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14 Ration Formulation and Evaluation The goal of feeding management is to provide nutrients intake. Optimal ranges of nutrient intake have been defined that efficiently maintain a horse’s body and well-being, and as levels between amounts that are marginally adequate or support functions related to growth, production, and work. deficient and upper levels that approach toxicities (Kronfeld, The process of formulation aligns types and amounts of 1998). feedstuffs with nutrient requirements and needs for feeding Horses have and continue to be fed a wide variety of management. Evaluation of rations allows for measurement feedstuffs with varying levels of processing. Many horses of how well the formulation process meets feeding manage- receive nutrition solely from forages. Others receive mixed ment goals. To be conducted correctly, ration formulation diets composed of concentrates, supplements, and forages. and evaluation requires knowledge of feedstuffs, feed man- Some consume complete mixes, which are processed to vi- ufacturing processes, feeding management practices, and sually resemble concentrates but contain nutrient profiles the nutritional requirements and physiology of the horse. more like mixed rations of concentrates and forages. Ration balancing involves mathematical procedures that One uniformly recommended guideline is for use of align nutrient composition of feedstuffs with nutrient and in- “high-quality” feedstuffs. Feeds should be free of irritants take needs of a horse. Methods range from simply account- that cause ill effects and supply a nutrient profile that is ing for nutrient profiles when combining certain feedstuffs aligned with requirements. Nutrients must be palatable and to methods that impose limits of use to certain feeds, costs, be safely fed through the intended feeding management rou- feeding plans, and manufacturing methods. Individuals with tine. Digestible feedstuffs increase the efficiency of use and limited experience in balancing rations or with limited decrease waste. Feed-related factors that affect the use of knowledge of nutritional science of horses are cautioned. specific ingredients include cost, availability, and palatabil- Mere mathematical manipulation of feedstuff nutrient val- ity. Horse and management-related factors include the ac- ues may fall short of effectively meeting dietary require- cess to growing forage, the need for energy-dense rations, ments. Successful diet formulation must take into account the use of the horse, and feeding management practices. feed palatability, feeding behavior, and physiology of horses Decisions to utilize specific feeds or feeding practices are and feeding management practices. also influenced by the decision maker’s previous experience with particular feeds or rations, current trends in feed manufacturing, and the effects of marketing on purchaser IDENTIFYING REQUIREMENTS AND preferences. SELECTION OF FEEDS Nutrient needs of horses within classes of production and DETERMINING THE NUTRIENT CONTENT OF FEEDS use vary because of individual differences in the ability to utilize feeds and differing responses to environmental and Methods used to estimate the nutritional value of feeds management conditions. These individual variations enforce include information from feed tags, nutrient databases, and the need to individually manage the feeding of horses, espe- nutrient analyses via testing laboratories. cially those with heightened requirements imposed by rapid The feed tag of commercially prepared feeds provides growth, heavy states of production, or intense work. Appli- minimum and maximum concentrations of certain nutrients. cation of nutrient requirements may vary between different Requirements for feed tags in the United States include sources of information, partially because some nutrients specified formats for listing product and brand names, in- may have wide ranges of what is considered to be optimal clusion statements of drugs, purpose and use statements, 280

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RATION FORMULATION AND EVALUATION 281 guarantees of limits to concentrations of certain nutrients, cautioned, as mere mathematical manipulation of feedstuff ingredient lists, directions for use, warning or caution state- nutrient values may fall short of effectively meeting the di- ments, quantity statements, and contact information for the etary requirements. manufacturer or person responsible for distributing the feed (AAFCO, 2005). Example A: Ration Evaluation Using Known Nutrient content of feedstuffs can also be estimated from Quantities of Two Feed Sources feed composition tables or databases. Most of these sources report average values of nutrient composition. Averages are Evaluate the nutrient profile of a ration containing 9 kg of of limited value when the nutrient composition of similarly forage and 1 kg of concentrate on an as-fed basis. Use the labeled feedstuffs is highly variable or if the average repre- nutrient compositions for forage and concentrate in Table sents a small number of samples. Variation is expected as 14-1 and the example estimates for nutrient requirements in nutrient content of feedstuffs is affected by agronomic prac- Table 14-2. tices, environmental influences, and feedstuff variety. Check the units of the nutrient composition analysis. Use of byproduct feeds has prompted reporting of nutri- These units will be listed on a dry matter (DM) or as-fed ent variability of these feedstuffs. Arosemena et al. (1995) basis. To convert as-fed to dry matter amounts, multiply the related the extent of nutrient variability of several byproduct amount of feedstuff on an as-fed basis by the dry matter per- feedstuffs to values listed in the Nutrient Requirements for centage of the feedstuff. To convert the amount on a dry Dairy Cattle (NRC, 2001). Comparison of average nutrients matter basis to the amount as fed, divide the amount of feed- of the analyzed byproduct feeds differed more than 20 per- stuff on a dry matter basis by the dry matter percentage of cent from values in the NRC (2001) table for most nutrients. the feedstuff. Largest variations within sources of the sampled feedstuffs In this example, the composition data are presented on a tended to be within mineral levels. Others have noted simi- dry matter basis. For accurate accounting, the amount fed lar variability in the composition between different sources must be converted to a dry matter basis, or the composition of byproduct feeds (DePeters et al., 2000) and differences in analysis must be converted to an as-fed basis. In this exam- nutrient composition reported by commercial laboratories ple, the amounts fed will be converted to a dry matter basis: compared to those reported in NRC feedstuff composition tables (Berger, 1996). 9 kg forage as fed × 89 percent dry matter = These reports reinforce the need to consider the potential 8.01 kg forage DM variability of the chemical composition of different sources 1 kg concentrate as fed × 90 percent dry matter = of all feedstuffs when using estimates from nutrient tables 0.9 kg concentrate DM and databases. The accuracy of use of values in nutrient databases is increased when sample sizes are large; when Calculate the amount of nutrients supplied in the ration specific information is known about agronomic practices, by multiplying the amounts of dry matter for each feed environmental influences, and manufacturing conditions; source by the nutrient concentration in that feed source. For and when the nutrient level variation between sources of the example, 8.01 kg DM forage × 9% crude protein = 0.721 feedstuff is low. kg × 1,000 g/kg = 721 g of crude protein. Calculate the total Nutrient content of feedstuffs can be determined by near amount of each nutrient of concern, and compare the infrared reflectance and various wet chemistry procedures amounts to the example nutrient requirements (Table 14-3). as described in Chapter 10. Testing can provide more accu- rate information on nutrient composition of a specific feed source as compared with other sources of information. TABLE 14-1 Feed Ingredient Nutrient Composition (dry matter basis) SAMPLE EXERCISES IN RATION FORMULATION DM CP Ca P AND EVALUATION (%) (%) (%) (%) Forage 89 9 0.3 0.2 There are numerous methods used to formulate and eval- Concentrate 90 10 0.5 0.4 uate rations, ranging from methods similar to these simple examples to more complex procedures that involve more nu- trients, have more controls, and require higher degrees of ac- TABLE 14-2 Example Estimates of curacy. To be conducted correctly, ration formulation and Nutrient Requirements evaluation require knowledge of feedstuffs, feed manufac- turing processes, routine feeding management practices, and Nutrient g/d the nutritional requirements and physiology of the horse. In- Crude protein 630 dividuals with limited experience in balancing rations or Calcium 20 with limited knowledge of nutritional science of horses are Phosphorus 14

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282 NUTRIENT REQUIREMENTS OF HORSES In this example, the level of crude protein, calcium, and In this example, the total intake (as fed) is estimated at phosphorus are above the estimated requirement when feed- 8.98 kg to meet the estimated digestible energy requirement ing 10 kg of total ration per day on an as-fed basis. of 16.7 Mcal per day. This level of intake is well below the example upper intake limit of 12 kg per day. As such, total intake should be consumable, thus allowing for further Example B: Ration Evaluation Using Predetermined evaluation. Forage to Concentrate Ratio Compare the nutrients provided by the forage and con- Evaluate the nutrient profile of a 90:10 (as-fed) forage to centrate with the estimated requirements. Once an estimated concentrate ratio, using the nutrient compositions for forage amount of total ration is determined, the amount of forage and concentrate in Table 14-4, and the upper intake limit and and concentrate can be determined by multiplying the total estimated requirements in Table 14-5. amount by the percent of feed source. In this example, for- The amount of ration is determined by meeting the esti- age is 90 percent and concentrate is 10 percent of the ration. mated digestible energy requirement. Amount of forage: 8.98 kg (0.90) = 8.08 kg Digestible Energy Density of a 90:10 Ratio of Amount of concentrate: 8.98 kg (0.10) = 0.90 kg Forage to Concentrate (energy density of forage × percent forage in ration) + Table 14-6 shows the total amount of crude protein (CP), (energy density of concentrate × calcium (Ca), and phosphorus (P) are higher than the exam- percent concentrate in ration) ple requirements when feeding this ration at levels to meet 1.7 Mcal/kg (0.90) + 3.3 Mcal/kg (0.10) = the estimated digestible energy requirement of 16.7 Mcal 1.86 Mcal DE per kg per day. If levels are unacceptable, the ratio of forage to con- centrate or feed sources should be altered to provide a lower Determine the amount needed to meet the estimated di- density of protein, calcium, and phosphorus in relation to gestible energy (DE) requirement using the energy concen- the density of digestible energy. tration of the combined forage and concentrate. Example C: Formulation of a Concentrate Amount of total ration: 16.7 Mcal DE ÷ 1.86 Mcal DE per kg = 8.98 kg Formulation methods were modified from procedures identified in Frape (1998) and Lewis (1995). The example uses a limited number of nutrients. Formulation methods for commercially prepared feed for horses will balance for spe- TABLE 14-3 Comparison of Nutrient Intake and cific energetic compounds, amino acids, vitamins, and addi- Estimated Requirements tional minerals. This example formulates a concentrate with the specifications listed in Table 14.7 from feedstuffs with DM Intake CP Ca P nutrient compositions provided in Table 14.8. kg (g) (g) (g) Determine the combination of grains needed to meet the Forage 8.01 721 24.0 16.0 targeted energy density of the concentrate. Note that if meet- Concentrate 0.90 90 4.5 3.6 Total 8.91 811 28.5 19.6 Requirement 630 20.0 14.0 TABLE 14-6 Comparison of Nutrient Intake and Estimated Requirements TABLE 14-4 Feed Ingredient Nutrient Composition (as-fed basis) Intake (as fed) DE CP Ca P DM DE CP Ca P (kg/d) (Mcal) (g) (g) (g) (%) (Mcal/kg) (%) (%) (%) Forage 8.08 13.7 889 24.2 16.2 Forage 89 1.7 11 0.3 0.2 Concentrate 0.90 3.0 108 5.4 3.6 Concentrate 90 3.3 12 0.6 0.4 Total ration 8.98 16.7 997 29.6 19.8 Requirement 16.7 630 20.0 14.0 TABLE 14-5 Example Intake Limit (as-fed basis) and Estimated Nutrient Requirements TABLE 14-7 Targeted Nutrient Concentration of the Example Concentrate (dry matter) Upper Intake Limit DE CP Ca P DE Intake CP Ca P (kg/d) (Mcal) (g) (g) (g) (Mcal/kg) (%) (%) (%) 12 16.7 630 20 14 Concentrate 3.5 14 0.5 0.4

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RATION FORMULATION AND EVALUATION 283 TABLE 14-8 Nutrient Composition of Feedstuffs (100% x = grain, 1 – x = protein supplement dry matter basis) 10.4x + 50(1 – x) = 14.5 DM DE CP Ca P 10.4x – 50x = –35.5 (%) (Mcal/kg) (%) (%) (%) –39.6x = –35.5 x = 89.6 Grain one 90 3.7 10 0.05 0.20 Grain two 90 3.2 12 0.09 0.38 Adjusting the ratio to a 90:10 grain mix to protein sup- Protein supplement 90 3.5 50 0.40 0.70 Mineral one 97 16.00 21.00 plement will slightly exceed the targeted crude protein den- Mineral two 97 39.00 sity of 14 percent. The subsequent nutrient densities are dis- played in Table 14-10. The totals indicate that digestible energy and crude protein are at or slightly above the targeted densities for the final concentrate. ing or exceeding the minimal energy density of the final mix Calcium and phosphorus are below the targeted densities is critical, solving for a slightly higher energy density may identified in Table 14-7. Solve for phosphorus first, as the be necessary to offset subsequent additions of ingredients available source of phosphorus, mineral one, also contains lower in energy density, i.e., minerals. Ensuring or exceeding calcium. minimal energy densities is most important when balancing x = grain mix with protein supplement, 1 – x = mineral one rations to be fed at intakes near maximal voluntary levels. In 0.29x + 21(1 – x) = 0.4 this example, the target energy density for the combination of 0.29x – 21x = –20.6 the two grains will be adjusted to 3.6 Mcal/kg DE. x = 0.995 Assign one of the grains a value of x, the other y which Adjusting the ratio to 99.4:0.6 grain mix with protein equals 1 – x, as x + y = 1. supplement to mineral, one will increase the level of phos- x = grain one, 1 – x = grain two phorus slightly above the targeted phosphorus density of the (Energy density of grain one)x + concentrate (Table 14-11). (Energy density of grain two)1 – x = The calcium density of the mixture is less than the tar- Target energy density geted level of the concentrate, so mineral two will need to be 3.7x + 3.2(1 – x) = 3.6 balanced into the mix. 3.7x + 3.2 – 3.2x = 3.6 0.5x = 0.4 x = grain mix, protein supplement and mineral one, x = 0.8 1 – x = mineral two 0.19x + 39(1 – x) = 0.5 A ratio of 80:20 of grain one to grain two would exceed 0.19x – 39x = –38.5 the targeted energy density of 3.5 Mcal/kg DE. The result- x = 0.992 ing nutrient densities for crude protein, calcium, and phos- phorus are calculated by summing the relative contributions TABLE 14-10 Comparison of the Grain Mix and Protein from each of the grains. For example, crude protein (%) = Supplement with the Targeted Nutrient Densities for the (10 × 0.8) + (12 × 0.2) = 10.4. The nutrient concentration of Concentrate the mix of grains one and two is presented in Table 14-9. % in DE CP Ca P Add feedstuffs that supply large concentrations of defi- mix (Mcal/kg) (%) (%) (%) cient nutrients starting with crude protein. Rounding up the Grain mix 90 3.24 9.36 0.05 0.22 percent crude protein needed for the final concentrate to Protein supplement 10 0.35 5.00 0.04 0.07 14.5 percent will assist with maintaining a minimal density Total 100 3.59 14.36 0.09 0.29 of crude protein as feedstuffs without protein are subse- Difference +0.09 +0.36 –0.41 –0.11 quently added. Balance the previously mixed grains with the protein supplement by methods similar to those used to bal- TABLE 14-11 Comparison of the Grain Mix, Protein ance energy density: Supplement, and Mineral One with the Targeted Nutrient Densities for the Concentrate % in DE CP Ca P TABLE 14-9 Nutrient Concentration of an 80:20 Mix of mix (Mcal/kg) (%) (%) (%) Grain One and Grain Two Grain mix 89.5 3.22 9.31 0.05 0.22 DE CP Ca P Protein supplement 9.9 0.35 4.95 0.04 0.07 (Mcal/kg) (%) (%) (%) Mineral one 0.6 0.00 0.00 0.10 0.13 Total 100.0 3.57 14.26 0.19 0.42 Grain mix 3.6 10.4 0.06 0.24 Difference +0.07 +0.26 –0.31 +0.02

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284 NUTRIENT REQUIREMENTS OF HORSES A ratio of 99.2:0.8 grain with protein supplement and TABLE 14-13 Formulated Concentrate Constituents on a mineral one to mineral two will increase the calcium density Dry Matter and As-Fed Basis to the targeted level of the concentrate. The comparison of Feedstuff % Dry Matter % As-Fed the final formulation to the targeted nutrient densities of the Grain one 71.0 70.9 concentrate are presented in Table 14-12. Grain two 17.8 17.8 If values are acceptable, the final step is to convert the Protein supplement 9.8 9.8 percentage contribution of feedstuffs in the concentrate from Mineral one 0.6 0.6 a dry matter to an as-fed basis. First, obtain an overall dry Mineral two 0.8 0.9 matter for the concentrate mix by summing the products of Total 100.0 100.0 each feedstuff’s contribution on a dry matter basis (Table 14-12) and its percent dry matter (Table 14-8): Concen- REFERENCES Protein Mineral Mineral trate Grain one Grain two Supplement one two % DM AAFCO (Association of American Feed Control Officials, Inc.). 2005. Of- (71.0 × 0.90) + (17.8 × 0.90) + (9.8 × 0.90) + (0.6 × 0.97) + (0.8 × 0.97) = 90.1 ficial Publication. Oxford, IN: Association of American Feed Control Officials. Arosemena, A., E. J. DePeters, and J. G. Fadel. 1995. Extent of variability Multiply the percentage contribution of each feedstuff on in nutrient composition within selected by-product feedstuffs. Anim. a dry matter basis by the ratio of its percent dry matter to Feed Sci. Technol. 54:103–120. percent dry matter of the concentrate to obtain the contribu- Berger, L. L. 1996. Variation in the trace mineral content of feedstuffs. Prof. tion on an as-fed basis (Table 14-13): Anim. Scientist 12:1–5. DePeters, E. J., J. G. Fadel, M. J. Arana, N. Ohanesian, M. A. Etchebarne, C. A. Hamilton, R. G. Hinders, M. D. Maloney, C. A. Old, T. J. Rior- Grain one 71.0 × (90/90.1) = 70.9 dan, H. Perez-Monti, and J. W. Pareas. 2000. Variability in the chemi- Grain two 17.8 × (90/90.1) = 17.8 cal composition of seventeen selected by-product feedstuffs used by the Protein supplement 9.8 × (90/90.1) = 9.8 California dairy industry. Prof. Anim. Scientist 16:69–99. Mineral one 0.6 × (97/90.1) = 0.6 Frape, D. 1998. Equine Nutrition and Feeding, 2nd ed. Malden, MA: Mineral two 0.8 × (97/90.1) = 0.9 Blackwell Science. Kronfeld, D. 1998. A practical method for ration evaluation and diet for- mulation: an introduction to sensitivity analysis. Pp. 77–88 in Advances in Equine Nutrition, vol. II. Lexington: Kentucky Equine Research. TABLE 14-12 Comparison of the Final Formulation with Lewis, L. D. 1995. Equine Clinical Nutrition: Feeding and Care. Media, the Targeted Nutrient Densities for the Concentrate PA: Williams & Wilkins. NRC (National Research Council). 2001. Nutrient Requirements of Dairy % DE CP Ca P Cattle, 7th rev. ed. Washington, DC: National Academy Press. in mix (Mcal/kg) (%) (%) (%) Grain mix 88.8 3.20 9.23 0.05 0.21 Grain one 71.0 2.63 7.10 0.03 0.14 Grain two 17.8 0.57 2.13 0.02 0.07 Protein supplement 9.8 0.34 4.90 0.04 0.07 Mineral one 0.6 0.00 0.0 0.10 0.13 Mineral two 0.8 0.00 0.0 0.31 0.00 Total 100.0 3.54 14.13 0.50 0.41 Difference +0.04 +0.13 +0.00 +0.01