The outcome challenge

Transcription

1 Feeding and managing for improved early cyclicity Thomas R. Overton Associate Professor of Animal Science Director, PRO-DAIRY Cornell University The outcome challenge High milk production Maintain/minimize loss of BCS Low incidence of metabolic disorders Minimize loss of immunocompetence Control/decrease days to first ovulation and maintain/enhance fertility Make $$ High producing dairy cows are subfertile Thatcher et al., Theriogenology. 76:

2 Risk factors for resumption of estrous cycles by 65 days postpartum and pregnancy at 1 st AI in lactating dairy cows Variable Cyclic, % (n/n) Adjusted OR (95% CI) P value BCS change from calving to 65 DIM Lost 1 unit or more 58.7 (279/475) Referent Lost < 1 unit 74.6 (2,507/3,361) 1.96 (1.52, 2.52) < No change 80.9 (2,071/2,560) 2.39 (1.74, 3.28) < Milk yield in the first 90 DIM Q1, 32.1 kg/d 72.7 (1,011/1,390) Referent Q2, 39.1 kg/d 77.6 (1,204/1,552) 1.34 (1.13, 1.60) < 0.01 Q3, 43.6 kg/d 77.6 (1,350/1,739) 1.36 (1.15, 1.62) < Q4, 50.0 kg/d 75.3 (1,292/1,715) 1.21 (1.02, 1.43) 0.04 Variable Pregnant, % (n/n) Adjusted OR (95% CI) P value BCS change from calving to 65 DIM Lost 1 unit or more 28.9 (132/472) Referent Lost < 1 unit 37.3 (1204/3230) 1.42 (1.13, 1.79) < 0.01 No change 41.6 (1008/2422) 1.69 (1.32, 2.17) < Milk yield in the first 90 DIM Q1, 32.1 kg/d 37.2 (496/1,334) Referent Q2, 39.1 kg/d 38.9 (576/1,481) 1.06 (0.91, 1.24) 0.42 Q3, 43.6 kg/d 39.3 (652/1,661) 1.09 (0.93, 1.26) 0.26 Q4, 50.0 kg/d 37.6 (620/1,648) 1.03 (0.88, 1.21) 0.65 Santos et al. (2009) Anim. Reprod. Sci. 110: Energy intake and energy balance Milk energy and energy balance r 2 = 0.57 r 2 = 0.07 Santos et al. (2010) Reprod. Dom. Rum. VII: The metabolism challenge required to meet the outcome challenge Abrupt changes in demands for energy (and other nutrients) High gluconeogenic rates during postcalving period Minimize negative diet interactions with metabolism (esp. adipose) Maintain sufficient DMI during precalving period and facilitate acceleration during postcalving period Manage interactions of facility/nonnutritional management factors with metabolism? 2

3 Metabolic Adaptation (Schoenberg, 2010) Increased mobilization of fatty acids Impaired glucose disposal Increased hepatic gluconeogenesis Decreased insulin response of adipose tissue Changes in intake Glucose sparing for gravid uterus and eventually the mammary gland Summary of metabolic regulation work focused on insulin resistance Glucose disposal slower and slope of NEFA decrease less following glucose challenge in prepartum cows compared to early lactation Smith et al., J. Dairy Sci. 87(Suppl. 1):442. Strengthening adipose tissue responses to insulin using targeted approaches in prepartum cows Decreased NEFA spike during immediate periparturient period Smith et al., J. Dairy Sci. 90: ; Smith et al., J. Dairy Sci. 92: Increased DMI during immediate periparturient period Smith et al., J. Dairy Sci. 90: ; Smith et al., J. Dairy Sci. 92: Decreased BCS loss during early lactation and days to first ovulation Smith et al., J. Dairy Sci. 92: Diet Composition (DM basis) Diet Ingredients (%) High Low Cornell T&R Wheat Straw Cornell T&R Corn Silage Concentrate Mix Nutrient High Low NE L (Mcal/kg) CP (%) Soluble protein, % of CP ADF (%) NDF (%) Starch (%) DM Intake High Low Daily DM intake (kg) Schoenberg et al.,

4 Cows fed low energy diets prepartum had greater NEFA decreases following GTT n plasma NEFA (µeq/l) Decrement in High 40 Time (min.) releative to glucose infusion Low Decrease faster AUC for cows fed Diet: P = 0.04 Low diet (1.35 %/min vs Decrease rate %/min) Diet: P = 0.01 Schoenberg et al., 2012 Common observations with prepartum overfeeding/excessive insulin resistance Large decreases in DMI as cows approach calving Low/sluggish increases in DMI in fresh cows Rapid BCS loss during postpartum period Higher incidence of subclinical and clinical ketosis and DA Take homes Coordination of metabolism to support late pregnancy and early lactation is extensive and exquisite Insulin resistance to spare glucose for fetus and mammary gland is important for successful adaptation to lactation Some degree of fat mobilization (and elevated NEFA) is normal Excessive mobilization of fat (elevated NEFA) is associated with metabolic disorders, lower milk production, and poorer reproductive performance Excessive insulin resistance in body fat likely contributes to hypermobilization of NEFA and lower DMI (cows resemble Type II diabetics) Fat cows Cows overfed energy during either far-off or close-up period Impact of environmental stressors? 4

5 Key components of transition cow management Nutritional management Tight control of macrominerals in diet fed to cows as they approach calving Controlling energy intakes both in far-off and close-up groups Ensure cows consume diet as formulated for maximum intake Feeding management is critical Minimize sorting Nonnutritional management Minimize stressors and potential impact on physiology and variation in DMI Prevention strategies for milk fever and related disorders Decrease dietary cation-anion difference (DCAD) of prepartum diet (Na + + K + ) - (Cl - + S -2 ) -- most commonly used and supported by recent meta analysis (Lean et al., 2006) (Na + + K + ) - (Cl S -2 ) supported by other recent meta analysis (Charbonneau et al., 2006); explained more variation in urine ph than in milk fever incidence Two major strategies Partial adjustment using low potassium forages Low potassium forages plus addition of an anionic supplement Martinez et al., 2012 FASS 5

6 Dry period energy formulation from herd to herd is a bit like walking a balance beam If cows consume insufficient energy, more metabolic problems postcalving If cows consume excessive energy, more metabolic problems postcalving Insulin resistance resulting in excessive body fat mobilization and low dry matter intake in fresh cows MAJOR influence of nonnutritional factors on AMOUNT and UNIFORMITY of energy intake during both the far-off and close-up periods Dictates different approaches on different farms to achieve same goal U.S. trends in last 6 to 8 years Largely abandoned steam up concept advocated by 2001 Dairy NRC Controlled energy strategies for dry cows during both faroff and close-up periods (Drackley, 2007) 0.59 to 0.62 Mcal/lb of NEL 12 to 16% starch 40 to 50% forage NDF Appropriate for multiparous cows Too low energy/too bulky for primiparous cows? MP supply?? (RUP supplementation even more important) Diets need to deliver 15 to 18 Mcal/d of NEL (110 to 120% of ME requirements) during both far-off and close-up dry periods Can you go too low? Janovick and Drackley (2010) Cows fed low energy dry cow diets (0.55 vs Mcal NEL/lb) had higher postpartum DMI, lower NEFA, better energy balance, but also yielded less milk (73.4 vs 85.8 lb/d for wk 1-8) 6

7 Overall goals for energy and metabolizable protein intake of both far-off and close-up cows Far off cows (dry off until ~ 3 weeks precalving) ~ Mcal of NEL per day 110 to 120% of ME requirements ~ 1000 g/d of metabolizable protein Close-up cows (last 3 weeks before calving) ~16-18 Mcal of NEL per day 110 to 120% of ME requirements ~ 1100 to 1200 g/d of metabolizable protein Vary energy density of diets based upon group DMI Which means have to know DMI to know how much to bulk up the diet Almost want to achieve the above in the largest DMI package that cows will consume consistently General goals for diet formulation for closeup cows Low K only Full anionic NE L, Mcal/lb ~0.64 to 0.66 NE L, Mcal/kg ~1.40 to 1.45 Metabolizable protein, g/d 1100 to 1200 NFC, % 28 to 32 Starch, % 16 to 19 Dietary Ca, g/d Dietary Ca, % Dietary P, % 030t 0.30 to Mg, % 0.40 to 0.42 Cl, % to 1.2 K, % < 1.3 < 1.3 Na, % 0.10 to 0.15 S, % to 0.4 Added Se, ppm (organic) 0.3 Vitamin A (IU/d) Vitamin D (IU/d) Vitamin E (IU/d) Prefer use of organic trace elements, including organic Se Potential management/facility related stressors for transition cows Overcrowding (increased stocking density) Commingling of cows and heifers Excessive number of pen moves (group changes) Heat stress Overall cow comfort/hygiene 7

8 Stressors for transition cows Decrease (?) dry matter intake and milk Increase body fat mobilization Divert nutrients from milk to stress response/immune system Potential mechanisms Release of pro-inflammatory cytokines (TNF, IL- 1, IL-6) Stress hormones (glucocorticoids, epinephrine, cortisol fecal cortisol metabolites) Inflammation (haptoglobin and other acute phase proteins) The outcome challenge High milk production Maintain/minimize loss of BCS Low incidence of metabolic disorders Minimize loss of immunocompetence Control/decrease days to first ovulation and maintain/enhance fertility Make $$ Why all the variation in cow/herd health/repro/performance? Net effects of integrated and dynamic set of factors Nutritional management (formulation and implementation) Facility characteristics Grouping management Cow/herd management 8

9 Challenges with assessing energy metabolism and inflammation-related opportunities in transition cows Most of dairy industry works on averages Challenges related to energy/grouping mgt/nonnutritional factors cause increases in variation in DMI/performance Almost impossible to detect some of these on farms Potential tools for use in monitoring variation in transition cow management NEFA (best marker for negative energy balance) BHB ( gold standard blood ketone) Haptoglobin and/or fecal cortisol? (not ready for prime time) Variation in early lactation milk yield Materials and Methods Convenience sample of herds Visited by study personnel <10% of herds submitted by veterinarians Cross-sectional sectional sampling ~15 cows 2 to 14 days prior to calving sampled/herd ~15 cows 3 to 14 DIM sampled/herd All appeared to be normal/not treated/not in sick pen 90% CI that sample represents herd prevalence Ospina et al., J. Dairy Sci. 93: Ospina et al., J. Dairy Sci. 93:

10 Herd-level impacts of elevated NEFA/BHB Metabolite level Herd Alarm Associated with: PRE-Partum NEFA > 0.3 meq/l 15% +3.6% Disease incidence -1.2% Pregnancy rate lbs ME305 milk (both heifers and cows) POST-PartumPart m 15% +1.7% Disease incidence b NEFA > 0.6 a -0.7 meq/l - 0.9% Pregnancy rate a Heifers: -640 lbs, Cows: - 1,272 lbs BHB > 10 a -12 b* mg/dl 15% *20% +1.8% Disease incidence b -0.8% Pregnancy rate b Heifers: -1,179 lbs*, Cows: lbs a *15% of 15 = 2-3 animals Ospina et al., 2010 Distribution of herds by proportion of prepartum animals with NEFA > 0.30 meq/l. Ospina et al., J. Dairy Sci. 93 : Distribution of herds by proportion of postpartum animals with BHBA > 12 mg/dl. Ospina et al., J. Dairy Sci. 93 :

11 Distribution of herds by proportion of postpartum animals with NEFA > 0.70 meq/l. Ospina et al., J. Dairy Sci. 93 : Approach for monitoring energy-related blood analytes in transition cows Sample size: 15 to 20 cows Cows to sample Pre-partum: 14 to 2 days before calving Post-partum: 3 to 14 DIM Sample to take Serum (red top tubes) Don t shake, keep cool What to do with sample? BHB: Lab or Precision Extra Meter NEFA: Lab What to do with results Interpret % above cut-point More than 15% above cut-point indicates herd-level problem 11

12 Interpretation of metabolites to assess herd-level opportunities Scenario 1 High prepartum NEFA, High postpartum NEFA and/or BHB Likely starting with low DMI in close-up cows Too low energy in prefresh diet, facility and/or management issues (grouping, stocking, heat stress)? Scenario 2 High prepartum NEFA, low postpartum NEFA and/or BHB Likely low DMI in close-up cows Are you sampling the survivors in the fresh pen? Is the herd outmanaging or putting band-aids on fresh cow issues? Scenario 3 Low prepartum NEFA, high postpartum NEFA and/or BHB Is herd overfeeding energy either far-off or close-up? Diet or facility/management issues specific to maternity/fresh cow group Physiological measures of stress and inflammation? Changes in the activity and functioning of the hypothalamic-pituitary-adrenal (HPA) axis are often used to quantify an animal s response to a potential stressor. Plasma cortisol Non-invasive measures of stress? Fecal Cortisol Metabolites (Möstl and Palme) Environmental stressors can also induce an acute phase response in cattle. Haptoglobin non-specific marker of inflammation, infection or injury Mean (±SE) haptoglobin concentration of healthy (n = 23), mildly metritic (n = 32), and severely metritic (n = 12) cows during the period around calving (From Huzzey et al., 2009) 12

13 What we did Data collected on 2 commercial dairy herds in NYS Weekly blood and fecal samples from 412 transition cows 3 weeks before calving until 1 week after calving Measured plasma NEFA, haptoglobin and cortisol Measured fecal cortisol metabolites 1. Recorded disorders up to 30 DIM DA, RP, Death (DC305) SCK (wk +1 BHB > 10 mg/dl) High Hp (wk +1 Hp > 1 g/l) 2. Predicted Milk Yield 305ME (2nd & 3rd Test day) 3. Reproductive Performance Survival analysis Ospina et al JDS 93: Huzzey et al JDS 89: Huzzey et al., J. Dairy Sci. 94 : Predictors of Disease Classified cows into 3 health categories No Disorder of Interest (NDI) N=183 NO cases of RP, DA, SCK HiHp or death by 30DIM One Disorder N=127 Only one case of RP, DA, SCK or HiHp (no deaths) > One Disorder or Death N=102 More than one case of RP, DA, SCK, HiHp or died by 30DIM Huzzey et al., J. Dairy Sci. 94 : Summary - Predictors of Health Prepartum plasma haptoglobin and cortisol were not good predictors of postpartum health status Cows that developed more than one disorder after calving had greater concentrations of fecal cortisol metabolites before calving BUT Prepartum NEFA was the analyte most strongly associated with our postpartum health outcomes Transition cow metabolite testing programs to evaluate disease risk should focus on NEFA concentrations BHBA also useful as front line monitor 13

14 2. Predictors of Milk Production Is there a relationship between these analytes and milk yield? Evaluated different cutpoints and then looked at the predicted 305ME (2 nd & 3rd test or ~60 and 120 DIM) for cows that were above or below a particular threshold for our analyte of interest 305ME = (305ME Above Cutpoint ) - (305ME Below Cutpoint ) NEFA & Predicted Milk Yield (~60 DIM) lbs Cutpoint: >0.50 meq/l >0.60 meq/l % Cows Above Cutpoint wk -3 wk -2 wk -1 wk +1 Primiparous Multiparous Haptoglobin & Predicted Milk Yield (~60 DIM) lbs Cutpoint: >1.1 g/l % Cows Above Cutpoint wk -3 wk -2 wk -1 wk +1 Primiparous Multiparous

15 Fecal Cortisol Metabolites & Milk Yield (~60 DIM) lbs Cutpoint: 2500 ng/g fecal DM 700 ng/g fecal DM % Cows Above Cutpoint wk -3 wk -2 wk -1 wk +1 Primiparous Multiparous Summary - Predictors of Milk Yield Haptoglobin and fecal cortisol metabolites are sensitive predictors of milk yield Hp and FCORT thresholds are associated with greater changes in 305ME estimates (identify greater milk losses) than NEFA - particularly when measured after calving More animals are identified above these cutpoints (high risk cows) Associations stronger among multiparous cows than primiparous cows. Testing during the week after calving may provide the most reliable information 3. Predictors of Reproductive Performance Is there a relationship between these prepartum analytes and time to conception? 15

16 NEFA and Reproduction % Not Pregnant NEFA > 0.45 meq/l NEFA 0.45 meq/l Heifers sampled 1 wk after calving 39% lower rate of conception (P = 0.02) 0 Days to Pregnancy Heifers > 0.4 meq/l Pre-partum - 42% lower rate of conception (P=0.02) Among Cows NEFA not associated with reproductive performance Haptoglobin and Reproduction % No ot Pregnant Hp > 1.3 g/l Hp 1.3 g/l Heifers sampled 1 wk after calving 42% lower rate of conception (P = 0.02) Days to Pregnancy Heifers > 0.4 g/l Pre-partum - 41% lower rate of conception (P = 0.05) Among Cows Hp not associated with reproductive performance Summary - Reproductive Performance Increased Hp concentrations one wk before (>0.4 g/l) and after ( >1.3 g/l) calving were associated with a % lower rate of conception. NEFA was also associated with reproductive performance but when modeled with Hp was no longer significant. Fecal cortisol metabolites > 2300 ng / g fecal DM were associated with 47% lower rate of conception NEFA was also associated with reproductive perfomance but when modeld with Hp was no longer significant. These associations were limited to primiparous cattle 16

17 the next steps Large scale studies to understand the variation in these biomarkers across herds Identify herd alarm levels (i.e. proportion p of sampled animals that have excessive Hp concentrations) Thanks!!! tro2@cornell.edu 17