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Monitoring of the dairy cow for optimizing health and production - energy and protein status i Klaus Lønne Ingvartsen Department of Animal Science, Aarhus University, Tjele, Denmark AU-FOULUM AU AARHUS KLAUS LØNNE INGVARTSEN UNIVERSITY HEAD OF DEPARTMENT 25 AUGUST 2015 DEPARTMENT OF ANIMAL SCIENCE 1

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 AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 2

Average herd milk yield close to 10,000 kg / cow i en Consequences of a 1.5% increase in milk yield / year? OUTPUT: IMPROVED:  Milk yield Breeding  Efficiency Feeding -  Health? Management  Reproduction Environment/ Housing AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 3

Disease incidence relative to days from calving (Ingvartsen et al., 2003) AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Production diseases are multifactorial Clinical Risk of disease Subclinical Nutrition Physiological Stress Production Management and Status Immuno- Rumen/ Genotype reproduction logical organ Prod. system Better to prevent than to treat! AU AARHUS 5 UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Physiological – immunological interactions and risk of infections (mod. from Ingvartsen et al. 2003; Ingvartsen & Moyes, 2012, 2015) Changes around calving   NEFA GH Environment Genotype   ketone bodies IGF-I • nutrition   glucose insulin • management   glutamine leptin • stress  other AA  cortisol • infection progesterone  immune  Immune system pressure  estrogen  hematopoesis proteins  chemotaxis  migration Peripheral tissue Liver  milk yield  fat infiltration  i mmune proteins  mobilisation of  collectin secretion  opsonisation  acute phase proteins body tissue  phagocytosis  synthesis of other  oxidative “kill” proteins  Risk of infections  Ig production AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

From dry to late pregnancy and i early lactation en g Day 250 of pregnancy: ksten ),  Foetus weight = 35; energy req. = 2.3 Mcal NE l /day or 1.2 FE/day (35-40% brug ‘Forøg listeniveau’ glucose, 55% amino acids, 5-10% acetate)  + development of mammary tissue etc. kst g Early lactation, nutrients for 50 kg milk: ‘Formindsk listeniveau’  2000 g milk fat  1600 g milk protein  2500 g lactose  65 g Ca, 50 g P, 8 g Mg AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Is it milk yield or acceleration in milk yield that is a i risk factor (Ingvartsen et al., 2003, Hansen et al. 2006 en g ksten ), brug ‘Forøg listeniveau’ kst g ‘Formindsk listeniveau’ › Cause of increased disease risk: › Probably not yield per se. › Rate of increase in daily milk yield (acceleration) → Adaptational problems. Physiological imbalance? AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 8

i Physiological Imbalance (PI) en g  Hypothesis: Immune function and health can be improved by ksten ), reducing the PI in cows, and at the same time it will improve brug ‘Forøg listeniveau’ production and reproduction (Ingvartsen et al., 2003, 2006; Ingvartsen and Moyes, 2012) kst g ‘Formindsk listeniveau’  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) AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 9

Surveillance is essential for prevention  Manual surveillance is important – but has its limitations  Surveillance at feeding and milking has changed  Large herds  Subclinical problems AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 10

Early identification is key to reduced disease i incidence and secures optimal production en Biomarkers in relation to state: g ksten ), brug ‘Forøg listeniveau’ Health: kst g ‘Formindsk listeniveau’ Production: AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 11

Efficient management calls for:  Early identification of “risk cows” Proactive  Manage animal status & risk by management  c hanging “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 Cost effective  Optimization at cow and herd level AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

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 optimization cow as its own control AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Herd/group vs. individual i en Effect of parity and TMR energy density on plasma [BOHB] mM 1,49 12.9 MJ DE 13.6 MJ DE pr. kg DM pr. kg DM 1,22 1,00 0,82 0,67 0,55 Weeks around calving Weeks around calving Parity: ∆ ∆ = 1.; ౦ ౦ = 2.; □ □ = 3. AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Large between cow differences Weeks around calving Total var. Genetic var. Between cows var. Residual 0 42 84 128 168 210 Days around calving Days around calving AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Periparturient changes in NEFA, BHBA and glucose i - the “text book cow”, high yielding and healthy en Glucose NEFA BHBA AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Periparturient changes in NEFA, BHBA and glucose i – the mobilizing healthy but low performance cow en Glucose NEFA BHBA AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Periparturient changes in NEFA, BHBA and glucose i – the mobilizing high yielding risk cow en Glucose NEFA BHBA AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Problem and challenge  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) AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 19

“Off feed” challenge – Cows, design, sampling  29 healthy Holstein cows:  early lactation (n = 14; 22-86 DIM) Nutrient Restriction:  mid-lactation (n = 15; 100-217 DIM) 40% NE L requirements -96 -72 -48 -24 0 24 48 72 96 Hours  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 AU AARHUS UNIVERSITY 25 August 2015  2. iTRAQ-based quantitative profiling using LC-MS/MS (proteomics) Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department

Change in energy density caused marked changes i in DMI and milk yield en DMI, Kg/d Milk Yield, kg/d Time relative to restriction, h Time relative to restriction, h Bjerre-Hapøth et al., 2012 AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen 21 DEPARTMENT OF ANIMAL SCIENCE Head of Department

i EB was reduced by reduced energy density en EB, Mcal/d Time relative to restriction, h Bjerre-Hapøth et al., 2012 AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 22

Changes in milk parameters during nutrient i restriction – early and mid-lactation en Early lact. Mid lact. Time relative to nutrient restriction (0-96 h) AU AARHUS UNIVERSITY 25 August 2015 Klaus Lønne Ingvartsen DEPARTMENT OF ANIMAL SCIENCE Head of Department 23