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Do all methods of calculating TDN give useful results?

Posted by jhheiss | November 15, 2021

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Beef Cattle Myth Buster

Dr. Don Llewellyn1, Gary Rohwer2, and Sarah Dreger1
1WSU Department of Animal Sciences and WSU Extension, Pullman, WA
2Bar Diamond, Inc., Parma, ID

Do all methods of calculating TDN give useful results?

That depends: Total Digestible Nutrients (TDN) has existed as a measure of the digestible energy of food and feeds since 1890. Atwater and Rubner & Hill related the digestible combustible energy of a food or feed to the digestion of protein, carbohydrate, and fat. Factors to convert protein and fat to carbohydrate energy equivalents were developed. The digestibility of protein, carbohydrate, and fat was measured with digestion feeding studies. The original equation proposed by Atwater was TDN = 1.36 X dCP + 1 X dCHO + 2.25 X dFAT = digestible combustible energy where dCP is digestible protein, dCHO is digestible carbohydrate, and dFAT is digestible fat. By 1915 Henry and Morrison determined that energy lost from protein in the urine was not accounted for with dCP. To account for this urine loss, the factor for protein was changed from 1.36 to 1.0 for dCP. This changed TDN from a measure of digestible combustible energy to catabolizable energy.

Today, TDN is used to define the energy value of foods and feeds from prediction equations where laboratory measurements of protein, fats, and carbohydrates are made. Laboratories also predict measures based on light spectra data that is used to predict the actual laboratory measures. To further compound the issue, some TDN prediction methods attempt to relate the numerical value, to the productive state of the target species as well as adjust for methane loss from fermentation. Owens and Zinn (2019) found that fifty prediction equations exist in the peer-reviewed literature. From the beginning with Atwater, a summative approach to the problem has been apparent. Summative equations are more robust and can be used across multiple feeds and feed mixtures. However, it is common to predict TDN based on one or two laboratory measures such as protein and fiber. Usually, the equation is valid for an individual type of feed such as alfalfa hay, corn silage, and others; but not all feedstuffs.

The problem becomes apparent when the equation is used on the wrong feed type, a common mistake. To demonstrate the problem, fourteen feeds from the analysis tables in the 2000 edition of NRC Beef Nutrient Requirements publication were selected where protein (CP), FAT, neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin, and ash values were available. The feed selected were Oat Straw (1), Alfalfa Hay Mature (2), Barley Straw (3), Timothy Hay Seed Stage (4), Oat Hay (5), Alfalfa Hay Early Bloom (6), Brome Hay Mid Bloom (7), Beet Pulp Dehydrated (8), Corn Silage 45% Grain (9), Soybean Hulls (10), Barley Grain Heavy (11), Oats 38 lb./bushel (12), Wheat Ground (13), and Corn Dry Grain 56 lb./bushel (14).

The TDN and Digestible Energy (DE) of each feed was calculated using a summative equation, Rohwer, Unpublished, 2021, and two TDN estimates were made. One, using the National Forage Testing Association (NFTA) equation for alfalfa hay. A second, using Rasby (2008) for dairy cattle feeds. Both equations use ADF as the independent variable (Figure 1).

TDN calculations by summative equations as compared to National Forage Testing Association (NAFTA) and Rasby (2008) equations.
Figure 1. TDN calculations by summative equations as compared to National Forage Testing Association (NAFTA) and Rasby (2008) equations.

Oat Straw and Alfalfa Hay Mature were overestimated by both NFTA and Rasby. Feeds 3 through 14 were underestimated by NFTA. Rasby (2008) reasonably estimated feeds 4 through 9, but overestimated the TDN of grains (feeds 11 through 14).

There you have it; the Myth is Busted: The use of thoroughly validated summative prediction equations can prevent serious errors in estimating the economic and feeding values of feeds and feed mixtures. When utilizing TDN in your feeding programs, it is essential to choose the right predictor of TDN based on the specific type of feed(s). In doing so, you can more accurately predict the TDN of the feeds and the level of performance expected. When evaluating feeds for TDN or any of the essential nutrients, your WSU Extension professionals are happy to help ensure a properly balanced diet is achieved.

References:

Metabolizable Energy (ME) Content of Feeds: Errors that need Attention, Fred Owens and Richard Zinn ASAS, 2019 Austin Texas

Available and Unavailable Fiber Content of Feeds, Gary Rohwer, Bar Diamond, Inc. 2019, Unpublished