EVALUATING FORAGE VARIETY
TRIAL EFFECTIVENESS FORAGE VARIETY TESTING
SYMPOSIUM |
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EVALUATING FORAGE VARIETY
TRIAL EFFECTIVENESS FORAGE VARIETY TESTING
SYMPOSIUM |
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EVALUATING FORAGE VARIETY
TRIAL EFFECTIVENESS |
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INTRODUCTION Forage variety testing has been practiced by farmers, private seed
companies, land grant colleges, and federal agencies for many years. Results of variety
tests frequently influence which varieties are released by both public and private
breeders. Test results also influence which varieties are marketed in particular regions
and which varieties are chosen for use by farmers. In view of their potential importance
forage variety tests should be highly effective. Variety tests should result in more than
a list of yields produced by a group of varieties. They should discriminate between
well-adapted varieties and inferior ones. They should provide good predictions of how one
variety will perform in relation to another variety. RECENT HISTORY OF ALFALFA VARIETY TESTING The task of variety tester has changed drastically during the last 20 years. Development of new varieties has changed in several ways in alfalfa, and to a lesser degree in other forages. Table 1 summarizes five major changes during the last 20 years with respect to new alfalfa varieties and testing. |
| Table 1. Current alfalfa variety development and testing situation compared to 20 years ago. | |
20 Years Ago |
Current Situation |
| Most varieties were developed by USDA/ARS and universities breeders with no financial incentive to release "new" varieties. | Nearly all varieties are developed by a few industry breeding programs with financial incentive to release "new" varieties. |
| 1 to 5 varieties were released each year in the US. | 50 to 70 new varieties per year are approved for certification, and others are also released. |
| Public breeders conducted variety tests. | Forage extension specialist oversee technicians charged with variety testing. |
| Variety testing was coordinated at "alfalfa" meetings. | Few public variety testers attend "alfalfa" meetings. More attend ASA and AFGC meetings. |
| Almost everyone involved with alfalfa testing understood strengths and weaknesses of other alfalfa testing programs. | Testers receive lists of lists of test results, and sometimes have time to look over others' results. |
| Several questions have been asked during this symposium and should be addressed by
forage variety testers. Three questions that may lead the list follow:
Many forage variety testing programs should answer these questions with strong "yes". It is, however, apparent that many public and private workers could (should) improve their tests, as indicated by Moutray (1992). In alfalfa there are standard test procedures to describe resistance to 6 insects, resistance to 16 disease, resistance to 3 nematodes, resistance to 5 environmental stresses, and 2 morphological or quality traits (Fox et al. 1991). There is no "standard test" to describe a variety's potential yielding ability or persistence, the traits most important to most producers and to the industry. OBJECTIVES OF FORAGE VARIETY TESTING PROGRAMS Forage variety testing programs have many objectives and the importance of the objectives change among locations and over time. Four objectives that are important to most university and private testing programs follow:
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WAYS TO EVALUATE FORAGE VARIETY TESTS Many general ways to evaluate forage tests are utilized to some degree; however, most of them do not indicate if tests meet objectives listed above. There is no single way to evaluate the effectiveness of all forage variety tests because of diverse environments, purposes, measurements used, etc. We propose the use of two closely related methods based on common statistics to evaluate the merits of a forage test. These evaluations should meet the needs of most variety tests when forage yield is the most important measurement. These effectiveness tests are probably more rigorous than needed when the primary measurements are qualitative in nature with large differences among test entries. The CV (Coefficient of Variation) is frequently somewhat abstract, but it is probably the simplest and most useful single statistic one can use to decide if a test meets normal objectives of typical forage variety tests. A forage yield trial with a test CV less than 8% normally discriminate well enough to indicate if the poor varieties are really poor and the good varieties are really good. Tests with CV's greater than 12% do not discriminate well enough to separate varieties that are generally well adapted to the test environment. Forage yield differences must be very large (qualitative differences) to conclude that one variety is significantly better (or worse) than another when CV's are greater than 15%. Caddel (1993) examined 117 statistics sets from 12 central states that contributed to the 1992 CAIC (Central Alfalfa Improvement Conference) Variety Tests report. The CV's ranged from 3.4% to 18.6% with a mean of 7.8%, indicating many tests did not meet an acceptable level of effectiveness. Busbice (1995) reported similar results. Caddel (1993) and Busbice (1995) proposed the value of an alfalfa variety forage trial can be estimated by the modified coefficient of variation (MCV). Where
The MCV (LSD expressed as a fraction of the mean) will estimate the percentage difference between varieties that can be detected at a stated confidence level (p=0.05 is suggested). Busbice (1995) stated that a MCV value of less than 10% is required for a yield test to have practical value. Forage yields of adapted commercial alfalfa varieties are not expected to differ by more than 10%. Caddel (1993) regressed the CV of many different alfalfa forage tests against the MCV and showed that MCV can be calculated by multiplying the CV by 1.3 for most alfalfa variety forage yield tests with four replications (n=4) and 15 to 40 entries. A few other common methods to evaluate forage variety tests are discussed below. Each one has certain merits but rarely addresses the central issue -- "Does this test separate the good varieties from the poor ones?"
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HOW GOOD SHOULD TESTS BE? Forage variety yield tests should be good enough to declare yields of two varieties significantly (p=0.05) different, if their yields differ by 10% of the test mean. In view of this, we propose to use and distribute data that do not meet this level with caution. When MCV is between 10% and 15%, {10%< ( 1. Send results to those who submitted material for the test, including data and statistics for only the originator's entries and checks varieties. 2. Do not send results of other entries. 3. Do not include results in extension publications 4. Do not include results in regional variety test reports (such as CAIC and WAIC). In those cases when MCV is greater than 15% {15%< ( 1. Treat data as if they were not collected. 2. Treat data as if the tests were not conducted. There will be those who object to throwing away data; however, using the data from poor forage variety tests in other ways causes confusion and is likely to proliferate inaccurate information. It answers no normal objective of conducting forage variety tests and should be ignored. This approach puts yield data on the same footing as pest resistance data and data describing physiological data which must meet certain criteria before acceptance. For perennial forages with multiple harvests each year, when should these criteria be applied? They may be applied to individual harvests, annual totals, and/or totals over years. When they should be used depends on the purpose of the test. Forage yields for individual harvests normally tell very little about the overall worth of a perennial variety. The total yield over the life of a test is the most important criterion for judging the worth of a variety and is the most important place to test the effectiveness of a test. Frequently yields of individual harvests are not effective in discrimination among varieties, but the total of harvests within a year and totals of years discriminate well. Consequently testers should use totals, not individual harvest results. |
WAYS TO IMPROVE ALFALFA
VARIETY TESTS Everyone involved in variety testing has horror stories. Everyone also has partial solutions to the problem of controlling variation in forage tests. The following are suggestions of ways to improve alfalfa variety evaluations for forage yield and can be applied to many other variety tests. The "bottom line" is to carry out the best possible test. We cannot cut corners to make false time- and dollar-savings and expect to separate good varieties from poor varieties.
Table 2 illustrates the improvement of MCV's in 11 alfalfa variety forage yield evaluations conducted in Oklahoma, using tests with six replications as compared to four replications. The "4 Reps" column was generated by randomly omitting two of the six replications and reanalyzing. As expected, the MCV was higher for the four reps than for the six reps. All MCV's were acceptable using data from six replications; however, MCV's in three tests exceed 10% when data from only four replications were used in analyses. |
| Table 2. MCV for total forage yield of 3-year alfalfa tests. | ||
| MCV Based on | ||
| Test No. | 6 Reps | 4 Reps |
| 931-92 | 4.8 | 5.5 |
| 961-92 | 4.8 | 6.6 |
| 962-92 | 8.4 | 11.5 |
| 982-92 | 6.0 | 7.3 |
| 001-93 | 4.8 | 6.5 |
| 002-93 | 9.2 | 11.4 |
| 032-93 | 8.0 | 11.5 |
| 041-93 | 7.6 | 9.5 |
| 101-94 | 5.5 | 6.9 |
| 121-94 | 4.7 | 6.0 |
| 151-94 | 4.7 | 5.6 |
| Mean | 6.2 | 8.0 |
| Data from alfalfa variety tests in Oklahoma, sown 1989-1991. MCV's were calculated by -- LSD/test mean X 100. | ||
 Frequent Observations Make frequent visual observations. If you can see real differences, you should be able to measure the differences. There are differences you cannot see. With a one-time observation, most of us cannot see differences as small as 15% in total annual yield. Apparent yields of varieties change over time and small differences add up over a year and over the life of an experiment.
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LITERATURE CITED Busbice, T. H. 1995. How Good are Alfalfa Variety Trials? A Question of Ethics and Accuracy. Proc. 25th Cent. Alfalfa Imp. Conf. p. 9. Caddel, J.L. 1993. How well are we testing alfalfa variety yields? Proc. 23rd Central Alfalfa Imp. Conf. p. 19. Fox, C.C., R.C. Berberet, F.A. Gray, C.R. Grau, D.J. Jessen, and M.A. Peterson (ed.). 1991. Standard tests to characterize alfalfa cultivars. N. Am. Alfalfa Imp. Conf., Beltsville, MD. Moutray, Jim B. 1992. Alfalfa variety testing, current status and future needs from an industry viewpoint. Proc. 22nd National Alfalfa Symposium. p. 10-13. |
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Forage yield
vs. expected yield tells the tester if yields are in a "normal" range of
production in the area, but it does not indicate if the test discriminates between good
and poor varieties. 
) >15%} test data should not be published. One may then ask
what should testers do with such data? If the tester believes that something must be done
with the data, we suggest: 
)} test data should be rejected as not serving
any know purpose. Do not publish test data or use it for any purpose.