Remember the days of crude fiber? In the past 20 years, forage testing and evaluation have come a long way. The development of NIR and testing procedures for acid and neutral detergent fiber fractions resulted in the formation of a single term index for forage quality called Relative Feed Value (RFV). Although not used for ration balancing per se, RFV has been used widely in hay marketing circles for pricing hay, to describe standing hay forage quality, and as a general term of quality for all harvested forage. Its greatest acceptance and use has been in the upper Midwest.
It took several years to adjust to the RFV concept. It was not a percentage of anything, it didn't take into account the old standby forage quality parameter of crude protein, and an RFV of 100 was considered bad. However, most of the industry did adjust.
RFV is founded on the concept that ADF and NDF are good predictors of intake potential and digestibility, respectively. The RFV is then used to rank forages on their ability to provide energy to a high producing ruminant. The concept of RFV and modern forage testing techniques have succeeded in bringing to the forefront a great appreciation for the importance of forage quality. However, RFV does have limitations and there are those in the industry who have never embraced the concept (see this forage commentary from Cornell University).
RFV does a poor job of making quality comparisons across forage species. Comparing the RFV of alfalfa to that of red clover, a cool season grass, or corn silage is not a valid approach for feedstuff evaluation. The variation in digestibility of structural cell wall components across species is largely responsible for this problem. For this reason, it is best only to use RFV for the purpose of describing alfalfa quality and only alfalfa quality. Even within the alfalfa species, there have been situations where RFV has misrepresented the value of the forage. This is likely the reason for hearing comments like "this hay don't milk like it tests." Another problem with RFV is that equations used to predict digestibility are different for different parts of the United States. Thus, it is sometimes difficult to compare forage analyses from different regions.
Further limitations of RFV include that the system implies a linear relationship between fiber level and animal production. In other words, a 30 point RFV gain from 100 to 130 will result in the similar economic animal value gains as an RFV gain from 160 to 190. Actual animal performance measurements would indicate that this is not the case. Finally, it's thought that the RFV system tends to overestimate the energy availability of low fiber forages and underestimates the value of grasses.
Currently the alternatives are limited to those that have a new set of limitations. Most of the other approaches currently being used in other regions of the U.S. are also some form of predictive equations. Obviously, the most accurate method would be to measure forage digestibility in vitro (using actual rumen fluid to digest forage samples in a lab) or in situ (digest forages in the rumen of an animal). Obviously, neither one of these approaches is practical for the commercial lab handling thousands of forage samples each year.
As was reported at the Dairy Forage Seminar in December by Dr. David Combs, UW Dairy Scientist, forage researchers at the University of Wisconsin are working on a system to estimate forage digestibility using NIR. This approach would also incorporate digestion kinetics. That is, it would take into account rate of passage through the rumen and measure the proportions of indigestible, partially digestible, and soluble dry matter. Preliminary results look promising but are still far from "hitting the market". It is thought that this approach would offer a better alternative than RFV for valuing feedstuffs across a wide species base, make it easier to balance rations, and offer forage breeders a new tool for germplasm selection.
RFV still offers producers a valuable tool for forage evaluation if its limitations are known. It is a system that best used when evaluating and comparing alfalfa. The predictive value of RFV in estimating energy is still strong but realize that animal productivity is not necessarily linear. As has been preached for many years, match RFV to the productive requirements of the animal.
For more information contact Mike Rankin|
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