Understanding CNCPS and CPM: Biology, Modeling, and Best Cost Applications for Balancing the Nutrient Requirements in Dairy Diets T. R. Overton, M. E. Van Amburgh, and L. E. Chase Department of Animal Science Cornell University, Ithaca NY Novus International Breakfast at 2010 Penn State Dairy Nutrition Workshop
Outline of discussion Overview of CPM Dairy and CNCPS Key biological concepts in models Opportunities to use models to improve efficiency of nitrogen use on farms Uses of CPM/CNCPS fatty acid submodel Diet comparison CPM and CNCPS 6.1
CPM Dairy Development led by University of Pennsylvania with collaboration from Cornell and W. H. Miner Institute Initial release of CPM Dairy version 1.0 in 1998 Release of CPM Dairy version 3.0 in 2006 CHO and protein biology similar to CNCPS 5.0 Nonlinear optimization Addition of fatty acid submodel Available at www.cpmdairy.net
CNCPS 6.1 Available at www.cncps.cornell.edu in beta form Anticipate final release January 2011 Updates within CNCPS 6.1 Expanded carbohydrate pools and changes in CHO rates Changes in passage rate assignments Changes in nitrogen recycling and protein fraction rates Corrections to accounting in previous versions Net result is significant changes in how CNCPS evaluates nitrogen economy of the cow along with predictions of metabolizable protein Also available to the industry in licensed platforms AMTS www.agmodelsystems.com NDS www.rumen.it
Overview of key biological concepts in CPM/CNCPS
Characteristics of CNCPS and CPM compared to other formulation programs Breaks down carbohydrates and proteins into fractions and models their fermentation/digestion Dynamic versus static Amounts of nutrient fractions fermented/degraded in the rumen depends upon competition between rates of degradation and rates of passage Values for CHO and protein degradability not constant Focused on nutrient requirements versus ingredient requirements Provides ability to focus on improving efficiency of nutrient (N and P) use (and now also methane production in CNCPS 6.1)
CHO fractions and rates in CPM Dairy 3.0 Pool Composition Ruminal Kd (%/hr) Intestinal digestibility, % A1 Silage acids 1 2 100 A2 Simple sugars 100 300 100 B1 Starch 10 40 75 B2 Soluble fiber 40 60 75 B3 Available NDF 2 15 20 C Unavailable NDF 0 0
CNCPS 6.1 CHO Pools and Rates Item Pool Calculation kd %/hr ID % mass Acetic A1 C2 + C3 + C4 0 100 Prop. A1 C2 + C3 + C4 0 100 But. A1 C2 + C3 + C4 0 100 Lactic A2 Lactic 5 100 Other Organics A3 Other OAAs 3 100 Sugar A4 Sugar 40-60 100 Starch B1 Starch 20-60 75 Soluble Fiber B2 Total CHO - (A1 + A2 + A3 + A4 + B1 + B3 + C) 20-60 75 NDF B3 NDF - C 1-15 20 Lignin C Lignin x 2.4 0 0 10
Rates of degradation (kd) of protein A and B1 pools in CNCPS v5.0 and v6.1. Feed ProtA kd v.5.0 ProtA kd v.6.1 ProtB1 kd v.5.0 ProtB1 kd v.6.1 Corn Grain Ground 10000 200 135 50 Corn High Moisture 22% 10000 200 135 50 Soybean Meal 48 10000 200 230 46 Corn Silage 10000 200 300 28 Grass Silage 10000 200 200 49 Alfalfa Silage 10000 200 150 28 From: Broderick, 1989; Volden et al. 2002, Choi et al., 2003; Hequist and Uden, 2006; Lanzas et al., 2007
Pool Disappearance Calculations Rumen disappearance used to be calculated using the same passage rate (feed specific) for all pools. So, disappearance is now calculated as: Protein A and B1 flow with the LIQUID passage rate Carbohydrates A1-A4 flow with the LIQUID passage rate Carbohydrate B1 flows with the CONCENTRATE passage rate All other pools flow with the feed specific passage rates
Summary for CNCPS V6.1 Several updates to the biology and fixes New carbohydrate fractions the CHO A pool has been fractionated into the constituents: volatile fatty acids, lactic acid, organic acids, and sugars (Lanzas et al., 2007) New solid and liquid passage rate equations (Seo et al., 2006) Ruminal nitrogen limitation submodel (Tedeschi et al. 2002) Bacterial ash accounting (Tylutki et al. 2008) Additional updates to pool sizes, chemistry and passage assignments (Van Amburgh et al.)
CNCPS v6.1 Most limiting ME or MP Allowable Milk Yield from 21 to 52 kg/d and CP from 12.7 to 17.4% among 24 data sets (1000 individual cows represented) research to herd level data
Opportunities to improve efficiency of nitrogen and AA use in dairy rations
Protein metabolism in cows Dietary CP Saliva True protein Peptides NPN Urea RUMEN RUP Amino acids Microbial protein Ammonia Liver Amino acids SMALL NTESTINE RUP Microbial protein Endogenous protein Mammary gland Metabolizable protein (absorbed AA) MILK Schwab, 2005
Summary of whole-body nitrogen (protein) metabolism in the cow About 35% of nitrogen intake is excreted in the manure 25 to 30% of nitrogen intake is excreted in the milk Excessive ammonia in the rumen is absorbed and detoxified to urea in the liver Amino acids supplied in excess of requirements absorbed by liver and nitrogen detoxified to urea Urea produced in the liver can be recycled to the rumen for use by rumen bacteria Urea also is excreted in the milk (MUN) and in the urine (waste)
Practical ways to improve N efficiency (Van Amburgh) Reduce amount of N fed Reduce/remove safety factors Utilize N fractions wisely Pay attention to forms fed (soluble, RDP, RUP) rather than total amount of protein Learn how to rely on recycled N to improve efficiencies Focus on absorbable AA Ratios and amounts for maintenance and production
How does decreasing the supply of rumen degradable protein (RDP) affect efficiency of nitrogen use by the cow?
Composition of diets used to evaluate effects of decreasing RDP supply while maintaining RUP supply on performance and nitrogen utilization (Cyriac et al., 2008). NRC predicted RDP, % of diet DM Item 11.3 10.1 8.8 7.6 Ingredient, % of DM Corn silage Mixed grass legume silage Whole cottonseed Rolled high moisture shelled corn Soybean hulls Soybean meal Protected soybean meal Corn grain, ground Tallow Mineral/vitamin 39.7 7.8 2.9 15.5 9.7 20.4 0 0.6 0.9 2.6 39.7 7.8 2.9 15.5 11.4 13.6 4.1 1.3 1.2 2.6 39.7 7.8 2.9 15.5 13.0 6.8 8.3 2.0 1.5 2.7 39.7 7.8 2.9 15.5 14.7 0 12.4 2.7 1.8 2.7 Composition and NRC estimate CP, % of DM NDF, % of DM ADF, % of DM NEL, Mcal/kg RDP supply, g/d RDP balance, g/d RUP supply, g/d 18.4 31.4 18.6 1.6 2611 301 1646 16.8 32.8 20.0 1.6 2328 9 1648 15.2 34.1 21.4 1.6 2045 282 1649 13.6 35.4 22.8 1.6 1762 574 1651
Performance and nitrogen utilization in cows fed diets to decrease RDP supply while maintaining RUP supply on performance and nitrogen utilization (Cyriac et al., 2008). NRC predicted RDP, % of diet DM Item 11.3 10.1 8.8 7.6 DMI, kg/d * Milk yield, kg/d * Milk CP, % Milk CP, kg/d * MUN, mg/dl * NRC predicted NEL allowable milk, kg/d NRC predicted MP allowable milk, kg/d 24.1 41.2 2.98 1.23 20.2 42.0 46.0 23.9 42.1 3.00 1.26 17.6 43.2 44.4 23.2 40.3 3.01 1.21 14.2 41.3 37.8 20.4 36.6 2.92 1.07 12.4 35.4 29.3 Nitrogen Intake N, g/d * Milk N, g/d * Predicted urine N, g/d * N efficiency (Milk/intake), % * 719 197 350 27.7 613 191 304 30.9 544 193 248 35.5 453 169 210 38.6 * denotes significant (P < 0.05) linear or quadratic effect of treatment
Example use of CNCPS to improve efficiency of nitrogen use
900-cow dairy, Lansing NY High group ~1550 lbs ~ 100 DIM 60 lb/d DMI ~ 120 lb/d milk 16.1% CP 60% forage
Item CP (%DM) 16.1 SP (%CP) 38 RDP (%DM) 8.14 Ether Extract (%DM) 5.2 LCFA (%DM) 4.1 Total Unsaturate (g/day) 726.7 NFC (%DM) 41.1 Total Ferm. CHO (%CHO) 59.0 Ash (%DM) 7.59 Forage (%DM) 60.0 NDF (%DM) 30.93 Forage NDF (%DM) 24.22 Forage NDF (%NDF) 78.31 Forage NDF (%BW) 0.94 CHO A4 (Sugar) 5.5 CHO B1 (Starch) 28.3 CHO B2 (Sol. Fiber) 7.4 CHO_B3 (Avail. NDF) 24.2 CHO C (2.4 * Lig) 6.7
N efficiency 37% Most farms are 25 to 30% Productive N:Urinary N 1.47:1 Most farms are 0.6 to 0.8:1 Van Amburgh, Chase, and Higgs, unpublished data
Survey of commercial herds achieving high levels of milk nitrogen efficiency. From Higgs (2009) MS Thesis LE Chase, advisor
Survey of commercial herds achieving high levels of milk nitrogen efficiency. From Higgs (2009) MS Thesis LE Chase, advisor
Survey of commercial herds achieving high levels of milk nitrogen efficiency. From Higgs (2009) MS Thesis LE Chase, advisor
Fatty acid submodel (Moate et al., 2004) New addition with CPM 3.0 Incorporated into CNCPS 6.1 Predicts intakes, ruminal metabolism, flows to intestine, and digestibility of fatty acids Strengths Feed fatty acid library (intake predictions) Weaknesses Predictions of duodenal flows of individual fatty acids
Milk fat case study 70-cow dairy Production average ~ 90 lbs Milk fat consistently running ~3.0 to 3.1%
Rumensin ~ 320 mg/d
Ration example CNCPS 6.1 vs. CPM
Northeast/Upper Midwest ration example
Base diet Modified diet
Base diet Modified diet
Base diet Modified diet
Base diet Modified diet
Base diet Modified diet
Base diet Modified diet
Summary and conclusions Updates to CNCPS 6.1 have made the model more robust in evaluating on farm nutritional management Updates to pool sizes, digestion and passage rates/assignments made the model more sensitive in predicting ME and MP allowable milk Most apparent for protein and N supply, especially with lower CP diets Fatty acid submodel has some utility in helping troubleshoot milk fat issues
Novus International / Cornell webinar series Conducted in collaboration with Dairy Herd Management magazine www.dairyherd.com Webinars already conducted (recorded and available) Overview of CNCPS 6.1 and comparison to CPM Drs Mike Van Amburgh and Tom Overton Improving efficiency of nitrogen use Drs Mike Van Amburgh and Larry Chase Upcoming webinars November 17 Oxidative balance Drs. Barry Bradford (K State) and Julia Dibner (Novus) December 16 Transition cow nutrition Dr. Tom Overton January 12 Cow comfort study February 9 Troubleshooting milk fat Dr. Tom Overton