeprotein AAT Infunderet protein

58% udnyttelse 50% udnyttelse 57% udnyttelse n = 5

Larsen et al. 2014 Larsen et al. 2015

Days around calving Days around calving

Foulum experiment Canadian experiment

Utilization of extra AAT for milk protein Utilization of extra AAT for milk protein

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Catabolism of amino acids?

Urea i blodet Dage efter kælvning

  • 14

4 15 29

  • 14

4 15 29 mmol/L 2.5 3.0 3.5 4.0 4.5 5.0 5.5

Kontrol AAT

Ptrans x beh = 0.01 Pbeh = 0.03, Pdag = 0.37 n = 4

Urea i blodet Dage efter kælvning

  • 14

5 15 29

  • 14

5 15 29 mmol/L 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

Kontrol AAT

Pbeh = 0.01, Pdag = 0.50 n = 5

Larsen et al. 2014 Larsen et al. 2015

Days around calving Days around calving

Foulum experiment Canadian experiment

Urea in blood Urea in blood

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Dry matter intake did not change significantly

Tørstofoptagelse

Dage efter kælvning

  • 15
  • 10
  • 5

5 10 15 20 25 30 kg/d 5 10 15 20 25

AAT Kontrol Ptrt = 0.36, PDIM < 0.01 n = 4

Tørstofoptagelse

Dage efter kælvning

  • 15
  • 10
  • 5

5 10 15 20 25 30 kg/d 5 10 15 20 25 30

AAT Kontrol n = 5 Ptrt = 0.02, PDIM < 0.01

18.8 ± 0.4 20.4 ± 0.5

Larsen et al. 2014 Larsen et al. 2015

Days around calving Days around calving

Foulum experiment Canadian experiment

Dry matter intake Urea in blood Dry matter intake

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Only increased fat mobilization in week one

Langkædede fedtsyrer i blodet Dage efter kælvning

  • 14

4 15 29

  • 14

4 15 29 mol/L 100 200 300 400 500 600 700

Kontrol AAT

Ptrans x trt = 0.97 Ptrt x DIM = 0.07 n = 4

Langkædede fedtsyrer i blodet Dage efter kælvning

  • 14

5 15 29

  • 14

5 15 29 mol/L 200 400 600 800 1000

Kontrol AAT

Ptrt x DIM = 0.05 n = 5

Days around calving Days around calving

Foulum experiment Canadian experiment

Plasma NEFA Plasma NEFA

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

Animal behavior as indicators

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  • Diseases:
  • E.g. abnormal walking, reduced eating time, increased lying -> indicator of

lameness.

  • Basic needs:
  • Easy access to food and water, milking, resting.

Effect of increasing milk yield

10,9 9,8 4,7 5,4 8,3 8,8 4 8 12 16 20 24 20kg 40kg

Standing/walking Eating Lying

Hours/day

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

In conclusion - future challenges

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  • To better understand the physiology and immunology of the dairy cow,

particularly in the periparturient period

  • To understand the biological basis of individual differences
  • To improve phenotyping by:
  • Making better use of existing data
  • Developing new biomarkers for common use in management and genomic selection

(e.g. physiological imbalance)

  • To further develop sensors and technology for future automatic proactive

management strategies (incl. optimization)

  • To find “the local truth”
  • To optimization at both individual cow and herd level
  • production, reproduction, risk of disease,

environmental impact, animal welfare, ……

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25 August 2015 Head of Department Klaus Lønne Ingvartsen

DEPARTMENT OF ANIMAL SCIENCE

AARHUS UNIVERSITY

AU

i en

Thank you for your attention

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