Dairy cow longevity early and late predictors. Ulf Emanuelson Dep t Clinical Sciences Swedish University of Agricultural Sciences

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1 Dairy cow longevity early and late predictors Ulf Emanuelson Dep t Clinical Sciences Swedish University of Agricultural Sciences

2 Roadmap of today s journey Background Early and late events with implications on cow longevity Monitoring of these events

3 Dairy cow lifecycle 1 st Breeding period Weaning 1 st calving Transition period Calving Dry period, mammary involution, BCS, risk of infection Early lactation Peak lactation Colostrum period Conception Preconception Birth Late lactation After John Roche, DairyNZ

4 Why should a dairy cow live long? Early culling may indicate health / welfare problems. The carbon footprint per kg produce is reduced. The costs for a replacement heifer will be recovered Months Source: Patrik Nordgren, Växa Sverige

5 Why should a dairy cow live long? Early culling may indicate health / welfare problems. The carbon footprint per kg produce is reduced. The costs for a replacement heifer will be recovered. Longevity included in genetic selection in many countries for years.

6 Why should a dairy cow live long? Early culling may indicate health / welfare problems. The carbon footprint per kg produce is reduced. The costs for a replacement heifer will be recovered. Longevity included in genetic selection in many countries for years SRB SH SRB SH Average breeding value for survival for Swedish cows per year of birth and breed (Eriksson J-Å, personal communication) Age (in months) of culled Swedish cows per year and breed (Swedish Dairy Assoc., )

7 Early predictors

8 Calf morbidity Warnick (1997): No association (tendency for dullness); owner recorded diseases Hultgren (2009): No association; technician / vet / owner recording of diseases Bach (2011): Diarrhoea, navel infection no association Bovine respiratory disease (BRD) reduced chance to complete 1 st lactation Stanton (2012): BRD before 120d reduced chance to complete 1 st lactation Schaffer (2016): BRD before 120d reduced chance to complete 1 st lactation

9 Growth Le Cozler (2010) Lower growth rates d & d decreased longevity Bach (2011) Higher growth rates 12-65d increased chance to complete 1 st lactation NB high rates before puberty not always beneficial for milk production

10 Failure of passive transfer (FPT) Faber (2005): 2 vs. 4L colostrum within 1h of birth; the rest of feeding was equal 75 and 87% survival through 2 nd lactation, respectively Epigenetic programming? [Raboisson (2016): FPT increased risk for BRD]

11 Monitoring early predictors

12 Characteristics of a monitor Objective High accuracy and precision Cheap / cost-effective Easy / feasible to use Non-invasive

13 Monitoring morbidity (BRD) Objective Accurate/precise Cost-effective Easy Non-invasive Observations by farmer, technician Automatic calf feeder Svensson (2007) unrewarded visits associated with disease Borderas (2009) milk intake / frequency / duration associated with disease, but affected by feed allowance Social and feeding behaviour [Weary, 2009; Rushen, 2012] Cramer (2016) behaviour scoring and association with BRD Moya (2015) feeding behaviour + pattern recognition and BRD (feedlot) de Passillé (2010) activity meters; health? Smith (2015) - triple-axis accelerometer and health (steers) Position location (only cows?); health? Sound analysis; health?

14 Monitoring growth Electronic scales (automatic?) Girth tape Withers / rump height Objective Accurate/precise Cost-effective Easy Non-invasive

15 Monitoring FPT Refractometer (Brix) on serum samples (at 48h age) Deelen (2014) Brix % and IgG highly correlated (0.93); Sensitivity / Specificity for FPT 89% / 89% Hernandez (2016) r=0.79; Se / Sp = 100% / 89% Epigenetic programming; Telomere length? Objective Accurate/precise Cost-effective Easy Non-invasive

16 Late predictors

17 General longevity Age at first calving (AFC) mixed results Milk production mixed results Foot lesions Lameness Reproduction (not pregnant) Diseases: Metabolic disorders Mastitis Reproductive disorders (metritis)

18 Specifically on-farm mortality, early cull On-farm mortality can be an iceberg indicator for involuntary culling Alvåsen (2014): Traumatic events and (several) diseases Dystocia, stillbirth Early lactation Low or missing milk yield at first test-milking (~disease / disturbance) A transition cow problem Metabolic load, negative energy balance Metabolic adaptation (van Knegsel, 2014)

19

20 Monitoring late predictors

21 Monitoring general predictors Dairy herd improvement / farmer records AFC, milk production, reproduction, diseases Routine claw trimming information foot lesions (triple-axis) Accelerometer lameness, diseases Force sensors lameness Rumen bolus (ph, temperature) diseases Position location lameness, diseases Objective Accurate/precise Cost-effective Easy Non-invasive [Caja, 2016]

22 Monitoring transition problems Objective Accurate/precise Cost-effective Easy Non-invasive Stangaferro (2016) rumination and activity monitoring associated with metabolic, mastitis, metritis risks [and culling ] Roberts (2012) metabolic parameters nonesterified fatty acids (NEFA), β-hydroxybutyric acid (BHBA), calcium associated with early-lactation culling risk Milk-fat composition as biomarkers of metabolic state Crookenden (2016) circulating exosomes as biomarkers of metabolic state Hallén Sandgren (2016) automatic body condition scoring; intra-class correlation ; health?; fertility!

23 At the end of the day (journey) Longevity is in the head of the farmer! Bergeå (2016): Farmers seemed well aware of biological factors related to cow longevity Farmers had not worked explicitly with longevity The heifer push Monitoring and acting on predictors: may not necessarily improve longevity will still improve animal welfare provides room for voluntary culling

24 Concluding remarks Not a completely exhaustive review! There are early predictors! There are ways to monitor these predictors Careful considerations are necessary in choosing if / how to monitor for longevity! There are several later predictors There are ways to monitor these predictors Careful considerations necessary Combinations of monitoring devices Caja (2016): the third sense approach

25 References Warnick, LD; Erb, HN; White, ME The relationship of calfhood morbidity with survival after calving in 25 New York Holstein herds. Preventive Veterinary Medicine 31, , /S (96) Faber, S. N.; Faber, N. E.; McCauley, T. C.; Ax, R. L Case study: effects of colostrum ingestion on lactational performance.. Professional Animal Scientist 21, , Svensson, C.; Jensen, M. B Short communication: Identification of diseased calves by use of data from automatic milk feeders. Journal of Dairy Science 90, , Borderas, T. F.; Rushen, J.; Keyserlingk, M. A. G. von; Passille, A. M. B. de Automated measurement of changes in feeding behavior of milk-fed calves associated with illness.. Journal of Dairy Science 92, , /jds Hultgren, J.; Svensson, C Lifetime risk and cost of clinical mastitis in dairy cows in relation to heifer rearing conditions in southwest Sweden. Journal of Dairy Science 92, , /jds Weary, D. M.; Huzzey, J. M.; von Keyserlingk, M. A. G BOARD-INVITED REVIEW: Using behavior to predict and identify ill health in animals. Journal of Animal Science 87, , /jas de Passille, A. M.; Jensen, M. B.; Chapinal, N.; Rushen, J Technical note: Use of accelerometers to describe gait patterns in dairy calves. Journal of Dairy Science 93, , /jds Le Cozler, Y.; Peccatte, J. R.; Delaby, L A comparative study of three growth profiles during rearing in dairy heifers: Effect of feeding intensity during two successive winters on performances and longevity. Livestock Science 127, , /j.livsci Bach, A Associations between several aspects of heifer development and dairy cow survivability to second lactation. Journal of Dairy Science 94, , /jds Roberts, T.; Chapinal, N.; LeBlanc, S. J.; Kelton, D. F.; Dubuc, J.; Duffield, T. F Metabolic parameters in transition cows as indicators for early-lactation culling risk. Journal of Dairy Science 95, , /jds Rushen, Jeffrey; de Passille, Anne Marie Automated measurement of acceleration can detect effects of age, dehorning and weaning on locomotor play of calves. Applied Animal Behaviour Science 139, , /j.applanim

26 References, cont d Stanton, A. L.; Kelton, D. F.; LeBlanc, S. J.; Wormuth, J.; Leslie, K. E The effect of respiratory disease and a preventative antibiotic treatment on growth, survival, age at first calving, and milk production of dairy heifers. Journal of Dairy Science 95, , /jds Alvasen, K.; Mork, M. Jansson; Dohoo, I. R.; Sandgren, C. Hallen; Thomsen, P. T.; Emanuelson, U Risk factors associated with on-farm mortality in Swedish dairy cows. Preventive Veterinary Medicine 117, , /j.prevetmed Deelen, S. M.; Ollivett, T. L.; Haines, D. M.; Leslie, K. E Evaluation of a Brix refractometer to estimate serum immunoglobulin G concentration in neonatal dairy calves. Journal of Dairy Science 97, , /jds Knegsel, A. T. M. van; Hammon, H. M.; Bernabucci, U.; Bertoni, G.; Bruckmaier, R. M.; Goselink, R. M. A.; Gross, J. J.; Kuhla, B.; Metges, C. C.; Parmentier, H. K.; Trevisi, E.; Troscher, A.; Vuuren, A. M. van Metabolic adaptation during early lactation: key to cow health, longevity and a sustainable dairy production chain.. Cab Reviews 9, 1-15, Moya, D.; Silasi, R.; McAllister, T. A.; Genswein, B.; Crowe, T.; Marti, S.; Schwartzkopf-Genswein, K. S Use of pattern recognition techniques for early detection of morbidity in receiving feedlot cattle. Journal of Animal Science 93, , /jas Smith, Jacqueline L.; Vanzant, Eric S.; Carter, Craig N.; Jackson, Carney B Discrimination of healthy versus sick steers by means of continuous remote monitoring of animal activity. American Journal of Veterinary Research 76, , Weller, J. I.; Ezra, E Environmental and genetic factors affecting cow survival of Israeli Holsteins. Journal of Dairy Science 98, , /jds Bergea, Hanna; Roth, Anki; Emanuelson, Ulf; Agenas, Sigrid Farmer awareness of cow longevity and implications for decision-making at farm level. Acta Agriculturae Scandinavica Section A-Animal Science 66, 25-34, / Caja, Gerardo; Castro-Costa, Andreia; Knight, Christopher H Engineering to support wellbeing of dairy animals. Journal of Dairy Research 83, , /S

27 References, cont d Cramer, M. C.; Ollivett, T. L.; Stanton, A. L Associations of behavior-based measurements and clinical disease in preweaned, group-housed dairy calves. Journal of Dairy Science 99, , /jds Crookenden, M. A.; Walker, C. G.; Peiris, H.; Koh, Y.; Heiser, A.; Loor, J. J.; Moyes, K. M.; Murray, A.; Dukkipati, V. S. R.; Kay, J. K.; Meier, S.; Roche, J. R.; Mitchell, M. D Short communication: Proteins from circulating exosomes represent metabolic state in transition dairy cows. Journal of Dairy Science 99, , /jds Hernandez, D.; Nydam, D. V.; Godden, S. M.; Bristol, L. S.; Kryzer, A.; Ranum, J.; Schaefer, D Brix refractometry in serum as a measure of failure of passive transfer compared to measured immunoglobulin G and total protein by refractometry in serum from dairy calves. Veterinary Journal 211, 82-87, /j.tvjl Raboisson, Didier; Trillat, Pauline; Cahuzac, Clelia Failure of Passive Immune Transfer in Calves: A Meta- Analysis on the Consequences and Assessment of the Economic Impact. Plos One 11, -, /journal.pone Schaffer, Aaron P.; Larson, Robert L.; Cernicchiaro, Natalia; Hanzlicek, Gregg A.; Bartle, Steven J.; Thomson, Daniel U The association between calfhood bovine respiratory disease complex and subsequent departure from the herd, milk production, and reproduction in dairy cattle. JAVMA-Journal of The American Veterinary Medical Association 248, , Stangaferro, M. L.; Wijma, R.; Caixeta, L. S.; Al-Abri, M. A.; Giordano, J. O Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part I. Metabolic and digestive disorders. Journal of Dairy Science 99, , /jds