In the last issue we discussed the issues surrounding forage sampling and the information that can be produced in the process. We'll continue the discussion we started concerning the comparison of various nutrient values but this is a good time to point out that not all forage analyses are the same nor do they mean the same thing. While it is true that nutrient levels such as crude protein, fat, fiber, etc. are fundamentally the same from lab to lab and the analyses attempt to isolate the particular nutrient that is where the similarity ends and the confusion begins. Not all labs, assays and reports are the same but we'll get to that in a minute.
One fairly effective method of comparing the quality of two forage samples is by using a system know as Relative Feed Value or RFV. Relative Feed Value is an index used to rank hays, haylages or silages based on a calculation of Dry Matter Digestibility (DDM) and Dry Matter Intake (DMI). Remember that the dry matter portion of a given sample includes everything but the water in the sample. Digestibility and intake are estimated from Acid Detergent Fiber (ADF) and Neutral Detergent Fiber (NDF) analyses respectively. You will recall from Part One of this series that ADF represented fiber components that indicated digestibility. The higher the ADF level, the lower the digestibility. Also, NDF was made up of the ADF number plus hemicellulose and was a good indicator of intake levels. The number derived from the RFV calculation has no units and is used only as an index to compare different quality hays and/or haylages. The higher the RFV, the better the quality of hay. In other words, the higher the RFV of a forage sample the more digestible it is and the more an animal can eat. Crude protein, fat etc. are not factors. A forage with an RFV of 100 contains 41% ADF and 53% NDF. The formula for RFV is as follows:
So with the sample suggested above with the 41% ADF and 53% NDF, the equations would be:
DDM = 88.9 –0.779 (41.0) = 56.96
DMI = 120 / 53.0 = 2.27
RFV = (56.96 x 2.27) / 1.29 = 100.23
So as you can see, the math is fairly easy and you can generate these comparative numbers yourself as long as you have the values for the two fiber components. One especially important reason these equations are important is that they provide an index where you can compare values of forages which have unequal ADF/NDF relationships. In some cases you may have two forage samples where the ADF of No. 1 is higher than the ADF of No. 2 but, at the same time the NDF is lower in 1 but higher in 2. Without a way to put these on the same playing field, making a comparison between these two becomes difficult.
Table 1 below gives typical ranges in hay composition showing the calculated RFV's along with other nutrient information. The quality standard in the left hand column provides an overall description or rating of the samples.
Table 1. Typical ranges in legume, legume-grass, and grass hay composition.
Standard ---------% of DM--------
% % of BW
Typically, hays such as alfalfa fall into the Prime and No. 1 and 2 Standards while many grass hays, especially the bermudas, fall into the 3 to 5 range. Interestingly, based in the RFV system as well as the crude protein content, if a producer is required to buy hay, it is often a better value for him to spend more per ton and purchase a better quality hay, such as alfalfa, than to spend a bit less and buy some grass hays.
Other Calculated Values
From the preceding section you can see that there are some results found in the results of a forage assay that are not produced by pure chemical or other direct analyses. There numerous values that are generated by mathematical calculation, as we saw with RFV's. These equations and calculations have been developed by years of research and testing to determine a mathematical way to predict certain values. An important point to remember is that not all labs use the same equations nor are they required to. The equations they typically use will be those they have determined are most effective for their purposes and those of their clientele. This difference is one primary reason why we see some difference between lab values for assays of the same sample, in addition to typical analytical variation. This makes comparisons between laboratories difficult. Laboratories should be able to provide the source and accuracy of the formulas they use.
Other equations used include:
1) Digestible Protein (DP)
This calculated value is generated using some percentage of the crude protein value, such as 70 or 72 percent. Other laboratories may use other formulas such as:
· DP = (Crude protein X 0.908) – 3.77.
The digestible protein value gives no indication if any heat damage has occurred. It has little practical value in formulating rations.
2) Total Digestible Nutrients (TDN)
Some laboratories use the same formula to calculate the TDN value as they do the DDM; therefore, the two values would be the same. Other laboratories will use different formulas, such as:
· Alfalfa: % TDN = 96.35--(ADF % X 1.15)
· Corn Silage: % TDN = 87.84--(ADF % X 0.70)
As the percent ADF increases, TDN will decrease.
3) Net Energy-Lactation (NEL), Net Energy-Maintenance (NEM), and Net Energy-Gain (NEG)
These net energy values are often calculated from TDN values, which in turn are generated from percent ADF. Examples are:
· NEL: Mcal/lb = (TDN % x 0.01114) – 0.054
· NEM: Mcal/lb = (TDN % x 0.01318) – 0.132
· NEG: Mcal/lb = (TDN % x 0.01318) – 0.459
As the percent ADF in the forage increases, the net energy values will decrease.
Not all Laboratories are Created Equal
There are dozens, if not several hundred analytical laboratories scattered across the United States. Many of these are private or commercial labs set up to provide analyses services as their means of revenue generation. Others can be found in universities, agriculturally based companies (i.e. feed companies, etc.), consulting firms, research facilities, etc. No two labs are set up alike and no two labs will have the same people operating them. As we discussed before, they also use varying methods of calculating the values they produce and additionally, they use different methods of performing the bases analyses. Let's take a moment and discuss the basis on which different labs are founded.
a.) Wet Chemistry Laboratories
Wet Chemistry Labs perform analytical procedures bases on approved chemical protocols which have been proven to extract a given nutrient (i.e. nitrogen, fat, the various fiber components) in a manner that can be measured. For instance to measure the protein content of a sample it must be measured, “digested” or broken down, and the nitrogen extracted in order for the calculation to be made of the crude protein content. There is not an actual test for crude protein. As mentioned the test actually measures the nitrogen level and with nitrogen being a primary component of protein, it is then used to determine the crude protein level. Fat, on the other hand, can be isolated, more or less, as it is and subsequently measured or quantified. The same is true for the fiber components such as acid detergent fiber, which uses an acidic or low pH environment to extract and measure the levels of cellulose, lignin and ADF protein. Neutral detergent fiber (NDF) isolates these components plus hemicellulose and is an assay that uses a more neutral pH. Minerals are also isolated by various means. Other nutrients can also be assayed, such as vitamins, but these are complicated procedures and are quite expensive due to the cost of the instrumentation needed and the time involved.
Many nutritionists and researchers feel that wet chemistry is a more direct and more accurate method of determining nutrient concentrations in a sample. The downside is that it is more time consuming to run a fairly comprehensive test and somewhat more expensive. Qualities to look for in a good wet chem lab are relatively quick turn-around time and consistency (small variability) of assay results - in other words, if they run a sample more than once they get very similar results. Other features include reasonably priced assays or groups of assays and reports generated in a format that is relatively simple to understand. Average cost of a wet hem analysis which includes dry matter, protein, fiber, possibly fat, energy calculations, macro and micro trace minerals should be in the mid $20.00's per sample. Additional assays for less common nutrients will increase this cost.
b.) NIR Laboratories
NIR stands for Near Infra-Red Spectrophotometry analysis. NIR tests are based on the theory that certain nutrients within a given sample will respond differently to different types of light and this response can be compared to calibrations from standard values that have been input into the machine. Typical NIR analysis will involve taking the sample, grinding it, weighing out the appropriate amount, placing it into an appropriate vessel which is then placed in the instrument. The NIR is computer controlled and in a very short period of time (minutes) generates a set of results for the nutrients desired. Current NIR procedures have greatly improved over the years with the increased numbers of samples assayed and increasing the database available to develop the calibrations. The advantages to NIR analysis is that it is fast and relatively inexpensive. The downside is that a given assay from a given lab is only as good as the calibrations and standards it has upon which to base the tests. Many nutritionists and researchers feel we still have a ways to go before NIR assays become as readily acceptable as those generated by wet chemistry. Still others feel we are already there.
Forage testing for any cattle operation is a very important management tool. Select a lab based on references from several sources and develop a relationship with the organization. Check them out from time to time by comparing their results and prices to other labs of the same basic type. The most important thing to remember is to find a forage lab you can work with and make it part of your program.
Dr. Steve Blezinger is a nutritional and management consultant with an office in Sulphur Springs, Texas. He can be contacted at P. O. Box 653 Sulphur Springs, TX 78543, by phone at (903) 885-7992 or by e-mail at firstname.lastname@example.org.