Using Digestible NDF to Determine Forage Quality Dr Dan Undersander, Forage Specialist, Wisconsin (http://www.uwex.edu/ces/forage/) Manitoba Forage Marketers Conference, April 9 th 2003, Winnipeg Relative feed value has been used for a number of years to indicate the overall feed value of forage. In recent years, there have been some changes considered to make this assessment more accurate in regards to predicting the feed value of forage. It is well accepted that there is a correlation between the acid detergent fiber (ADF) portion of forage and the energy value of the forage. One of the problems has been that different labs will use different methods of calculating the energy value from the ADF fraction. 1. Western: %TDN=82.38-(0.7515 x ADF) 2. Pennsylvania will use the formula: % TDN=4.898+(89.796 x NEL). In this equation NEL=1.044-(0.0119 x ADF) 3. Midwest: %DDM = 88.9-(0.779 x ADF) TDN Estimates from Different Empirical Equations This graph indicates some of the comparisons between some of the different systems. The problem is that none of the systems real work very well. The lines are all averages of individual analysis. TDN 80 30 Western Pennsylvania Midwestern 20 30 Acid Detergent Fiber (%) Dairy producers, in particular, found that they were minimizing the forage interaction in the ration when they used the TDN value for forage. Relationship of In Vitro Digestibility to ADF for Alfalfa In Vitro Digestibility (%) 75 65 55 45 y = -0.8003x + 92.035 R 2 = 0.5458 25 30 35 45 Acid Detergent Fiber (%) WEX Relationship of NDF digestibility to NDF Content y = -0.2184x + 62.015 R 2 = 0.0264 A comparison of ADF, which is the main component for determining TDN, from a number of feed samples indicates a very wide distribution of the data. The R 2 or correlation means that 54% of the time these numbers are accurate not very comforting. A comparison of the digestibility of the cell wall and the cell wall content (ADF) were compared, the relationship was even lower (R 2 =.02). in vitro NDFD 48h, % of NDF 75 65 55 45 35 30 30 35 45 55 65 NDF, % of DM 1
These samples were randomly selected and included not only pure alfalfa, but also alfalfa/grass and grass only samples. The grasses have a higher ADF but also have a higher digestibility, which may not be evident in the equation. 1: Predicting TDN or Energy of Forage: Due to these variations in the TDN prediction, in 2001, the National Research Council (NRC) came out with a new method of calculating TDN. This new method was actually based on the old method, which included the digestible crude protein, as well as the digestible fatty acid the digestible fiber and the digestible non-fibrous carbohydrates. NRC (2001) Dairy Approach to Predicting TDN of Forages: TDN 1-x = tdcp + (tdfa x 2.25) + (tdndf) +tdnfc 7 Note: (tdndf =.75xNDFD 45 x NDF) which is the NDF x the NDF Why did they go away from the old system in the first place? Apparently they thought that there were too many factions to measure. So they thought that 80% of the ADF should be a good estimate of the TDN of forage. However that system was sound on a research basis, but not accurate enough on a practical basis. Based on the new system, the following are two examples of alfalfa forage samples when a digestibility factor is introduced into the equation: NDF ADF NDFD 45 TDN DDM* Forage A: 30 58 61.6 65.5 Forage B: 30 36 53.6 65.5 *DDM= 88.9 *.779(ADF) In these two samples, they are equal in both NDF and ADF, however by including the digestible NDF faction, this results in a major difference in the TDN level of the forage. This will affect how TDN or energy content of a forage-based ration is to be determined. 2: How much as a cow will eat is the second major factor to energy in determining animal performance. In this example, dry matter intake (DMI) was determined on the basis of the NDF at 2.78% of Body Wt. Under this new system, the same two alfalfa samples: NDF ADF NDFD 45 dintake DMI* Forage A: 30 58 31.0 2.78% of BW Forage B: 30 36 22.8 2.78% of BW Note: dintake = base intake plus adjustment for dndf = base intake + (NDFD average NDFD) *.374) (Ref: Oba and Allen, 1999. J.Dairy Sci. 82:589-596 The problem with the old system was that dairy producers were minimizing the forages in their rations because they could not accurately predict the feed value of the forage. This system provides a better 2
assessment. It will also provide a better market assessment of forage in terms of a better energy value and feed intake of the forage. The following is an example rations based on the two feed samples, which reflect the different digestibility of the feeds. Base TMR Adjusted TMR (20-30--58)* (20-30--36) Rations: Lbs DM Lbs DM Alfalfa 25 22 Corn Silage 6 5 High moisture corn 20 17 Protein/mineral/vitamins 7 6 DMI (dry matter intake) 58 NRC 2001 ration evaluation (110 lb milk) NE allowable milk, lb 93 83 MP allowable milk, lb. 110 91 NEI balance. Mcal -5.6-8.7 TMR Nel. Mcal/lb..73 *Note: (CP 20%, ADF 30%, NDF %, Dig 58%) In these examples, by involving the digestibility fraction of the forage, the second forage will result in lower milk being produced. It will provide a better indication of the energy value of forage and will result in a greater use of high quality forage in a ration. Proposed Change to the new Relative Feed Quality (RFQ) system In this example, under the old system, both forages would have the same RFV but under the new system, there is a now major difference between the two feeds. It is expected that the new system will be a more accurate prediction of how the feeds will perform in the ration. NDF ADF NDFD 45 TDN dintake Forage A: 30 58 61.6 31.0 Forage B: 30 36 53.6 22.8 RFQ RFV* Forage A 151 152 Forage B 112 152 *old RFV=(DDMDMD)/1.29 There is some implication to this new RFQ system and they include: Better linkage between forage quality and animal response ADF is eliminated All forage species predicted equally well (the old system was primarily for alfalfa) Variance of forage quality is increased Heat damage results in lower energy predictions (much more sensitive to heat damage) Mature forages = very low energy content TDN calculation is now more appropriate to all feedstuffs 3
The New Relative Forage Quality Formula The former RFV system was based on the following formula: Relative Feed Value = (Intake potential * Digestible Dry Matter Constant Intake potential = 120/NDF, the Digestible Dry Matter = 88.9 (0.779*ADF) and the Constant = 1.29 In this equation, the problem was the ADF, which did not reflect the digestibility of the fiber portion. This has been corrected by the new equation of: Relative Forage Quality (RFQ ) = (dintake Potential * dtdn) Constant In this formula we are now using digestible fiber and digestible TDN. Although these formulas are quite detailed, it is the concept that is important. The detailed formulas for those interested are as follows: Intake potential = base intake + ((dndf-average dndf) * 0.374) = (0.012/NDF)+(NDRD-45)*0.374*13/100 TDN = [(NFC*.98)+(CP*.93)+(FA*.97*2.25)+NDF*NDFD]-7 (Oba and Allen, 1999, J.Dairy Sci) The formula for determining Relative Feed Quality in the short form is: RFQ = dintake potential *dtdn 1.23 One of the objectives of the new system, Comparison of RFV and RFQ for Hay, Haylage, and was to have it similar to the old RFV Baleage, 2002 Worlds Forage Superbowl system, but of course more accurate. In this chart, these samples were obtained 300 from about 200 samples submitted from y = 1.1446x - 32.224 2 20 States and Provinces for the World R 2 = 0.8623 Super bowl in Wisconsin last year. 200 There was a high correlation between RFV and RFQ 1 Mean of RFQ=174, RFV=179 100 However, 22% of the samples submitted to this competition varied 100 1 200 2 300 by over 20 points and some up to RFV points that s a lot! The main reason for this variability was that some samples came in with a fiber digestibility of % and some with 25%. This is the type of difference that will be picked up in the new RFQ formula. RFQ 4
Feed Value of High Quality Forage Forage quality of alfalfa in Kawas trial Effect of forage quality on dry matter intake CP ADF NDF Pre Bloom 21.1 30.2.5 Early Bloom Mid Bloom Full Bloom Percent (dry matter basis) 18.9 14.7 16.3 33.0 38.0 35.9 42.0 52.5 59.5 Dry matter intake (lb/day) 30 20 10 0 Prebloom Early bloom Mid bloom Full bloom Alfalfa Maturity 20% 37% 54% 71% One of the challenges in valuing forages is to determine how much quality is worth? These charts are the results of a study completed in Wisconsin. The forage fed to dairy cows in the rations are 20%, 37%, 54% or 71% of the total ration. The more high quality forage that was introduced into the ration, the higher the dry matter intake. 4% fat corrected milk (lb/day) Effect of forage quality on 4% fat corrected milk at four concentrate levels 90 80 Prebloom Early bloom Mid bloom Full bloom Alfalfa maturity stage 20% 37% 54% 71% From Kawas et al 1989 Effect of forage quality on butterfat content of milk at four concentrate levels The major observation form this trial was the effect of the higher quality forage on the production of milk. You cannot just substitute grain for the lower quality forage and expect the same results. Butterfat Content of milk (%) 3.9 3.7 3.5 3.3 3.1 2.9 2.7 2.5 Prebloom Early bloom Mid bloom Full bloom 20% 37% 54% 71% Alfalfa maturity stage From Kawas et al 1989 This chart is an indication of how much RFV or RFQ worth to the dairy farmer. This data is from hay auctions over a 15- year period in Minnesota and Wisconsin and averages out to $0.90 (US) per point of RFV. So, for the higher quality forage, this averaged out at almost $200 per ton more than the lower quality forage. Dollars per ton Value of milk from forage quality $2 $200 y = 3.7819x - 384.73 $1 $100 $ $0 90 100 110 120 130 1 1 1 Relative Feed Value From Kawas et al. 1989 5
Value of High Quality Hay To the hay marketer, to produce high quality hay, there usually is a reduced yield and the hay marketer needs to be compensated for that. The results of the hay auctions show that there usually is compensation. Another justification to the marketer to stress high quality forage is that it costs just as much to haul high as low quality hay. To the dairy farmer with the adoption of the RFQ system, there will be a more accurate prediction of the energy content and also the potential intake of the forage. There should be a greater interest in using high quality forage, as supplementing low quality with grain will not produce as much milk. There is an upper limit to quality as generally, feeding forage above 1 has not been worthwhile. Some dairy farmers who have access to TMR systems will mix it with lower quality forages. But the greatest advantage for the use of the very high quality forage will be to mix it with corn silage. Results of discussion questions There is a higher digestibility of fiber for forages grown under cooler climatic conditions, such as in the northern latitudes. This is why many Wisconsin Dairy producers prefer to use Manitoba Hay. Alfalfa varieties do show differences in forage quality as new varieties are being developed for more leafiness and more digestible stems. Varieties with a higher leaf to stem ratio will have higher digestibility (some States do publish results of tests eg: Wisconsin Web site). Better fertility will result in higher quality The benchmark for fiber digestibility is 45%, however, most of Manitoba s samples beat that, further south they fall down. Transcribed by Fraser Stewart, Manitoba Forage Council April 2003 6