ABSTRACT. INTRODUCnON

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1 OBTAINING GREATER CONSISTENCY IN ALFALFA FORAGE TESTING Dan Putnam1 ABSTRACT Laboratory test results detennine a considerable proportion of alfalfa crop value. National and regional voluntary efforts to standardize the hay testing process have been ongoing in response to grower and purchaser concerns about lab consistency. The National Forage Testing Association conducts split-sample tests of laboratories nationwide, and local groups, such as the California Hay Testing Consortium, address needs of local importance. Issues pertaining to laboratory methods for fiber and dry matter detennination, NIR practices, and handling of samples have been addressed. In addition, methods of optimum measurement of forage quality have been discussed. Standardization across states is a laudable goal, but forage quality concepts have developed locally and are somewhat idiosyncratic, so methods of measurement continue to differ from state to state. The sampling process has a tremendous impact upon detennination of feeding value of alfalfa, and a method of certification for hay testing has been proposed in California. Key Words & Abbreviations: Forage Quality, Forage Testing, National forage Testing Association (NFrA), California Hay Testing Consortium (CHTC), Total Digestible Nutrients (TDN), Acid Detergent Fiber (ADF), Neutral Detergent Fiber (NDF), Crude Protein (CP), Dry matter (DM). INTRODUCnON Development of a scientific approach to estimating the quality of forages through laboratory testing has had a tremendous impact upon the way in which alfalfa is bought and sold. Visual inspection. while still an important aspect of evaluation, does not usually reveal the potential feeding value of a forage. There are many examples ofhay which "looks good~' but does not feed well, and visa-versa. Even experie!lced hay buyers can be fooled. Laboratory:testing has provided a much-needed objective measuring stick in what is sometimes a contentious hay trading process. In California, where most hay enters the marketplace, hay is often sampled more than once: by the grower, the broker, and the dairy producer or nutritionist. 'Fair' hays «52% mn, 90%DM basis or >32%ADF, 100% DM basis) have sold for an average of30$/ton less than 'premium' alfalfa (>54%mN, <29% ADF) in California markets over a 5-year period in the mid- IForage Extension Agronomist, Department of Agronomy and Range Science, University of California, Davis, CA Published fu: Proceedings, 27th National Alfalfa Symposium and26th California Alfalfa Symposiwn December, 1996, San Diego, CA. Certified Alfalfa Seed Council, Davis, CA, and University of California, Davis. 195

2 19905 (putnam, 1994). Hence, each year, millions of dollars are gained or lost based upon the results of laboratory testing. One of the most common concerns expressed by hay and dairy producers is uncertainty regarding the consistency of the forage quality reports. Part of this concern may arise from genuine problems with laboratories achieving repeatable results. However, other causes of concern may be due to a lack of understanding of the limitations of laboratory testing, the degree of "normal" variation that one should expect, and the importance of other aspects of the hay testing process, such as sampling technique. This article is a review of several of the efforts made in attempt to address these issues. The National Forage Testing Association (NFTA) was fonned a number oryears ago to addresses methodological issues related to hay testing, and local groups have been fonned to address local needs. The NFTA publishes a booklet on accepted lab methods (Undersander et al., 1993), and holds annual meetings to discuss hay testing issues. A regional consortium oflabs in the Midwest was fonned about 5 years ago to increase the consistency ofnirs analysis in several states. The California Hay Testing Consortium (CHTC) was fonned in California in 1995 as a forum to discuss forage quality issues and issues related to hay testing in the state, and to increase consistency among labs. It is made up of nutritionists, University scientists, hay growers, and most of the laboratories in California. All of these represent voluntary efforts on the part of labs, nutritionists, and growers to improve the hay testing process. THE NATURE OF THE PROBLEM The purpose ofhay testing is to predict the gotential feeding value of the forage, or the ability of the feed to produce a desired outcome in the animal. The word "potential" is used here, since many other factors (animal genetics, management) also impact animal performance. In practice, alfalfa hays are tested to: l)determine the value ofhay in the marketplace, and 2) balance rations Different approaches may be required for these two objectives. When thinking about hay testing, the process appears to be somewhat preposterous. A small amount of sample (usually less than a pound) is obtained from a large mass (typically > 100,000 Ibs) of heterogeneous plant material, ground up and less than 4 grams analyzed--by the lab in hopes of predicting the performance of an equally heterogeneous group of cows! However, when approached with some care and with an understanding of the sources of variation, lab testing has proven to be quite successful at predicting the feeding value of alfalfa hay, as well as detem1ining its worth in the market place. One of the keys to accurate hay testing is to understand the potential sources of variation. Figure 1 indicates many of the sources of variation in the hay testing process. Each one of these steps can contribute to overall sampling error, and if improperly conducted can lead to an erroneous lab test. However, if steps are taken to understand and control variation of these steps, the hay testing process can work remarkably well, and successfully predict the feeding value of alfalfa. 196

3 , FIELD'.MA CY ANAL - TTER YSIS ADF,NDF,CP ANALYTICAL ANALYSIS DRYMATTER G) 0 Figure 1. Flow sheet indicating many of the important potential sources of variation in the hay testing process. Sources 1 and 2 are under the control of the sampler, 4-7 under the control of the lab, and 8-9 are largely determined by the nutritionist. 197

4 Mean: 56.6 Lowest 5 = 54.9 Highest 5 = Core Figure 2. Bale to bale variation in a seemingly uniform stack of California hay (NIRS analysis). mn= ( xadf%) THE IMPORTANCE OF SAMPLING One of the largest sources of variation is the sampling of the hay lot (#1, Fig. 1). Often, complaints about two hay tests which return different results can be traced to sampling problems. Figure 2 shows the amount of variation which is common within a hay lot that appears relatively uniform. These cores were taken from randomly-chosen bales the center of the butt-ends of a stack (90 angle) by walking around the stack and taking every 5th bale. It is highly recommended to take at least 20 hay core samples from a "lot" of no greaterthan 200 tons ofhay. Those accepting a smaller number of cores are at risk that the cores may not represent the whole lot. For example, in Figure 2, if the lowest 5 cores were analyzed, the result would-have been 54.9, and if the highest 5 samples were taken, the result would have been Under normal conditions, and if the samples are taken properly, 20 or more cores should characterize the natural variation in a lot ofhay. A test of different hay probes at UC Davis revealed that when 20 cores are taken, three hay probes did not give different ADF or CP results (Ed DePeters, Barbara Reed, pers. Comm). Many different types ofhay probes have been used successfully. Several principles should be followed when choosing a hay probe: 1. The tip should be kept sharp, 2. The tip should be 90 angle to the shaft, not cut at a slant ( 45 ), 3. The tip should not be greater than 314", and not less than 318", 4. The cutting process should not segregate the leaves from the stems, 5. The sample should not be too large to be practically ground by the lab nor too small to represent the lot, and 6. The probe should penetrate at least 12" into the bale. 198

5 HAY SAMPLER CERTIFICAnON Since it is well understood that correct sampling protocols are a critical part of the hay testing process, the CHTC voted several months ago to develop a certification program for hay samplers. This certification program would be a means to place more a higher degree of confidence that a hay sample has been taken according to an established protocol. It also may be an effective means of emphasizing hay sampling and educating the public about the proper way to sample. Certification would consist of several steps, including reading educational materials, and taking a short test. One of the potential outcomes of this program would be that the Certified Sampler would be able to attest to the fact that a sample was obtained using established protocols, and this notice would travel with the sample, and be attached to the lab report. Although there are aspects of sampling which require some further research (for example, how to sample big bales), there is much that is currently known that can be used today to standardize the way in which samples are taken. Although not yet in place, we hope that this certification program will have an impact in the coming year. SAMPLE HANDLING & GRINDING Sample handling until it arrives at the lab in important, primarily to protect the sample from too hot or too moist conditions (#2, Figure 1). Samples need to be in sealed plastic, especially for field dry matter determination. At the laboratory, the grinding and sample handling is a potentially significant source of variation (#3, Figure 1). Since alfalfa hay is made of leaf and stem components, it is not difficult for segregation of the leaf and stem to occur during grinding or handling. Ground samples should be tumbled and mixed, and segregation offine/coarse particles avoided. There was an example last year of a lab which reported a set of ADF values in the range of 15-18, which is only likely to occur when there is some type of leaf separation during grinding and only the leaves are analyzed. Another problem is incomplete grinding. When a residual of about 5-6% of the dry matter (the coarse, fibrous material), is left in the grinder, a bias of % ADF results (3 sample test). Subsampling the ground sample is another source of variation (#5, Figure 1). Typically, a gram or less ofplant material is used for analysis, and this must be taken in a way that represents the whole well-mixed ground sample. We should remember that we are asking a gram of material to represent the feeding value of tons of alfalfa hay DRY MATfERANALYSIS Calculation of dry matter (DM) is another source of variation (#3, #6, Figure 1). A DM determination is typically performed both on the "as received" product (for reporting DM content from the field), and on the ground product for chemical analysis (Analytical Dry Matter). The "field DM" is used to detennining the amount of water being purchased or fed. The Analytical DM is important to standardize crude protein (CP) and acid detergent fiber (ADF) and other analyses on a 100% DM basis. Although very simple in concept, dry matter analysis can be tricky. When members of the California Hay Testing Consortium were polled, each lab was using a different protocol for DM analysis. We were curious as to the potential impact of this on lab testing. 199

6 In , the cmc conducted a study of dry matter techniques. There were seven samples in the study ranging from about 86% to 92%DM. We found that the reference method (recommended by the NFT A), drying 135 C for 2 hours gave a different result than drying samples 105 C for 16 hours. The 135 method always gives a lower apparent dry matter than does the cooler method, presumably because more water ( or volatile compounds) are driven off at the high temperatures (Table 1). This creates a hi.aa (not a random effect) in the ADF value of about 0.45 percentage points ADF, since a DM value is necessary to calculate ADF on a 100% DM or a 90% DM basis. Because of this bias, and the potential impact on ADF (and thereby mn) values, the CHTC has recommended to adapt the reference method (135 C), and many of our labs have switched to this method in T able 1. Effect of Dry Matter analysis technique on DM results, and ADF value. The DM analysis has an effect on the ADF {and thereby mn) value since the DM value is used to standardize results to 100% DM, or a 90% DM basis. 105 C at 16 hours C at 2 hours Samples ron by two labs (Agronomy and Animal Science) at the Univenity ofcalifornia, Davis, and by JL Analytical, Modesto, and by A&L Lab, Modesto. STANDARDIZATION OF FIBER PROCEDURE Fiber (primarily cellulose, hemicellulose, and lignin) is the least digestible portion of the plant. Therefore, fiber has a strong and negative: relationship to feeding value of a forage. Fiber has been measured using the Crude Fiber (CF) method, and later the Modified Crude Fiber (MCF) method, developed primarily at UC Davis. Nationwide this has largely been replaced by the detergent fiber system (Acid Detergent Fiber and Neutral Detergent Fiber, ADF and NDF), developed at Comell. Either method (ADF, MCF) can be used to predict energy (Total Digestible Nutrients, mn, or other measure), based upon equations derived from animal studies. The detergent fiber system, however, distinguishes the entire cell wall material (NDF) and the cell wall less the hemicellulose portion (ADF), which differ in digestibility. MCF has been used successfully to predict energy value and balance rations, and is highly correlated with ADF. However, theadf method is easier and faster to conduct. Also, when some labs use one method and others use another, a greater degree of variation is found in laboratory testing. Therefore, the CHTC recommended in 1995 that all members switch to ADF for predicting the mn value, which is used to buy and sell alfalfa hay. About 30% of the labs in the state switched (the rest had been using ADF), and all but one lab in California today are using the ADF method to predict mn value. 200

7 NDF has received increased attention in recent years, due to its ability to predict feed intake. Voluntary intake of digestible dry matter is one of the primary advantages of alfalfa forages, and NDF predicts intake better than ADF. When alfalfa-based rations are compared with com-silagebased or grass-hay-based rations of equal or even greater total TDN, the alfalfa diets produced more milk, primarily because of increased feed intake (Van Soest, 1995). More discussion of these issues can be seen in Ed DePeter's article, this proceedings, and in other sources. From the hay testing perspective, NDF tends to be less repeatable than ADF. Since ADF is highly correlated with NDF, in is open to question whether NDF would be a better way to identify superior hays for purchase. Even if nutritionists could agree that NDF is the most valuable measure offorage quality (they currently do not), it is possible that it might still be more desirable to use ADF to identify superior hays, because of its superior repeatability and use NDF to balance rations. In addition to shifting from MCF to ADF for predicting mn, the California Hay Testing Consortium has recommended that the NFT A procedures, or those recommended by the Association of Official Analytical Chemists (AOAC) be adapted by California Labs, in an effort to standardize methods. This is an effort to tighten up the iab procedures (#7, Figure 1), and to make them consistent from lab-lab. PREDICTION OF ENERGY In California, the concept of Total Digestible Nutrients (mn) has been used for a number of years as a determination of the energy content of the feed. It is negatively related to fiber, and is calculated from ADF (can also be calculated form MCF). The effect of calculation method on mn value can be seen in Figure 3. A sample returning a single ADF value can give a vastly ~ s "0 ~ O 0'\ ~ z Q E-.4 Figure 3. The influence of calculation method on TDN value. Data is from a split-sample receive from a lab in 1994, which reported a lab value of Their ADF value was used to calculated the other TDN values from published equations. The "Western Alfalfa " equation is recommended in CA. 201

8 different mn value, depending upon which equation is chosen (it was unclear, in this example, how the lab arrived at the mn value they reported). This is an obvious source of correctable error. In 1995, the CHTC recommended that a single equation (Bath and Marble, 1989) for Western hay be used, and a number oflabs began standardizing to that method. The potential for confusion between TDN equations is one reason why it might be better to use the ADF value itself to buyand sell hay, rather than the calculated TDN. There are some mathematical anomalies in the use of the TDN vs ADF (see Putnam, 1994). In addition, TDN is typically expressed at a 90% DM basis, but there may be some confusion about this among buyers and sellers. The only negative part about using the ADF value directly is that as the value goes up, the hay is poorer in forage quality. SPLIT SAMPLE TESTS Split-sample tests are an excellent way for laboratories to determine whether their lab results are close to those of other labs. The National Forage Testing Associate conducts a nationwide splitsample certification program, which includes alfalfa, corn silage, and grass hay samples. The techniques of the NFT A have changed in recent years to make the evaluations relate to reference labs using reference methods, and to make the evaluation process fairer, and somewhat more stringent. The NFT A offers an excellent means for quality maintenance for laboratories, and I strongly recommend that labs wishing to upgrade their quality control participate in the NFT A program. Several split sample tests have been conducted in California, with a slightly different objective. These are not for certification purposes, but are meant to allow individual labs the opportunity to continually test the quality of their results against other labs. Also, these tests serve to characterize the variation with the state in lab testing. The most recent test was conducted in 1996, using 3 hay bales provided by the San Joaquin Valley Hay Growers Association, participants in the CHTC. These represented a low, medium, and high quality hay (samples 1-3). Large samples were coarse-ground ( 4 mill), carefully mixed and riflle-split to make a large number of subsamples. Three samples were sent in April, another in June, and the last in July. Overall means and standard deviations of that study are given in Table 2. These data show that all labs were capable of predicting the low, medium, and high quality -samples. Standard deviations were generally around % for CP and ADF and CP, but much higher for NDF (Table 2). Standard deviations were generally lower for NIR than for wet chemistry, similar to the results of previous year. we conducted analysis of variance and calculated variance estimates for 9 of the wet chemistry labs which returned a complete dataset (allj replications). This analysis indicated a greater within lab (between replicate) variance for DM than for the other parameters. This is likely because duplicate samples were made all at once and distributed over time, and dry matter may have genuinely varied in the "replicates". More than half of the variance for CP. ADF. and mn was due to between-iab error, and about 202

9 40-44% due to within-iab error (Table 3). Within-Iab standard deviations were lower than between lab variation. It should be pointed out that within-lab variation includes subsampling variation, as well as changes over time. Samples run on the same day should vary far less than those run weeks apart. Table 2. Average, low, high, and standard deviation datafrom the 1996 California Hay Testing Consortium Split Sample Test. A total of 19 lab units participated in this test, both wet chemistry and NIRS. Samples were split after coarse grinding using a riffle-~e Splitter, and sent in Ap~ and again in July Crude Protein :ND:E: AD.E InN - Wet NIRS Wet NIR Wet NIR Wet NIR N: Average ! ! Low High Samp1e 1 (Low Quality ) I j j j 1.7 Sf Dev Sample 2 (Medium Quality) Average j ~ Low ! High i!! StDev ~ ~ Sample 3 (High Quality) Average ~ j Low j i High StDev i ~

10 Analysis of variance (Table 3) indicated that the samples differed significantly, and that the labs produced statistically significantly different values. While between lab variation continues to be present, most labs, with a few exceptions, returned values that were remarkably similar.the Sample x Lab interaction in the analysis of variance was non-significant for each parameter, indicating that all labs ranked the hays in a similar fashion. Table 3. Means, Analysis o/variance, andvariance components/or 9 labs with equal replication participating in a split-sample test in Samples were sent at different times. Means are those o 3 sam les, re licated3 times (N=9). = - Between Lab Within Lab Lab Number DM CP ADF TDN % % of Total Variance % 59% 56% 56% 68% 41% 44% Standard Deviation Between Lab Within Lab % Anal~sis of Variance: Source: df Sample 2 ** ** ** ** Lab 8 ** ** ** ** =Samnle*T~ah 1 n = = n~ n~ n~ n~ 204

11 CONCLUSIONS Largely voluntary efforts, such as the National Forage Testing Association certification program, and the California Hay Testing Consortium, can be quite effective in improving the hay testing process. It is important to include an parties in discussions about hay testing: labs, nutritionists, hay brokers and growers, as well as scientists. A number of steps have been taken to improve hay testing in California, which include standardization of lab methods, uniformity of energy equations, and educational programs for sampling consistency. A CKN O WLEDGMENTS I and grateful to Dr. Shu Geng for his help in statistical analysis, and to Celia Lamb for her good efforts in managing the NIRS, and to Steve Orloff for review of the manuscript. REFERENCES Bath, D.L., and V.L. Marble Testing Alfalfa for its Feeding Value. Leaflet 21457, WREP 109. Division of Agriculture and Natural Resources, University of California. Putnam, D.H Alfalfa Hay Testing: What do the results really mean? In Proceedings, 24th California Alfalfa Symposium, 8-9 December, University of California, Davis. Undersander, D., D.R Mertens, N. Thiex Forage Analysis Procedures. National Forage Testing Association, Box , Omaha, NE Van Soest, P.J What constitutes alfa1fa quality: New considerations. In 25th National Alfalfa Symposium, February, Syracuse, NY. Certified Alfalfa Seed Council, Davis, CA. 205