Throughput Throughput is the rate at which the system generates money through sales. The Goal, Goldratt. Goal. Operational Expense.

Transcription

1 Optimizing Dairy Rations using CPM Dairy A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be. Wayne Gretzky. Where are you playing? Steve Massie, Western Technical Manager Ian Shivas, Renaissance Help Desk Goal What is the Goal Theory of Constraints What are the bottlenecks on the dairy Throughput Throughput is the rate at which the system generates money through sales. The Goal, Goldratt Inventory Inventory is all the money that the system has invested in purchasing things which it intends to sell Operational Expense Operational expense is all the money the system spends in order to turn inventory into Throughput 1/20

2 What is CPM Modeling? Putting math and numbers to nutritional art and science to increase ability to predict responses to diet change Schematic summary of nitrogen utilization by the ruminant. Source: Satter, Intake METHANE MANURE Environment Temperature Wind Solar Humidity Carbohydrate Protein Fat Minerals Vitamins Fermentation Bugs Digestion Rates ph Passage Rates Glucose VFA Amino Acids Fatty Acids Minerals Vitamins Efficiency of Utilization Insulation Maintenance service functions transport processes protein, fat, nucleic acid turnover substrate cycling Growth protein & fat accretion Lactation milk components Pregnancy fetal placenta HEAT CARBON DIOXIDE Linear vs non Linear Bodyweight at Miner Inst CPM optimizer is nonlinear D = kd/(kp+kd) Competitive situation between degradation and passage Conversion of Dietary Protein, Carbohydrates, and Fat into Milk Components Optimizing Rations Set By Nutrient constraints Set By MinVit constraints Set By Ingredient constraints Be sure prices are current and accurate Keep feed banks up to date with newest definitions 2/20

3 Optimizing Rations Optimizing DMI vs ME? Make sure that there are several ingredient sources for every nutrient constraint set Balancing Ingredients Consider starting with Templates, custom Feedbanks Formulated 2 scenarios DMI locked and ME ME locked and DMI off DMI or ME? Set DMI Set ME Cost ($) $ DMI (lb) CP (%) pendf ME milk MP milk FE Income ($) $10.80 $10.80 IOFC $6.65 $6.01 Forage 83% 59% Same DMI? Set DMI Set ME pendf at 47.5 lb Income ($) $10.80 $13.23 IOFC ($) $6.65 $7.60 Throughput is the rate at which the system generates money through sales. The Goal, Goldratt How about to Rumen Fill Maximize Forage Feeding Goal is to maximize forage feeding intake Ensure adequate rumen mat But not have so much that peak intake and milk are reduced Innovations by Hartwig pendf (%) DMIpeak /20

4 Fragility? Does BMR Corn Silage stimulate as much chewing as conventional Corn Silage? Does alfalfa forage stimulate as much chewing as straw? Forage Fragility Adjustments avgndfd30hr pendfadj pef _ x _ samplendfd30hr 94 x % pendf Takes advantage of forage quality Encourages more of the digestible forage into the ration Ensures that there is adequate effective fiber in the rumen for rumen health Improves efficiency How about to Rumen Fill undf = unavailable NDF undf /2.4 = adj Lignin 19.7/2.4 = 8.21 Disappearance of NDFd using indf to calculate the kd How about to Rumen Fill undf/ BWT x 100 = 5.68 / 1620 x 100 = 0.35 % BWT 4/20

5 Impact on milk Effect of Maturity on Plant Composition, Digestibility and Intake Rolling Herd average (lb/yr) Avg Lb Milk for 365 day 25, , , , , , at undf=0.35% of BWT Set DMI Set ME DMI from undf ME MP pendfsup FE Income $15.35 $25.47 IOFC $9.67 $15.48 High Med Digestibility, % Intake Fiber + Lignin Low Increasing Maturity--- NDF Digestibility Literature Review Every 1% increase in NDF digestibility will increase milk yield by 0.56 lb. and increase DMI by 0.37lb (Oba & Allen, 1996) CHO:A1 Silage Acids CHO:A2 Sugars CHO:B1 Starches CHO:B2 Soluble Fiber Silage Acids NFC CPM Fractions CHO Sugars Carbohydrates Starches Soluble Fiber CHO:B3 available NDF CHO:C Lignin x 2.4 NDF ADF Hemicelluloses Cellulose Available NDF Lignin indf= Lignin x 2.4 A1 A2 B1 B2 B3 C Rate of Fermentation Ruminal Feed Carbohydrate Fermentation Profile sugar Fast Starch and pectin Slow starch Fiber: cellulose hemicellulose This is an example of the information we use to synchronize proteins and carbohydrates 2910 time points are measured over 48 hrs as opposed to just one time point Gas Invitro Technology Gas Produced (ml) Time (hr) Fast Slow Total S (% f DM) 190 NDF NDFIP EAT Time after feeding 5/20

6 Starch Carbohydrate Digestion Starch disappearance needs to be at a rate that can be utilized by the bacteria If properly balanced rumen microbial yield is maximized, feed efficiencies improved If too fast the bacteria, spill to lactic acid and negatively impact on other microbial populations, reducing rumen efficiency If too slow bacteria maintain themselves and do not grow and multiply to produce quality protein for the cow our highest quality of protein for milk production Cell Contents Sugar, Starch, Sol Fiber, Protein Cellulose/Hemicellulose/Lignin Cell Walls = NDF Protozoa Bacteria Fungi Lignin Ether vs. Ester bonds NDF Digestibility Monitor undf Bact Eval Tab To Maximize Microbial Yield 3.01 lbs Most of the microbial protein comes from NFC bacteria. HOWEVER, it is essential to have highly fermentable fiber (and bacterial growth) to encourage higher total ration DMI and allow more NFC intake into the rumen to increase NFC bacterial growth Fermentable Cho = 43% of DMI (41-44%) fstarch+fsugar = 26% (24-28) fstarch+fsugar+fsf = 31% (29-34) Based on 54 lbs DMI or less >32% >10% % 19-21% of DM 30-31% 6%of DM 4-9% 6% of DM (5-8%) Adapted from Wm Chalupa 6/20

7 Synchronizing Carbohydrate and Protein Degradation in the Rumen Carbohydrate Settings Slide from Chuck Schwab Recommended Carbohydrate Levels (DM basis) Group Fermentable Total CHO Fermentable Fiber Fermentable Starch Fermentable sugar Fermentable soluble fiber Close up to Early lacation to Peak to Midlactation Late lactation to to Sniffen & Tucker, 2011: Hoards Dairyman 156: % Fiber Hard, Floury starch Germ Sol Prot ~48 %CP 56% CP more sol protein NDFD 30hr 55.4% 51.3% less dig fiber Lactic Acid (%DM) ph Tip Cap 3 7/20

8 Starch Target 6 7% of starch DMI available after 24hr for post-ruminal digestion Target 19 21% of DMI as rumen Fermentable starch Total Starch ferm Starch = 6 to 7% Too little = Low Milk Too much = Hindgut fermentation 65 to 90% of post ruminal available starch is digested and absorbed as Glucose for milk Optimizing for protein Rumen N Balance 8/20

9 Lactation Protein Efficiency 9/20

10 Amino Acid Efficiency Settings and Results Amino Acid Settings Check AA g/me Mcal Let s Formulate 10/20

11 Fatty Acids Fatty Acid Formulation Fatty Acid Formulation for Butter Fat Fatty Acid Formulation for Butter Fat Monitor C18:1-3 to ensure that it is <2.5% of DM for good butter fat. If 2.6% of DM increased risk of lower BF. Compare Lipolysed with intake, if <90% decreased risk when unsatured g>2.6% DMI Monitor C18:1-3 to ensure that it is <2.5% of DM for good butter fat. If 2.6% of DM increased risk of lower BF. Compare Lipolysed with intake, if <90% decreased risk when unsatured g>2.6% DMI CLA Shift CLA Shift t10c12 CLA trans-10 18:1 t9c11 CLA c10t12 CLA t10c12 CLA MFD trans-10 18:1 Linoleic (18:2) MFD Requires BOTH Shift and Bottleneck Stearic 18:0 Linoleic (18:2) Stearic 18:0 c9t11 CLA trans-11 18:1 c9t11 CLA trans-11 18:1 11/20

12 Bottleneck? linoleic 18:2 trans 18:1 stearic 18:0 CLA 18:2 From Kellens et al., Butter Fat % Predictor personal communication with Adam Lock Sept 2009 Input in tan boxes Results in yellow & green boxes Total Absorbed FA from CPM 88 milk (lb) predicted BF% in above milk (lb) Fatty Acid Monitor personal communication with Charlie Sniffen Jan 2010 Grams intake from CPM Lipolysis DM Intake C18:1 (T+C) C18: C18: % of DMI Total > Target <=2.6%; More than 2.6% is a concern If Lypolysis is <90% then Unsaturated >2.6% may not be a concern Risk of Butter Depression Fats to Add Unsaturated Fatty Acids (%DM) Low Risk Moderate Risk High Risk Highly Available Slowly Available Saturated Fats New Fatty Acid Paradigm MP Amino Acids (Met) Rulquin Ratio Lys:Met 3:1 Gram Intake LCFA Fatty Acids (C18:2) Fatty Acid profile Omega 6 : Omega 3 5:1 Gram Intake Solubility (g/100g 40C) Supplier Bioavailability Zinc sulfate Zinc Proteinate Zinpro 40 Intellibond Zinc 40 Zinc Chelate Mintrex 50 BioPlex Zinc 40 Copper Sulfate Copper Proteinate Zinpro 10 Intellibond Copper 10 Copper Chelate Mintrex 20 BioPlex Copper 10 Manganese Sulfate Manganese Proteinate Zinpro 2.4 Intellibond Manganese 2.4 Manganese Chelate Mintrex 20 BioPlex Manganese /20

13 Rumen Unavailable Mineral Concept Mineral Bioavailability ByPass Mineral Nutrient Sulfate Mineral Nutrient Delivered to absorption site Summary Maximize Microbial yield by feeding highly digestible forages Most of microbial yield comes from NFC bact Highly digestible forages increase kd and kp which increases microbial yield Balance for amino acids to increase prot eff Meet LCFA needs and the LCFA type A good hockey player plays where the puck is. A great hockey player plays where the puck is going to be. Wayne Gretzky Questions?. Where are you playing? Are you formulating for CP or MP or AA per Mcal, Fat or LCFA, NEL or Rumen Fermentable CHO and Post Ruminal CHO? RNI offers training programs through Fast Start to help you differentiate yourself from your competition. If you would like more information regarding Fast Start training please contact your Regional Manager or Steve.Massie@rennut.com. 13/20

14 Before starting: A word about Managing Files How to set up the farm files Strongly suggest weekly BACKUP of these files CPM Preferences Set up, update as needed Make changes on Preferences Menu Click input Block to change colors, name, display units, page layout Click on input block, then button to access folders & select files Click to set up auto loading Feedbank locations Animal Screen Example Animal Inputs Large Holstein 85# milk, 3.8 BF%, 3.15% True Prot 2) Check that Weight matches expected range and default growth for specified Lactation Current Age 37 = 24 mo at 1 st calving +13 mo calving Int. Environment Screen Temp and humidity (avg of high and low) affect intake, and increase maintenance; previous values are cooler going into spring, warmer going into fall Heifers (or cows) may be outside, run a seasonal example (or bad weather) to see environment effect on growth Small breed Weight avg 1) First Enter Mature /- 150; weight from Taped 4th Large breed Lact Cows, check other /-150 lact wts by tape Days in milk (180) Days open (120) = Days Preg (60) / 30 = Calving Int. (13) Night Temp >70 drops intake Hair coat drop down, critical info for heifers especially in winter Look at ages, lbs/day growth for different mature weights Management Screen Ionophore box not active for cows; use for heifers compare with & without Choose appropriate activity level from dropdown, Choose longer distance for 3x-4x herd or long slope up to parlor Note differences in time standing, distance traveled, consider Miner Institute spreadsheet for estimating time budget Calibrating the Model to the Herd Matching Current Milk MP and ME Snapshot of what is going on today If you don t know where you are; how can you tell if you get there or even how to get there. Calibrating gives us a GOOD starting point 14/20

15 Calibrating a Herd Input Current Feed Amounts in Diet Use Min/Vit if minerals are unknown Confirm DMI (predicted vs. actual vs. what is in the current diet) Compare predicted ME & MP Milk to actual Change Corn CHO Rates Main Working Screen Compare herd avg to predicted Feeds Panel Calibrating a Herd Confirm DMI Match Animal Info w/ current numbers Confirm Environment/Management # s Enter Forage Test on Quick Edit On Carbohydrate Page Enter NDF Kd Run Kd Calculator CHO Rate Changes Lab or Kd Calculator Starch Chart Or JJ s Lab # Escape Chart Carb Edit Corn (CS) Starch Fermentability Use the Chart Starch Escape Use the Chart Soluble Fibers use book values Starch Ruminal Fermentability Rates Microns >4,750 4,750-3,250 3,250-2,725 2,725-1,150 1, <600 Moisture Whole L. Coarse M.Coarse Med L. Fines S. Fines Powder 10% 5% 6% 7% 8% 9% 10% 11% 11% 6% 7% 8% 9% 10% 11% 12% 12% 7% 8% 9% 10% 11% 12% 13% 13% 8% 9% 10% 11% 12% 13% 14% 14% 9% 10% 11% 12% 13% 14% 15% 15% 10% 11% 12% 13% 14% 15% 16% 16% 11% 12% 13% 14% 15% 16% 17% 17% 12% 13% 14% 15% 16% 17% 18% 18% 13% 14% 15% 16% 17% 18% 19% 19% 14% 15% 16% 17% 18% 19% 20% 20% 15% 16% 17% 18% 19% 20% 21% 21% 16% 17% 18% 19% 20% 21% 22% 22% 17% 18% 19% 20% 21% 22% 23% 23% 18% 19% 20% 21% 22% 23% 24% 24% 19% 20% 21% 22% 23% 24% 25% 25% 20% 21% 22% 23% 24% 25% 26% 26% 21% 22% 23% 24% 25% 26% 27% 27% 22% 23% 24% 25% 26% 27% 28% 28% 23% 24% 25% 26% 27% 28% 29% 29% 24% 25% 26% 27% 28% 29% 30% 30% 25% 26% 27% 28% 29% 30% 30% 31% 26% 27% 28% 29% 30% 30% 30% 32% 27% 28% 29% 30% 30% 30% 30% 15/20

16 Starch Escape Digestibility Rates Microns >4,750 4,750-3,250 3,250-2,725 2,725-1,150 1, <600 Moisture Whole L. Coarse M.Coarse Med L. Fines S. Fines Powder 10% 55% 60% 65% 70% 75% 80% 85% 11% 56% 62% 66% 71% 76% 81% 86% 12% 57% 63% 67% 72% 77% 82% 87% 13% 58% 64% 68% 73% 78% 83% 88% 14% 59% 65% 69% 74% 79% 84% 89% 15% 60% 67% 70% 75% 80% 85% 90% 16% 61% 68% 71% 76% 81% 86% 91% 17% 62% 69% 72% 77% 82% 87% 92% 18% 63% 70% 73% 78% 83% 88% 93% 19% 64% 71% 74% 79% 84% 89% 94% 20% 65% 72% 75% 80% 85% 90% 95% 21% 66% 73% 76% 81% 86% 91% 95% 22% 67% 74% 77% 82% 87% 92% 95% 23% 68% 75% 78% 83% 88% 93% 95% 24% 69% 76% 79% 84% 89% 94% 95% 25% 70% 77% 80% 85% 90% 95% 95% 26% 71% 78% 81% 86% 91% 95% 95% 27% 72% 79% 82% 87% 92% 95% 95% 28% 73% 80% 83% 88% 93% 95% 95% 29% 74% 81% 84% 89% 94% 95% 95% 30% 75% 82% 85% 90% 95% 95% 95% 31% 76% 83% 86% 91% 95% 95% 95% 32% 77% 84% 87% 92% 95% 95% 95% Rate (%/hr) Changes on CS over Time CHO:B1 Kd Sept Oct Nov Dec Jan Feb March Estimated Starch Ruminal Fermentability Rates Microns > 2,725 2, % < 800 Coarse Med Fine Moisture Fall/Winter RATES 18% 10% 12% 14% 22% 12% 14% 16% 26% 14% 16% 18% 30% 18% 20% 22% Spring/Summer Color = kernel hardness: yellow = hard/vitreous, white = soft/floury Changing Corn CHO Rates If MP is too low; Starch (kd) Fermentability If MP is too High; Starch (kd) Fermentability If ME is too Low; Starch (ID) Escape Rate If ME is too High; Starch (ID) Escape Rate If Predicted Milk is High, Go Low Continue to Calibrate until: Get MP milk close ME reflects BW gain/loss ME is within 2 3 lbs of MP Your Gut says I am going too far Aka. More than a 4 5% change Call the Help Desk for more direction 16/20

17 Actual Milk Production and Components Reality Check Run Gas Analysis Corn is NOT Corn Watch the Cows! Calibrate the Cows Recalibrate, Things Change Schematic summary of nitrogen utilization by the ruminant. Source: Satter, Benefits of Balancing for Amino Acids Increased milk and milk protein production Reduced need for supplemental RUP More space in diet for other nutrients Reduced N excretion More predictable changes in milk and milk protein production to changes in RUP supply Increased profitability 17/20

18 Introduction to AA Formulation When EAA are absorbed in the profile that closely matches the animal s requirements, requirements for total EAA and total AA (EAA + NEAA) are reduced and their efficiency of use for protein synthesis is maximized Schwab s 5 steps for maximizing milk components and MP utilization through AA formulation 1. Feed a blend of forages, processed grains and byproduct feeds in a balanced ration that provides a blend of fermentable CHO formulating for a physically effective NDF that maximizes intake 2. Feed adequate but not excessive levels of RDP to meet rumen bacterial requirements for AA and NH3 Schwab s 5 steps for maximizing milk components and MP utilization through AA formulation 3. Feed high Lys protein supplements to achieve a targeted level of Lys in MP 4. Feed a rumen protected Met supplement in amounts needed to achieve the optimal ratio of Lys and Met in MP 5. Don t overfeed RUP Factors Affecting RUP Requirements 1. Quantity of MP provided by microbial protein 2. RUP digestibility 3. Amino acid composition of RUP, most importantly content of digestible Lys and Met Chemical composition and 2001 NRC evaluation of Conventional and New UNH diets (% of DM) Item Old diet New diet NDF CP RDP RUP RDP balance, g/d RUP balance, g/d MP balance, g/d Lys, % MP Met, % MP A Case Study - Applying the Principles of Balancing for LYS and MET and Including a Ruminal Source of HMB. Rations OLD NEW Milk (kg/day) 41.2 = 41.1 True Protein % Protein (kg/day) Fat % Fat (kg/day) Milk urea N Estimated Nutrient Composition - CP,RDP and RUP (% of DM), LYS and MET (% of MP) OLD CP, 10.8 RDP, 7.3 RUP, 6.37 LYS, 1.73 MET NEW CP, 10.6 RDP, 6.6 RUP, 6.55 LYS, 2.20 MET Schwab et al (unpublished) 18/20

19 Sloan thumb rules For each gm of Met added get 7 gm of milk protein Response is Increase in [ ] If add >5 gm of MP Met also expect an increase in BF of 0.1% For each gm of Lys increase expect 5 gm of Milk Prot ½ in increased [ ] ½ in increased yield Protein Summary The most efficient use of MP occurs when the profile of EAA in MP matches the profile as required by the cow Balancing diets for optimal Lys and Met in MP reduces requirements for RUP, increases milk and milk components, and improves health Balancing for AA in MP should always be part of ration formulation.. regardless of milk and feed prices (Schwab CNC 2009) Microbial Protein Near perfect Amino Acid profile. Can produce up to 3.9 lbs of protein/day! Cheap NH3 and Peptide sources to make. Need fcho to really drive the bus. CHO Bugs are 80% of what passes out of rumen CHO live only about 20 minutes. Digestible starch is the key b/c it ferments into propionic acid which makes more glucose in the liver than any other of the VFA s. Amino Acid Profiles Milk Bugs TMR Mix Methionine 2.7% 2.7% 2.7% Lysine 7.6% 8.2% 7.3% Arginine 3.4% 6.9% 2.0% Threonine 3.7% 5.5% 3.5% Leucine 9.2% 7.5% 7.7% Isoleucine 5.8% 5.9% 1.5% Valine 5.9% 6.2% 4.3% Histidine 2.7% 2.7% 4.4% Phenylalanine 4.8% 5.2% 6.4% Tryptophan 1.5% 1.6% 1.1% Microbial Protein Forage bugs are slower growing (2 3 days). More forage bugs than starch bugs in the rumen. Growth rate makes the difference. fndf drives Butterfat% fndf by products drives NFC bugs. NDFD is a great indicator how well the forage is going to feed. NDFD also controls rate of passage. Microbial Yield and Milk NFC FC Total Response hr for increase 10 d to 2 wk for increase Drop for 4 to 10 days then increase gradually 19/20

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