Energy Evaluation: Theory Versus Reality
By Bill Mahanna
The future of the consulting nutritionist seems secure from a takeover by robotic computers given the importance of the "eye of the master" in adjusting the energy estimates of dairy rations.
This was reinforced in a paper Dr. Bill Weiss recently presented at the Four-State Dairy Nutrition & Management Conference held in Dubuque, Iowa.
As a member of the National Research Council (NRC) subcommittee on dairy cattle nutrition responsible for compiling the most recent NRC Nutrient Requirements of Dairy Cattle (seventh revised edition, 2001), it was very informative to listen to Weiss present some of the flaws in the current net energy of lactation (NEL) system found in the NRC recommendations and other formulation models and to have him state that "a good nutritionist should not hesitate to make appropriate adjustments to either feed NEL values or requirements based on apparent energy balance and experience."
This column will attempt to summarize the key points in Weiss's presentation.
There has been a constant evolution in attempts at measuring feed energy values, from the proximate analysis chemical scheme for describing feeds developed in Germany more than 100 years ago to the total digestible nutrients (TDN) system that associates standard digestion coefficients with the organic compounds determined by proximate analysis. TDN then evolved to the NEL system introduced in the fifth revised edition of the Nutrient Requirements of Dairy Cattle (1978) that attempted to account for important energy losses associated with urine, gas and heat.
While gross energy can be determined very accurately with a bomb calorimeter, arriving at a net energy value is much less accurate or precise because NEL includes all of the error associated with determining digestibility coefficients to calculate digestible energy and errors in determining urine and gas to arrive at metabolizable energy values. Finally, data on heat losses to calculate net energy, although extremely important in high forage rations, are limited and expensive to obtain.
The two main flaws in all energy systems (NEL included) are:
- Cows do not have a specific energy requirement. Cows require chemical entities from which adenosine triphosphate is produced or for the synthesis of lactose, milk protein and lipids.
- Rations have NEL, not individual feeds. NEL concentrations are assigned to individual feedstuffs because energy is something we could measure and to allow for linear programming of diet formulations.
Still, we know that the final diet can have a significant effect on the nutrient value of individual ingredients (e.g., excessive ruminal starch availability reducing neutral detergent fiber [NDF] digestibility or high NDF digestibility increasing rate of passage, thus lowering the digestibility of the entire ration).
Another issue with the current NEL system was presented by Robinson (2007) in a review of published dairy studies suggesting that the NEL density of a diet is a function of:
- the inherent characteristics of the entire ration
- the level of consumption, and
- the genetics and/or stage of lactation of cows consuming the ration.
Robinson's review called into question the long-held assumption of a linear discount (4% per unit of maintenance output to three times maintenance levels) in ration NEL due to increased rate of passage and nutrient absorption time with increased dry matter intakes. These energy discounts may be overstated in high-production rations, where cows are fed more grains and/or high-quality forages, resulting in lower urinary and methane losses and a net energy density that may actually be greater as intakes increase (Old, 2008).
Robinson's review also suggested that cows with a higher genetic ability may have a greater ability to digest and absorb dietary nutrients, requiring a more curvilinear approach to energy discounting.
Proposed balance adjustments
Several versions of the NRC Nutrient Requirements of Dairy Cattle calculated maintenance energy requirements as 0.08*BW0.75, with bodyweight (BW) expressed in kilograms and derived from U.S. Department of Agriculture calorimetry data.
Weiss suggested that cows in a metabolism chamber do not accurately model cows housed in large pens that are required to walk considerable distances to be milked three times daily. If this "activity requirement" is added to maintenance, Weiss suggested that the current NRC equations likely underestimate maintenance requirements by 3-5%.
Old (2008) also believes the current NRC maintenance requirements have not significantly changed from the 0.077*BW0.75 estimates derived from beef growing and finishing studies by Lofgreen and Gareett (1968), and yet the lactating cow clearly supports higher metabolically active tissue.
Weiss offered several proposed adjustments to help fine-tune the 2001 NRC-based NEL estimates (the logic of which is also found in many other formulation models) of some common feedstuffs while offering the prediction: "As our knowledge base, computing capacity and analytical abilities increase, practical nutritional models will be developed that do not include energy."
What is really required is "reverse engineering" of the synthesis of lactose, lipids and proteins, ending with the chemical entities required in alfalfa, corn silage, cereal grains, etc. (Old, 2008).
Dry-ground corn grain
Given the increased reliance on corn grain to support energy demands of high-producing animals, it is clear that the NRC model does not account for all of the variation in high-starch feeds. Unfortunately, particle size (or time ensiled for fermented feeds) is not routinely published in most studies, so developing a robust quantitative relationship between corn grain particle size and digestibility has not been possible.
As the industry becomes sensitized to the importance of monitoring particle size, these relationships will likely be better understood in the future. Based on actual trials measuring dietary NEL and milk yields, consider reducing 2001 NRC NEL-3X values for dry-cracked corn by 2.5%, and increase NEL-3X values of dryground corn by 2.5%
The 2001 NRC model predicts only about a 1% increase in NEL for high-moisture corn diets compared to dry corn. Research studies show the difference in diets containing high-moisture corn to be closer to 4-6% more energy than those containing dry corn. NRC does value the high-moisture corn ingredient at about 10% higher NEL. However, when incorporated into the diet, with the NRC discount factor, most of that difference disappears.
Weiss suggested that the NRC discount factor likely over-discounts highly digestible feeds like high-moisture corn. He suggested increasing the 2001 NRC NEL-3X of high-moisture corn by 10%. If the dry matter of the high-moisture corn increases above 75%, smaller adjustments are recommended.
Despite research showing the effect that time in storage has on increasing starch digestibility, there are still no standard recommendations on how to handle this effect in ration formulation models (Mahanna, 2007a).
For steam-flaked corn with a density of approximately 29 lb./bu., it is suggested that the 2001 NRC NEL-3X be increased by 3-4%. As density increases, the adjustment should be less.
The variation in starch content and NDF digestibility in corn silage can significantly affect NEL estimates. Interactions have been found between hybrid and kernel processing; hybrid and maturity, and hybrid and diet formulation.
Weiss suggested that, at the current time, there are not adequate data to quantify the effects of these interactions based on measurable inputs. However, he did suggest increasing the NEL-3X of mature corn silage (greater than two-thirds milk line) by 7.5% when processed.
A positive development in the evaluation of corn silage by Dairyland Laboratories Inc., in conjunction with Sapienza Analytica LLC, is the availability of a 12-hour ruminal and total tract starch digestibility adjusted for the kernel particle size distribution of individual silages (Mahanna, 2007b).
Yet unaccounted for is how to adjust for the effect reported in the research by Hallada et al. (2008) showing increases in both corn silage starch (12 hours) and NDF (30 hours) digestibility over time in storage (1.63% units per month and 1.16% units per month, respectively).
Alfalfa hay marketed in California is currently sold on TDN, which is estimated from fiber content. Studies conducted by the University of California-Davis in the 1950s indicated that the single proximate entity most highly correlated with TDN was modified crude fiber. At that point in time, the use of a single entity to estimate quality was understandable.
Since the 1980s, acid detergent fiber (ADF) has been used to estimate TDN. Chemical entities comprising ADF are not constant and vary with season and stage of maturity. Alfalfa hays with the same ADF content can vary dramatically in digestibility. The current system is antiquated due in part to the efforts of geneticists and agronomists who have developed new alfalfa hay varieties.
The California chapter of the American Registry of Professional Animal Scientists (ARPAS), in conjunction with the University of California-Davis, California State Polytechnic University-San Luis Obispo and Sapienza Analytica, has undertaken a project to update the method used in California to better characterize alfalfa hay quality.
A series of studies are planned with the goal of estimating metabolizable energy of alfalfa hay from near-infrared reflectance spectra. These studies employ both in vivo and in vitro methods to measure disappearance of organic matter, dry matter as well as rate, site and extent of digestibility of selected chemical and proximate entities.
Sampling alfalfa hays for both the in vivo and in vitro studies, representing the diversity seen throughout California, began in April and will continue until this fall. It is expected that the in vitro portion of this study will be completed by the middle of 2009 and that the in vivo study will be completed by early 2010.
California ARPAS is funding this project via corporate sponsorships and also by holding a series of raffles. Those interested in becoming corporate partners are asked to contact John Miller at (559) 909-1731. Raffle tickets may be purchased from Bill Vogt by calling (559) 970-0097.
The Bottom Line
The current cost of cereals and forages dictate that nutritionists assess energy values as accurately as possible to help in balancing ruminally healthy rations as well as to help dairy producers make economically sound decisions about feedstuff inclusion rates.
The 2001 NRC NEL energy system, which forms the basic energy logic of many formulation models, does posses certain inherent flaws and limitations that need to be understood by consulting nutritionists.
Future approaches to feedstuff evaluation and ration formulation will likely move beyond the current reliance on energy systems like NEL. Research studies and laboratory methods are emerging to directly provide digestibility estimates, but even these approaches will likely require the skills of an observant nutritionist to adjust rations based on actual cow performance metrics.
Hallada, C.M., D.A. Sapienza and D. Taysom. 2008. Effect of length of time ensiled on dry matter, starch and fiber digestibility in whole plant corn silage. Abstract T87. J. Dairy Sci. Vol. 91, E-Suppl.
Lofgreen, G.P., and W.N. Gareett. 1968. A system for expressing net energy requirements and feed values for growing and finishing beef cattle. J. Anim. Sci. 27:793-806.
Mahanna, W.C. 2007a. Watch for changing starch digestibility. Feedstuffs. June 11. p. 12-13.
Mahanna, W.C. 2007b. Feed particle size — Important in the cow and in the lab. Feedstuffs. Aug. 13. p. 11.
National Research Council. 2001. Nutrient Requirements of Dairy Cattle. 7th Revised Edition. National Academy Press, Washington, D.C.
Old, Carl. 2008. Personal communication.
Robinson, P.H. 2008. A new look at energy discounts: Using published studies to calculate discounted net energy values for dairy cows fed ad libitum. Can. J. Anim. Sci. 87:57- 70.
Weiss, W.P. 2008. Feed energy applications. Proc. Four-State Dairy Nutrition & Management Conference. June 11-12. Dubuque, Iowa.
Originally published in the August 2008 Feedstuffs issue. Reproduced with permission.