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Review: Advantages and limitations of dairy efficiency measures and the effects of nutrition and feeding management interventions

      ABSTRACT

      Economists, nutritionists, and geneticists have attempted to describe dairy cattle efficiency in simple, quantifiable terms. On-farm measures of dairy efficiency include physical feed efficiency, efficiency of nutrient usage, economic feed efficiency, total dairy enterprise efficiency, and lifetime efficiency. Each calculated measure of dairy efficiency has its own advantages and limitations. Each measure has merit for describing a segment of dairy efficiency, yet no one measure can sufficiently describe dairy efficiency or be applicable across all farms. Use of multiple dairy efficiency metrics, each with a moving target specific to the individual dairy enterprise, should be considered. Nutrition and nutrient management interventions can improve the use of dairy resources, increasing both economic and environmental sustainability. With greater DMI and milk yield, a smaller proportion of dietary nutrients are used for maintenance functions, improving productive efficiency and reducing the environmental impact of the dairy cow. Nutritional factors independent of cow genetic merit affect energetic losses in the form of feces, heat of digestion and metabolism, or methane. Improvements in nutrient retention can occur with increases in rate of digestion and decreases in rate of passage of feed ingredients. Forage and grain losses, feed ingredient options, and forage and feed ingredient targeting according to cow potential need to be considered. Consistency of delivery and consumption of the formulated ration without high feed refusal rates typically improves dairy efficiency. Cow grouping affects social behavior, cow well-being, nutrient wastage, milk yield, and expenses, with optimum strategies being farm specific.

      Key words

      INTRODUCTION

      Sustainable dairy production must return a profit for the dairy enterprise and produce quality milk for consumers while maintaining optimal cow well-being and practicing environmental stewardship (
      • von Keyserlingk M.A.G.
      • Martin N.P.
      • Kebreab E.
      • Knowlton K.F.
      • Grant R.J.
      • Stephenson II, M.
      • Sniffen C.J.
      • Harner III, J.P.
      • Wright A.D.
      • Smith S.I.
      Invited Review: Sustainability of the US dairy industry.
      ). Feed typically accounts for 50 to 60% of the operating expenses on a dairy farm, making it a logical focal point when trying to increase efficiency (
      • Knoblauch W.A.
      • Putnam L.D.
      • Karszes J.
      • Overton R.
      • Dymond C.
      Dairy Farm Management Business Summary, New York State, 2011.
      ). Yet, high milk production, which requires proper nutrition, typically generates more profit than low feed cost (
      • Dunklee J.S.
      • Freeman A.E.
      • Kelley D.H.
      Comparison of Holsteins selected for high and average milk production. 1. Net income and production response to selection for milk.
      ;
      • VandeHaar M.J.
      • St-Pierre N.
      Major advances in nutrition: Relevance to the sustainability of the dairy industry.
      ). The economic objective of the farm is generally to maximize net economic returns while converting a greater percentage of feed nutrients into milk with little nutrient wastage. Fortunately,
      • Place S.E.
      • Mitloehner F.M.
      Invited review: Contemporary environmental issues: A review of the dairy industry’s role in climate change and air quality and the potential of mitigation through improved production efficiency.
      concluded that increasing productive efficiency also results in fewer air emissions per unit of milk.
      In today’s marketplace, sustainability is a new indicator of quality. It can be tempting to use dairy efficiency metrics to address consumer and retailer questions about sustainability. However, although each measure has merit for describing a segment of dairy efficiency, no one measure can entirely describe a dairy’s efficiency or be applicable across all farms. Each calculated measure of dairy efficiency has its own advantages and limitations. Dairy efficiency goals should be considered to be moving targets that are specific for the current situation of individual dairy enterprises with the focus placed on continuous progress. The objectives of this review are to discuss the advantages and limitations of current measures of dairy efficiency and to describe the effects of nutrition and feeding management on dairy efficiency regardless of genotype. Actions that herd managers and nutritionists can immediately implement to increase dairy efficiency in their operations are discussed.

      REVIEW AND DISCUSSION

      Dairy Efficiency Measures—Description, Advantages, and Limitations

      Physical Feed Efficiency

      The most well-known and used measure of dairy efficiency is the amount of milk produced, expressed as 3.5% FCM, 4% FCM, or energy-corrected milk, per unit of DMI or “physical feed efficiency” (physical FE). This is a measure of gross feeding efficiency calculated as the ratio of total outputs divided by total inputs (Table 1). Physical FE indicates whether cows are digesting their ration according to expectations (
      • St-Pierre N.
      Managing measures of feed costs: Benchmarking physical and economic feed efficiency.
      ) and influences both environmental and economic outcomes.
      Table 1Advantages and limitations of various dairy and feed efficiency measures
      MeasureAbbreviationCalculationAdvantagesLimitations
      Physical feed efficiencyPhysical FEFCM or energy-corrected milk/DMIIndicates digestibilityIgnores nutrient density, cost, and body reserves
      Energy conversion efficiencyECEMilk energy/ME intakeConsiders diverse nutrient efficienciesIgnores body reserves
      Residual energy intakeREIME intake − Energy requirementLess influence of body reservesRelies on prediction of energy requirements
      Ration cost efficiencyFEvcFiscal milk value/Fiscal DMI valueReflects profitsIgnores body reserves
      Feed cost per hundredweight (45.4 kg)Feed cost/cwtFarm feed cost/45.4 kg of milk shippedIncludes cost of dry period and reproductive efficiencyIgnores heifer costs and fiscal value of milk
      Milk income over feed costIOFCMilk income − Feed costsHelpful for short-term feeding decisionsDependent on feed costs and milk value
      Lifetime efficiencyEnergy in lifetime milk, conceptus, and body/Lifetime GE intakeIncludes heifer, reproductive, and longevity efficienciesDifficult to calculate for individual farms
      The simplicity of calculating physical FE as FCM/DMI incurs numerous limitations (Table 1). First, physical FE does not consider body tissue accretion and mobilization, the implication being that physical FE changes with DIM. Maximum physical FE occurs in early lactation when cows are in negative energy balance and mobilizing body tissue to support milk production. As lactation progresses, physical FE declines exponentially over the first 3 mo and eventually linearly until lactation finishes (
      • St-Pierre N.
      Managing measures of feed costs: Benchmarking physical and economic feed efficiency.
      ). Based on field experience,
      • Hutjens M.F.
      Dairy efficiency and dry matter intake.
      suggested goals for physical FE (3.5% FCM/DMI) as 1.6 to 1.8 for multiparous cows <90 DIM, 1.3 to 1.4 for multiparous cows >200 DIM, and 1.4 to 1.6 as a mean for all cows between 150 to 225 DIM.
      • Erdman R.
      Monitoring feed efficiency in dairy cows using fat-corrected milk per unit of dry matter intake.
      suggested assessment of 150-d physical FE to correct for the effects of DIM and evaluate nutrition and management changes on a dairy in year-on-year comparisons.
      It is evident that physical FE as a benchmark for sustainable milk production has numerous limitations, making it necessary to evaluate other economic and efficiency measures concurrently. Primiparous heifers still using nutrients for growth will present lower physical FE values than mature cows (
      • Hutjens M.F.
      Dairy efficiency and dry matter intake.
      ). Physical FE also ignores environmental stressors such as heat or cold that depress efficiency (
      • Britt J.S.
      • Thomas R.C.
      • Speer N.C.
      • Hall M.B.
      Efficiency of converting nutrient dry matter to milk in Holstein herds.
      ;
      • Hutjens M.F.
      Dairy efficiency and dry matter intake.
      ). Physical FE gives no consideration to nutrient density and nutrient profile. For example, increasing dietary fat increases dietary energy density, also increasing physical FE by 0.03 to 0.10 units per percentage unit of fat addition (
      • Erdman R.
      Monitoring feed efficiency in dairy cows using fat-corrected milk per unit of dry matter intake.
      ). Typically, supplemental dietary fat is more costly than other energy sources. Protein quality and cost play a role in dairy efficiency but are not considered with FCM/DMI. With ideal rumen function, digestion, and microbial protein synthesis, RDP can make up a greater proportion of dietary protein, reducing the need for RUP, which is typically more expensive. Grain and forage lost from shrink and feeding refusals are not considered in physical FE either but greatly influence environmental and economic outcomes.

      Efficiency of Nutrient Usage

      Efficiency of use of individual dietary nutrients may not be similar (
      • Armentano L.
      • Weigel K.
      Considerations for improving feed efficiency in dairy cattle.
      ), and calculation of separate nutrient efficiencies such as energetic efficiency and N efficiency can be valuable. Gross nutrient efficiencies, based on the amount of nutrient consumed, are typically calculated. Digestive efficiencies can be informative for comparing genotypes but can also be useful for nutritionists and environmentalists if fecal nutrient losses are separately accounted (
      • Owens C.E.
      • Zinn R.A.
      • Hassen A.
      • Owens F.N.
      Mathematical linkage of total-tract digestion of starch and neutral detergent fiber to their fecal concentrations and the effect of site of starch digestion on extent of digestion and energetic efficiency of cattle.
      ). Differences in metabolic efficiency suggest divergence in nutrient partitioning between milk production and other nutrient uses such as body tissue accretion. Thus, metabolic efficiency is used more by geneticists rather than by nutritionists or environmentalists (
      • Phuong H.N.
      • Friggens N.C.
      • de Boer I.J.M.
      • Schmidely P.
      Factors affecting energy and nitrogen efficiency of dairy cows: A meta-analysis.
      ).
      Energy conversion efficiency is calculated as milk energy output divided by ME intake (Table 1). Unfortunately, as with physical FE, energy conversion efficiency will be improved with greater mobilization of body reserves (early lactation) and reduced during body tissue accretion (late lactation). Because of the negative effects of body reserve loss on reproduction and health, greater energy conversion efficiency is not always desirable. Residual energy intake (REI) is actual ME intake minus the predicted energy requirement of the cow based on production, BW, BW change, and gestational energy needs (
      • Mantysaari P.
      • Liinamo A.-E.
      • Mantysaari E.A.
      Energy efficiency and its relationship with milk, body, and intake traits and energy status among primiparous Nordic Red dairy cattle.
      ; Table 1). Because BW changes are predicted and accounted for, REI is influenced less by body reserve loss and gain. A reduced REI indicates that less energy is wasted after accounting for the energy in milk, maintenance, and growth and that efficiency of energy use is improved.
      • Mantysaari P.
      • Liinamo A.-E.
      • Mantysaari E.A.
      Energy efficiency and its relationship with milk, body, and intake traits and energy status among primiparous Nordic Red dairy cattle.
      concluded that stage of lactation affected REI among Nordic Red cows. This relationship could be due to true energetic efficiency differences during the lactation or to inadequate assessment of changes in body reserves affecting calculated REI.

      Economic Feed Efficiency

      As measures of physical FE increase, economic profitability typically increases, but this positive association is not always true (
      • St-Pierre N.
      Formulating rations based on changes in markets.
      ).
      • Robinson P.H.
      • Erasmus L.J.
      Feed efficiency and lactating cows: Expressing and interpreting it.
      demonstrated that greater DMI and milk yield are typically more profitable than a similar physical FE ratio with reduced DMI and milk yield. Because dairy sustainability also requires dairy profitability, calculation and evaluation of economic efficiency is prudent. Ration cost efficiency is the fiscal value of milk divided by the fiscal cost of consumed DM (
      • Robinson P.H.
      • Erasmus L.J.
      Feed efficiency and lactating cows: Expressing and interpreting it.
      ; Table 1). Unfortunately, ration cost efficiency does not account for BW changes, heifer growth, health, longevity, forage DM losses, feed refusals, and feed shrink.
      Feed cost per hundredweight (45.4 kg) is calculated as the accumulated feed cost for lactating and dry cows divided by the amount of milk (hundredweight) shipped (Table 1). Feed price, feed refusals, feed shrink, dry period length, reproduction, and herd health all affect feed cost per hundredweight; however, the heifer enterprise and milk composition are not considered (
      • Bethard G.
      Controlling feed costs: Focusing on margins instead of ratios.
      ).
      • St-Pierre N.
      Formulating rations based on changes in markets.
      argued against the objective of minimizing feed cost per hundredweight of milk but rather supported a system of accurate nutrient value estimation based on market prices of many feed ingredients and optimization of feed resources and production.
      Milk income over feed cost (IOFC) is a calculated margin that has been used for decades (Table 1). Use of IOFC is helpful for short-term feeding and management decisions, but it is not recommended for long-term herd performance assessment because it is dependent on fluctuating milk and feed prices (
      • Bethard G.
      Controlling feed costs: Focusing on margins instead of ratios.
      ). Calculated IOFC may or may not include costs of feed shrink, feed refusals, cow health, dry cow management, or heifers. A survey of 95 Pennsylvania dairy herds from 2009 to 2012 determined a mean IOFC of $7.71, ranging from −$0.33 to $16.60 (
      • Buza M.H.
      • Holden L.A.
      • White R.A.
      • Ishler V.A.
      Evaluating the effect of ration composition on income over feed cost and milk yield.
      ). Improved nutrition and milk yield positively affected IOFC more than reduced feed cost. Money Corrected Milk (
      • Bethard G.
      Controlling feed costs: Focusing on margins instead of ratios.
      ) calculates milk prices in the same way as milk processors, with fixed feed and milk component prices over time, to more accurately reflect herd performance over time. This measure is an improvement over IOFC yet still does not include costs of feed shrink, feed refusals, cow health, dry cow management, or heifers.

      Lifetime Efficiency

      Lifetime efficiency is the percentage of lifetime feed energy (GE) intake converted into milk, conceptus, and body tissues (
      • VandeHaar M.J.
      • St-Pierre N.
      Major advances in nutrition: Relevance to the sustainability of the dairy industry.
      ; Table 1). Obviously, earlier and more efficient calf and heifer growth and greater longevity generally equate to improved lifetime efficiency. It was calculated that a cow producing 9,000 kg of milk/yr at maturity would have a lifetime efficiency of 17% after the first lactation and 20.5% after the third lactation, only increasing to 21.4% after the fifth lactation (
      • VandeHaar M.J.
      • St-Pierre N.
      Major advances in nutrition: Relevance to the sustainability of the dairy industry.
      ).

      Total Dairy Enterprise Efficiency

      To accurately describe the efficiency of a dairy enterprise, all nutrient losses and gains need to be accounted for. This includes nutrient losses associated with crops, manure, feeding management and reproductive inefficiency, feed nutrients required for replacement heifers and dry cows, and the value of animals sold for beef or other purposes. Integration of accurate farm data including actual DM and nutrient intakes with advanced nutrition models such as the
      • NRC
      Nutrient Requirements of Dairy Cattle.
      , Molly model (
      • Baldwin R.L.
      • France J.
      • Beever D.E.
      • Gill M.
      • Thornley J.H.
      Metabolism of the lactating cow. III. Properties of mechanistic models suitable for evaluation of energetic relationships and factors involved in the partition of nutrients.
      ), or Cornell Net Carbohydrate and Protein System (
      • Sniffen C.J.
      • O’Connor J.D.
      • Van Soest P.J.
      • Fox D.G.
      • Russell J.B.
      A net carbohydrate and protein system for evaluating cattle diets: II. Carbohydrate and protein availability.
      ;
      • Higgs R.J.
      • Chase L.E.
      • Ross D.A.
      • Van Amburgh M.E.
      Updating the Cornell Net Carbohydrate and Protein System feed library and analyzing model sensitivity to feed inputs.
      ;
      • Van Amburgh M.E.
      • Collao-Saenz E.A.
      • Higgs R.J.
      • Ross D.A.
      • Recktenwald E.B.
      • Raffrenato E.
      • Chase L.E.
      • Overton T.R.
      • Mills J.K.
      • Foskolos A.
      The Cornell Net Carbohydrate and Protein System: Updates to the model and evaluation of version 6.5.
      ) and whole-farm dairy models such as DairyWise (
      • Schils R.L.M.
      • de Haan M.H.A.
      • Hemmer J.G.A.
      • van den Pol-van Dasselaar A.
      • de Boer J.A.
      • Evers A.G.
      • Holshof G.
      • van Middelkoop J.C.
      • Zom R.L.G.
      DairyWise, a whole-farm dairy model.
      ) and the Integrated Farm Systems Model (
      • Rotz C.A.
      • Corson M.S.
      • Chianese D.S.
      • Montes F.
      • Hafner S.D.
      • Coiner C.U.
      The Integrated Farm System Model.
      ) could help to more accurately calculate actual total dairy enterprise efficiencies.

      Nutritional Factors Related to Dairy Efficiency

      With greater milk yield, a smaller proportion of dietary nutrients are used for maintenance functions. This “dilution of maintenance” has been the primary source of increased productive efficiency on commercial dairies for the last century. For example, a Holstein cow producing 45 kg of milk/d needs 4 times as much energy as that needed for maintenance, whereas a Holstein cow producing 90 kg/d requires 7 times as much (
      • VandeHaar M.J.
      • St-Pierre N.
      Major advances in nutrition: Relevance to the sustainability of the dairy industry.
      ). Improved milk production also has been a major contributor to the reduced environmental impact of the dairy industry over the last century (
      • Capper J.L.
      • Bauman D.E.
      The role of productivity in improving the environmental sustainability of ruminant production systems.
      ).
      Physiological state, physical and chemical aspects of the diet, psychogenic factors, and environment influence dairy cow meal size and frequency (
      • Allen M.S.
      • Bradford B.J.
      • Oba M.
      The hepatic oxidation theory of the control of feed intake and its application to ruminants.
      ). If cows consume less DM and maintain milk yield, physical FE will improve. However, with greater on-farm DMI, diets can be reformulated so that required nutrients can be provided with reduced diet nutrient density, often promoting rumen health, reducing supplemental fat needs, and increasing economic FE if ration cost per kilogram is reduced. It must be recognized, however, that increased DMI can also promote feed passage, increasing fecal losses and reducing digestive efficiency to some degree (
      • Tyrrell H.F.
      • Moe P.W.
      Effect of intake on digestive efficiency.
      ).
      Maximum energetic efficiency in the dairy cow equates to minimal energy loss. Opportunities exist on many dairies for improving dairy efficiency with dietary changes that reduce energy losses (Table 2). Only about 24 to 33% of GE consumed by the cow is actually used for productive purposes (NEl;
      • Moe P.W.
      • Flatt W.P.
      • Tyrrell H.F.
      Net energy value of feeds for lactation.
      ;
      • Weiss W.P.
      Refining the net energy system.
      ). Energy losses as methane have been estimated at 3.7 to 10.1% of GE intake (
      • Yan T.
      • Agnew R.E.
      • Gordon F.J.
      • Porter M.G.
      The prediction of methane energy output in dairy and beef cattle offered grass silage-based diets.
      ). An evaluation of 20 energy metabolism studies with 579 lactating dairy cows concluded that high milk yield and high energetic efficiency reduce methane energy losses as a proportion of energy intake (
      • Yan T.
      • Mayne C.S.
      • Gordon F.G.
      • Porter M.G.
      • Agnew R.E.
      • Patterson D.C.
      • Ferris C.P.
      • Kilpatrick D.J.
      Mitigation of enteric methane emissions through improving efficiency of energy utilization and productivity in lactating dairy cows.
      ).
      Table 2Effect of nutrition and feeding management factors on dairy efficiency measures with considerations for nutritionists and dairy managers
      FactorDairy efficiency measures affected and considerations
      FE = feed efficiency; FEvc = ration cost efficiency; cwt = hundredweight (45.4 kg); IOFC = milk income over feed cost; ECE = energy conversion efficiency.
      DMIGreater DMI with increased milk yield may improve all efficiency measures. Reduced DMI with no change in milk yield may improve all efficiency measures. Greater DMI with reduced cost per unit of DMI can decrease physical FE but improve FEvc, feed cost/cwt, and IOFC.
      Fiber digestibilityGreater fiber digestibility may increase milk yield, reduce fecal losses, and improve all efficiency measures, but a portion of the effect can be negated by increased DMI.
      Starch digestibilityGreater starch digestibility may increase milk yield, reduce fecal losses, and improve all efficiency measures; however, economic costs of grain processing and silage storage need consideration.
      Added dietary fatIncreased dietary fat may improve physical FE while reducing FEvc and IOFC and increasing feed cost/cwt.
      Feed additivesFeed additives may improve rumen health and digestion, reduce methane losses, increase milk yield, and improve all efficiency measures.
      By-product feedsPurchased commodity by-product feeds can reduce feed expenses, improving FEvc, feed cost/cwt, and IOFC but not physical FE, ECE, or lifetime efficiency.
      Rumen functionImproved rumen function may increase digestibility, reduce fecal loss, increase rumen microbial protein yield, and improve all efficiency measures.
      Precision feedingProvision of optimal diets to all cows based on DIM, potential production, ingredient prices, and predicted variation in parameters may improve all efficiency measures.
      Feed storage losses and refusalsFewer feed storage losses and refusals can decrease feed cost/cwt and increase IOFC without affecting FEvc, physical FE, ECE, or lifetime efficiency.
      Methane lossesReduced methane losses can improve all efficiency measures.
      Cow comfort and feeding behaviorEnhanced cow comfort and feeding behavior can optimize rumen health and digestion, increase milk yield, and improve all efficiency measures.
      Milk compositionGreater milk component percentage can improve physical FE, ECE, FEvc, IOFC, and lifetime efficiency without affecting feed cost/cwt.
      Heifer growthImproved rates of gain in heifers resulting in reduced age at first calving can increase lifetime efficiency without affecting other efficiency measures.
      Dry period lengthReduced days dry can decrease feed cost/cwt, increase IOFC, and increase lifetime efficiency without affecting physical FE, ECE, or FEvc.
      1 FE = feed efficiency; FEvc = ration cost efficiency; cwt = hundredweight (45.4 kg); IOFC = milk income over feed cost; ECE = energy conversion efficiency.
      High efficiency of feed usage in the dairy cow requires maximum fiber and starch digestibility and minimal fecal excretion of energetic nutrients. Improved fiber digestibility potentially reduces fecal losses and increases milk yield (
      • Oba M.
      • Allen M.S.
      Effects of brown midrib 3 mutation in corn silage on productivity of dairy cows fed two concentrations of dietary neutral detergent fiber. 1. Feeding behavior and nutrient utilization.
      ;
      • Kendall C.
      • Leonardi C.
      • Hoffman P.C.
      • Combs D.K.
      Intake and milk production of cows fed diets that differed in dietary neutral detergent fiber and neutral detergent fiber digestibility.
      ). Yet, depending on other dietary ingredients, improvements in forage fiber digestibility may increase DMI and rate of passage, negating a portion of the benefits provided by increased digestibility (
      • Tine M.A.
      • McLeod K.R.
      • Erdman R.A.
      • Baldwin VI, R.L.
      Effects of brown midrib corn silage on the energy balance of dairy cattle.
      ).
      Grain type, endosperm type, maturity, DM, and particle size influence total-tract starch digestion, ranging from 70 to 100% (
      • Firkins J.L.
      • Eastridge M.L.
      • St-Pierre N.R.
      • Noftsger S.M.
      Effects of grain variability and processing on starch utilization by lactating dairy cattle.
      ). Degradation of zein proteins during ensiling increased starch digestibility in high-moisture corn (
      • Hoffman P.C.
      • Esser N.M.
      • Shaver R.D.
      • Coblentz W.K.
      • Scott M.P.
      • Bodnar A.L.
      • Schmidt R.J.
      • Charley R.C.
      Influence of ensiling time and inoculation on alteration of the starch-protein matrix in high-moisture corn.
      ). Kernel processing of corn silage improves starch digestibility, especially with more mature corn plants (two-thirds milkline or black layer;
      • Johnson L.M.
      • Harrison J.H.
      • Davidson D.
      • Hunt C.
      • Mahanna W.C.
      • Shinners K.
      Corn silage management: Effects of hybrid, maturity, chop length, and mechanical processing on rate and extent of digestion.
      ). Rumen starch digestibility of semiflint corn increased from 36% at a mean particle size of 3,668 μm to 59% at a mean particle size of 730 μm (
      • Remond D.
      • Cabrera-Estrada J.I.
      • Champion M.
      • Chauveau B.
      • Coudure R.
      • Poncet C.
      Effect of corn particle size on site and extent of starch digestion in lactating dairy cows.
      ). Extrusion of wheat dried distillers grains with solubles improved OM and starch digestibility and increased 3.5% FCM yield, without changing DMI, indicating greater physical FE (
      • Claassen R.M.
      • Christensen D.A.
      • Mutsvangwa T.
      Effects of extruding wheat dried distillers grains with solubles with peas or canola meal on ruminal fermentation, microbial protein synthesis, nutrient digestion, and milk production in dairy cows.
      ).
      Enhancements in rumen function can improve digestibility, reduce fecal loss, and maximize microbial protein yield, lessening the need for expensive RUP and fat supplementation and potentially improving economic FE (
      • Krause K.M.
      • Oetzel G.R.
      Inducing subacute ruminal acidosis in lactating dairy cows.
      ;
      • Roman-Garcia Y.
      • White R.R.
      • Firkins J.L.
      Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. I. Derivation of equations.
      ;
      • Strobel H.J.
      • Russell J.B.
      Effect of pH and energy spilling on bacterial protein synthesis by carbohydrate-limited cultures of mixed rumen bacteria.
      ). Dietary factors including total dietary starch and fiber, digestion rates, and rumen effective fiber all affect rumen pH and retention of feed particles. Cow comfort, cow management, feeding method, and forage management influence feeding behavior and feed intake patterns that also contribute to rumen health (
      • Nocek J.E.
      Bovine acidosis: Implications on laminitis.
      ;
      • Stone W.C.
      Nutritional approaches to minimize subacute ruminal acidosis and laminitis in dairy cattle.
      ).
      Proven feed additives can improve rumen pH, digestibility, milk yield, and physical FE and reduce methane losses (
      • Desnoyers M.
      • Giger-Reverdin S.
      • Bertin G.
      • Duvaux-Ponter C.
      • Sauvant D.
      Meta-analysis of the influence of Saccharomyces cerevisiae supplementation on ruminal parameters and milk production of ruminants.
      ;
      • Poppy G.D.
      • Rabiee A.R.
      • Lean I.J.
      • Sanchez W.J.
      • Dorton K.L.
      • Morley P.S.
      A meta-analysis of the effects of feeding yeast culture produced by anaerobic fermentation on Saccharomyces cerevisiae on milk production of lactating dairy cows.
      ). Ionophores such as monensin can be fed to inhibit growth of gram-positive bacteria, increase propionate yield, reduce acetate and butyrate, and decrease energy loss in the form of methane, and potential negative effects of ionophores are reduced milkfat concentration and decreased fiber digestion (
      • McGuffey R.K.
      • Richardson L.F.
      • Wilkinson J.I.D.
      Ionophores for dairy cattle: Current status and future outlook.
      ;
      • Ipharraguerre I.R.
      • Clark J.H.
      Usefulness of ionophores for lactating dairy cows: A review.
      ). In a meta-analysis with 22 studies with dairy and beef cattle, monensin decreased the percentage of GE lost as methane from 5.97 to 5.43% (
      • Appuhamy J.A.
      • Strathe A.B.
      • Jayasundara S.
      • Wagner-Riddle C.
      • Dijkstra J.
      • France J.
      • Kebreab E.
      Anti-methanogenic effects of monensin in dairy and beef cattle: A meta-analysis.
      ). Physical FE improvements with monensin may be diet dependent.
      • Akins M.S.
      • Perfield K.L.
      • Green H.B.
      • Bertics S.J.
      • Shaver R.D.
      Effect of monensin in lactating dairy cow diets at 2 starch concentrations.
      increased physical FE with monensin regardless of diet, but the response was greater with a diet containing 27 versus 20% starch.
      Formulation of efficient rations requires accurate laboratory evaluation of rumen fiber and starch digestion rates and dynamic nutrition models that optimize and predict DMI and reveal dietary factors limiting efficiency of feed usage. Sophisticated techniques should be used to simulate responses of cow groups to diets and predict optimum diet nutrient densities based on DIM, potential production, ingredient prices, and predicted variation in parameters (
      • St-Pierre N.R.
      • Thraen C.S.
      Animal grouping strategies, sources of variation, and economic factors affecting nutrient balance on dairy farms.
      ).

      Feeding Management Factors Related to Dairy Efficiency

      Total potential DM losses from harvest to feed out range from 17 to 64% for hay-crop silage and 12 to 23% for corn silage (
      • Holmes B.J.
      Getting the most from your bunker/pile silo.
      ). Reducing these nutrient losses can significantly improve total dairy enterprise efficiency. Forage decisions including crop and storage types should be based on land availability, soil characteristics, manure management needs, climate, and feeding method. Dynamic models such as the Integrated Farm System Model (
      • Rotz C.A.
      • Corson M.S.
      • Chianese D.S.
      • Montes F.
      • Hafner S.D.
      • Coiner C.U.
      The Integrated Farm System Model.
      ) can help to evaluate many of these factors, aiding the decision process.
      Once the crop is harvested and stored, DM losses continue. Typical silage storage losses range from 10 to 16% (
      • Rotz C.A.
      • Muck R.E.
      Changes in forage quality during harvest and storage.
      ). Numerous factors influence silage preservation, including extent of plant respiration, the activity of plant enzymes, aerobic microbes and Clostridia, and the rate of pH decline (
      • Muck R.E.
      Factors influencing silage quality and their implications for management.
      ). Strategies for reducing silage DM and nutrient losses from cutting to feed out include practicing wide swath mowing to reduce hay-crop respiration and mechanical losses, excellent silage management (rapid filling, packing, sealing, minimal air infiltration at silage face;
      • Ruppel K.A.
      • Pitt R.E.
      • Chase L.E.
      • Galton D.M.
      Bunker silo management and its relationship to forage preservation on dairy farms.
      ), use of oxygen-barrier film (
      • Borreani G.
      • Tabacco E.
      • Cavallarin L.
      A new oxygen barrier film reduces aerobic deterioration in farm-scale corn silage.
      ), and use of proven silage inoculants for rapid pH decline and longer aerobic stability.
      Dairies can reduce feed expenses and improve economic feed efficiency and total dairy enterprise efficiency by purchasing by-product feeds as commodities (
      • Buza M.H.
      • Holden L.A.
      • White R.A.
      • Ishler V.A.
      Evaluating the effect of ration composition on income over feed cost and milk yield.
      ) but must address their inherent variability in quality and nutrient profile (
      • St-Pierre N.R.
      • Weiss W.P.
      Understanding feed analysis variation and minimizing its impact on ration formulation.
      ;
      • Bradford B.J.
      • Mullins C.R.
      Strategies for promoting productivity and health of dairy cattle by feeding nonforage fiber sources.
      ). Also, the cost of feed shrink and spoilage on the farm should be assessed (
      • Kertz A.F.
      Variability in delivery of nutrients to lactating dairy cows.
      ). Often, dairies purchase 1 or 2 mixed grain and mineral supplements, which are used in multiple rations. If this strategy results in better quality ingredients and additives being fed to lower-producing cows in late lactation, a dairy efficiency loss will be incurred.
      For highest production and efficiency, consumed rations should be similar to the formulated ration with little daily variation. In a survey of 22 commercial freestall herds, the delivered TMR contained more NEl (+0.05 Mcal/kg) and NFC (+1.2%) but less CP (−0.4%) and NDF (−0.6%) than the formulated ration. Every 0.5-percentage-point reduction in daily NEl variation (CV) was positively related to 3.2 kg/d milk yield, 1.0 kg/d DMI, and 4.3% physical FE (kg of milk/kg of DMI;
      • Sova A.D.
      • LeBlanc S.J.
      • McBride B.W.
      • DeVries T.J.
      Accuracy and precision of total mixed rations fed on commercial dairy farms.
      ). Controlling variation in the delivery of nutrients to the animal by appropriate feed and forage selection, feed analysis, and mixing is essential. Separating forages by hybrid or cutting and sorting feed commodities by source can decrease the amount of fixed variation that would otherwise be assumed to be random (
      • St-Pierre N.R.
      • Weiss W.P.
      Understanding feed analysis variation and minimizing its impact on ration formulation.
      ). Increasing TMR moisture (
      • Shaver R.D.
      Rumen acidosis in dairy cattle: Bunk management considerations.
      ) and increasing feeding frequency from 1 to 2 times/d (
      • DeVries T.J.
      • von Keyserlingk M.A.G.
      • Beauchemin K.A.
      Frequency of feed delivery affects the behavior of lactating dairy cows.
      ;
      • Sova A.D.
      • LeBlanc S.J.
      • McBride B.W.
      • DeVries T.J.
      Associations between herd-level feeding management practices, feed sorting, and milk production in freestall dairy farms.
      ) can reduce TMR sorting.
      Low TMR refusal rates can equate to reduced feed wastage and improved dairy efficiency. However, time without available feed may limit DMI as well as increase slug feeding and subacute rumen acidosis (
      • Stone W.C.
      Nutritional approaches to minimize subacute ruminal acidosis and laminitis in dairy cattle.
      ). Experience on commercial dairies indicates that ad libitum intake and productivity can be maintained with low feed refusals (2–3%;
      • Barmore J.A.
      Fine-tuning the ration mixing and feeding of high producing herds.
      ). However, consistent feeding management is essential, including on-site forage DM analysis, accurate cows per pen counts, and a routine daily feeding schedule.
      Efficiency of feed usage is affected by the number of cow feeding groups and the criteria for grouping on the dairy (
      • VandeHaar M.J.
      • Armentano L.E.
      • Moody Spurlock D.
      Searching for a more efficient cow: Feeding and breeding to enhance efficiency.
      ). With precision feeding, lactating cows are separated into multiple feeding groups and fed diets closer to their requirements. According to
      • Maltz E.
      • Barbosa L.F.
      • Bueno P.
      • Scagion L.
      • Kaniyamattam K.
      • Greco L.F.
      • De Vries A.
      • Santos J.E.P.
      Effect of feeding according to energy balance on performance, nutrient excretion, and feeding behavior of early lactation dairy cows.
      , cows that were individually precision fed according to energy balance estimates had increased milk and 3.5% FCM yield as well as greater physical FE compared with control cows fed a ration designed to provide nutrients for 40 kg of milk per cow per day. When cow data from 30 Wisconsin dairy farms was analyzed using a nonlinear optimization approach for grouping, increases in IOFC of $161 to $580/yr per cow were predicted with a change from 1 to 3 lactating feeding groups (
      • Cabrera V.E.
      Grouping strategies for feeding lactating dairy cattle.
      ).
      • Talebi A.
      • von Keyserlingk M.A.G.
      • Telezhenko E.
      • Weary D.M.
      Reduced stocking density mitigates the negative effects of regrouping dairy cattle.
      concluded that reduced pen stocking density minimized regrouping issues, which typically result in more competitive behavior and decreased lying time.
      Best grouping strategies for dairy efficiency and optimal cow well-being are likely to vary with farm design, management, productivity, bST usage, feed expenses, labor, and equipment. Regardless, separation of cows into multiple feeding groups and provision of dietary nutrients closer to requirements generally improves dairy efficiency. Economic and welfare concerns with overcrowding, cow comfort, and transition cow management need to be respected both for long-term viability of the individual dairy as well as for best public image of the dairy industry (
      • Grant R.
      Stocking density and time budgets.
      ). Incorporating the effects of feeding management and behavior into dynamic dairy nutrition models offers potential for improving nutrition strategies and the prediction of milk yield and dairy efficiency (
      • Grant R.J.
      • Tylutki T.P.
      Influence of social environment on feed intake of dairy cattle.
      ).

      IMPLICATIONS

      On-farm dairy efficiency measures can be useful instruments to evaluate changes in nutrition and management on the dairy. Each on-farm dairy efficiency measure has both advantages and limitations. Each can be informative, but they provide more appropriate guidance when examined simultaneously rather than in isolation. Dairy efficiency goals should not be viewed as fixed but as moving targets specific to the current conditions of each dairy enterprise. For these reasons, individual farm dairy efficiency measures are not recommended to directly address consumer and retailer questions about sustainability.
      Nutrition and feeding management have major effects on dairy efficiency. Dairy managers and nutritionists need to carefully consider diet digestibility, rumen function, feed analyses, nutrient requirement estimates for various animal groups, forage selection and associated agronomic considerations, forage preservation, as well as TMR preparation, delivery, and intake to define reasonable dairy efficiency targets and production goals for individual farms that will lead to greater economic and environmental sustainability.

      ACKNOWLEDGMENTS

      The authors thank the Cow of the Future project and the Innovation Center for US Dairy (Rosemont, IL) for funding this project.

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