Use of of A nimal Animal B y By Products in Swine B. J. Kerr

Transcription

1 Use of Animal By Products in Swine Use of Animal By-Products in Swine B. J. Kerr

2 Introduction The cost of dietary energy, protein (amino acids), and phosphorus p is some of the highest recorded! Evaluate on a cost/unit of calorie, digestible amino acids, and digestible phosphorus. p Nutritionists must be able to assess and extract as much value as possible from feed ingredients. Take advantage of the variation. Variation is my friend! There are many factors related to utilizing animal fats and proteins in swine and poultry diets.

3 Obtaining the most value from rendered products Need more precision in formulating diets to meet nutrient requirements. Cost of overfeeding and underfeeding nutrients is high Overfeed-cost inefficiency, environmental waste Underfeed-performance reduction

4 Nutrient Requirements of Swine 1944, 11 pp 1998, 198 pp

5 Ideal Pattern of Amino Acids for Pigs NRC, to 20 kg 20 to 50 kg 50 to 100 kg Lys Thr Trp M+C Ile Val

6 Apparent Digestible Amino Acid Requirements LYS TRP THR ILE mg dig gestible aa/gr ram gain LYS THR ILE 4 TRP Body Weight, kg

7 Sources of Analytical Variation Sampling of the material to be analyzed Preparation of samples for analysis Methodological differences Technique differences among analysts Environment, reagent, equipment, and calibration differences among laboratories Errors in application or operation of methods Errors in calculating results

8 Terminology Accuracy the ability of a procedure to measure, or predict the true value (reference standards) (benzoic acid, bovine liver, glutamic acid, etc.) Precision the ability of a procedure to repeatedly provide the same result for a particular sample (corn, corn germ meal, cellulose, l etc.)

9 Nutrient Analysis Variability Among Labs Cromwell et al., 1999, 2000 / JAS 77:3262 & 78:2652 Dry matter: 0.8-Corn, 0.8-SBM, 1.1-Wheat midds Crude protein: 2.1-Corn, 1.8-SBM, 4.5-Wheat midds Phosphorus: 7.7-Corn, 3.5-SBM, 9.2-wheat midds NDF: 6.3-Wheat midds Variability Over Time Corn: DM-0.5, CP-2.9, P-6.6 SBM: DM-0.4, CP-0.8, P-5.3

10 Crude Fat, Poultry Meal (as-is) Fat, % (as s-is) Crude ARS, IA MN IL Eurofins, DSM ESCL, MO MVTL, MN

11 Lab Variation, Poultry Meal (as-is) ARS IA Eurofins DSM ESCL MO MVTL MN Dry Matter Ash Crude Protein NDF Crude Fat

12 Energy Prediction Equations ME = 6,982 + (0.283 GE, kcal/kg) (6.26 CP,,g/kg) g) (3.75 CFat, g/kg) + ( P, g/kg) (54.91 Ca, g/kg) (6.57 Ash, g/kg) [R 2 = 0.61, SD = 376] Adedukun and Adeola, 2005 / JAS 83:2519 ME = 13,587 (1.25 GE, kcal/kg) (3.51 CP, g/kg) +(304 P (30.4 P, g/kg) - (16.4 Ash, g/kg) [R 2 = 0.41, SD = NP] Olukosi and Adeola, 2009 / JAS 87:2590

13 Lab Variation DDGS (as-is) ARS IA Eurofins DSM ESCL MO MVTL MN DM ASH CP NDF EE

14 ME Estimation of DDGS from Ingredient Analysis ME = 3,996 + ( CP) ( NDF) + ( EE) ( Ash) [Anderson et al., 2012/JAS] ARS Eurofins ESCL MVTL

15 Major Rendered Products Meat meal, meat & bone meal, steamed bone meal Poultry by-product meal, chicken meal, hydrolyzed feather meal Blood meal Spray dried blood cells, plasma protein Fish meal Animal fats Tallow, choice white grease, yellow grease Blended d animal proteins and lipids

16 Nutrient Composition (NRC 1998) Meat & bone meal Poultry by-product meal Blood meal, ring dried Total Available Total Available Total Available Crude protein Lysine Methionine Tryptophan Crude fat ME, kcal/kg 2,227 2,862 2,948 Ash Calcium Phosphorus

17 Amino Acid Content and Digestibility Lys Met Thr Trp Ile Val Jorgensen et al., 1984/JAS 58: Knabe et al., 1989 / JAS 67: Stein et al., 1999 / JAS 77:1169 Pigs Gestating sows Lactating sows M&B samples (composition and energy evaluation) Adedokun and Adeola, 2005/ JAS 83: M&B samples (composition and energy evaluation) Olukosi and Adeola, 2009/ JAS 87:2590

18 Variation in Nutrient Composition Relationship between Crude Protein and Phosphorus (426 samples) and between Crude Protein and Lysine (73 samples) in Meat and Meat & Bone Meal (Knabe, 1995) Establish a central laboratory for compositional and quality analysis. E.g. AAFCO Check Sample Program Develop fast, accurate, inexpensive tools to manage (take advantage of) nutrient value variability. Energy, amino acids, and phosphorus Potential of NIR to predict measures of quality and composition Prediction equations and in vitro lab procedures to estimate digestibility

19 Feed Intake Relative to Amino Acid Intake Feed Intake Compar red to FI at Re quirement Ile Val Lys Thr Trp Relative Percent of Am ino Acid Requirem ent

20 4000 Validation of an Ile-deficient diet (5% SDBC) for late- finishing (90 kg) pigs Parr et al., 2003 / JAS 82: ADG, g ADFI, GF, g/kg C-SBM Neg. Cont. NC + Ile Total Ile 0.55% NRC rqt 0.33% Total Ile 0.25% Total Ile 0.49%

21 Growth Performance kg (5 reps with 4 pigs per pen) [Dean et al., 2005/ JAS 83:2543] C-SBM C+5%BC+Ile SEM ADG, g ADFI, kg G:F, g:kg The high Ile requirement estimate using RBC may be a function of the diet, and not the actual requirement in a C- SBM diets as the tidile requirement in a corn-sbm diet for kg barrows does not seem to be greater than 0.24%. [Estimated tidile:lys in RBC is 62, in C-SBM 55, Fu et al., 2005]

22 Energy of lipids in swine (NRC, 1998) DE values were calculated (Powles et al., 1995): DE (kcal/kg) = ( (0.005 FFA) (7.330 e x U:S )/4.184 Where FFA = free fatty acid content in g/kg U:S = ratio of unsaturated to saturated fatty acids FFA concentrations of all fats were assumed to be 50 g/kg (5%) (% FFA have been reported to range from 1.6 to 19.1% in tallow, 2.6 to 61.0% in AV blends) ME content was calculated as 96% of DE NE content was calculated (Ewan, 1989): NE = (0.599 ME) (15 %Ash) (30 %ADF)

23 U:S Ratio and FFA on Energy Value Wiseman et al., 1998 Low FFA High FFA Increase unsaturation = increased energy value. Increase FFA, decreased energy value. Largest impact in young birds, least in older pigs. Main effect is on lipid digestibility, not utilization.

24 Assessing fat quality Currently used traditional i tests MIU Moisture, insoluble, unsaponifiable Peroxide value Formation of primary lipid oxidation products Fatty acid profile Can be used to predict Iodine Value Can be used to predict Unsaturated:Saturated Ratio FFA Indicator of frying oil degradation. Titer T t t hi h f t lidifi Temperature at which fat solidifies. Color?

25 Other measures of fat quality (oxidation)? Hexanal Terminal product of lipid oxidation Anisidine value Measures carbonyl groups of oxidized lipids TBARS (thiobarbituric reactive substances) Measures compounds similar to malonaldehyde Hydroxylated aldehydes 4-hydroxy hydroxy-2-nonenal (4-HNE) OSI (oxidation stability index) Prediction of oxidative stability

26 DE, kcal/kg (Powles Lipid Quality Powles et al., 1995 / AS 61:149) 149) = (0.005 FFA, g/kg) (7.330 e Oxidation Potential U:S )/4.184 Composition (saturated vs unsaturated [18:2, linoleic]) Processing time and temperature (fats vs oils) Oxygen pressure, heavy metals, salts, water, etc

27 Lipid Peroxidation Lipid peroxidation a free radical chain reaction Free radical Lipid peroxidation products Chain cleavage Polymer Acid Ketone Aldehyde Lipid id hydroperoxide (Vickers et al., 2001)

28 Potential Effects of Dietary Oxidized Lipids Growth performance (feed intake) Rat (Nwanguma et al., 1999) Broiler (Wang et al., 1997) Pig (DeRouchey et al., 2004; Fernandez-Duenas et al., 2009; Harrell et al., 2010) Oxidative stress (Ringseis et al., 2006; Vazquez-Anon et al., 2008; Fernandez-Duenas et al., 2009; McGill et al., 2011) Immune responses? Intestinal integrity & gut barrier function?

29 Effect of Feeding Oxidized Corn Oil on Growth Performance of Pigs Nursery pigs (32d) Finishing pigs (56d) a a a a a Oxidized < Fresh (P < 0.05) a Oxidized < Fresh (P < 0.05) (Harrell et al., 2010) (Fernandez-Duenas et al., 2009)

30 PV and ethoxquin in healthy broilers PV = 0.01, A = 0.42, PV A = 0.96 PV = 0.75, A = 0.37, PV A = 0.72 AV blend 125 PPM 3%, 0-3 wk; 6%, 3-7 wk 8 reps w/ 30 birds/pen McGill et al., 2011 / IJPS 10:241 PV = 0.01, A = 0.49, PV A = 0.29

31 Endogenous Antioxidants superoxide dismutase, catalase, glutathionine peroxidase Natural selenium, Vitamin E Synthetic ethoxyquin, terbutylhidroqinone i (TBHQ), butylated hydroxytoluene (BHT), butylated hydroxyanisole (BHA)

32 Antioxidants in Animal Nutrition Fernandez-Duenas, 2009 / PhD. Thesis

33 What is the role of an antioxidant? Should antioxidants be added to sources of fats or fat containing feedstuffs for storage preservation? If so, under what conditions and at what cost? Should antioxidants be added to diets to reduce metabolic oxidation? If so, under what conditions and at what cost?

34 Phosphorus Huang and Allee, % bioavailability Traylor et al., % bioavailability Poulsen, % apparent digestibility Factors affecting availability Particle size slight increase from 6-mesh to 8-mesh Processing slight increase from 2.1 to 4.2 kg/cm 2 Ah Ash content t 15%U increase from low (porcine) to high h (bovine) ash content

35 Phosphorus Impact of DDGS on M&B s economic value of P Corn 0.28% P, 14% available = 0.04% Pa DDGS 0.61% P, 60% available = 0.37% Pa Kerr et al., 2010 impact of phytase on M&B s economic value of P? C-SBM diet P dig from 15 to 60% by using phytase

36 Rendered Products in Feed Formulations SBM DDGS M&B PM BC FM Corn SBM DDGS Meat & Bone Poultry meal Blood cells Feather meal Dical Limestone L-Lys-HClLys L-Thr DL-Met Other kcal ME/kg, 0.95%sidLys, TSAA:L, Thr:L, Trp:L, Ile:L, Val:L, 0.60%Ca, 0.25%aP

37 Other Comments Biosecurity relative to rendered trucks driving the same route where feed trucks deliver feed Adulteration Contamination with restricted use protein products from ruminants (dioxin) Inclusion of unhydrolyzed feather meal/hair (melamine) Raw material variability caused by blended products (source tracking/composition characteristics) Rapid composition & quality assessment? (NIR) Any functional/value added properties. Lower product nutrient variability/capitalize i on variability.

38 Final Comments Energy Amino Acids Phosphorus Lipid Quality Value Added Product Variability

39

40 Questions? I ll see if I can point you in the right direction!