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INTERPRETATION AND EXTRAPOLATION OF RESULTS
The zone across which such results can be applied depends on how many sites were used for the trials, the soil and climatic characteristics of the sites, whether similar results could be expected from other sites in the region, and how credible or repeatable the results are from the experiments. Several dimensions of this question have been discussed above. In statistical terms, the potential for application of results across a range of environments depends on the significance of the specific technology by environment.interaction. An example is the. testing of hybrids across locations, and measuring the genotype by location interaction. When this is low, it is relatively easy to recommend one or a few hybrids across a wide area; when the interaction is large, there is a high degree of site specificity and need for unique choices for different locations.
It is important to consider the effects of replications, years, and locations in contributing to. the value of results. Increasing number of locations and environments had little effect beyond about eight on the magnitude of the standard error of a genotype mean (Saeed et al., 1984). Increasing number of years from one to two substantially reduced the standard error of the mean, while adding an additional year had minimal effect. Likewise, increasing number of replications has little effect on the standard error. The influence of additional locations or environments is much greater than either adding years or replications to an experiment in order to reduce the variance of a mean, thus increasing the potential for detecting statistical differences among treatments in the experiment. Although it is less expensive to add replications in a single location, this is relatively ineffective in increasing the potential to detect differences. This is consistent with the above discussion on need for a large number of locations or environments for testing, and the relatively smaller need for replication in one site. The concept of single replications and a large number of locations. is-a, cornerstone..of: current commerciathybrid. testing. strategies .(Bradley et al., 1 9b8). The efficiency of this: procedure-inca testing- program has recently been described (Dofing and Francis, 1990). Replication at one site does improve the precision of measurement at that site in that year. But. with multilocational (multiple environment) on-farm testing, the relevant variance is that among locations or environments. Therefore, multiple replications- at one location contribute little to the potential extrapolation from that. site to others, or to other years.
The challenge for the individual farmer is to decide what information really applies to his or her site, given the abundance of results from trials that are available from industry, university, or private sources. The better a farmer is able to characterize the farm and the individual fields, and the better the description of the conditions under which data were collected in other sites, the easier it will be to decide which data or recommendations are relevant. This is a practical way of defining recommendation domains, a topic already explored. The best place to look for relevant data is within the same recommendation domain as that where the field is located. It should be apparent that these domains are not defined only by geographical location, by soil type, or by any single factor. Likewise, it is possible that a single farm may encompass several domains. It is important to understand the concept, and. to use this information to best access the most appropriate data. before making production technology decisions.
PARTICIPATORY MODEL FOR RESEARCH AND EXTENSION
On-farm research trials and demonstrations for extension purposes have long been. a staple component of comprehensive investigation and development programs in agriculture. Some of the reasons have been described above. There are even more compelling reasons today why research with individual farmers and groups of producers makes sense (Francis et al., 1990). There are limited research and extension budgets. with an increasing focus of federal funds irt the U.S. on basic- work at- the expense of applied research. This is a trend that is3 being followed by national