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Statistical analysis followed the standard procedures described above in model (1). Where replicated treatments were present, the analysis and comparison were conducted on each farm. In a number of cases there. was a single replication per farm, and these results were pooled with the replicated sites using a single mean per treatment per location, and locations used as replications. Regression analysis was used to compare the response of cereal yields to applied nitrogen in rotation compared to continuous culture. Grain yield response in maize and sorghum to applied nitrogen was measured at 29 sites With continuous cropping and at .57 sites in rotation with legumes and small grains. Continuous maize responded ta nitrogen up to about 80 kg N/ha, the maximum level' in the trials-. Maize and sorghum following small. grains or legumes showed only a, modest response in some cases, not statistically significant, and not economically sound because the cost of nitrogen plus application was not offset by the increase in yield. This type of analysis is useful for grouping results of like treatments across sites.
To reach more farmers with this information, eight meetings were scheduled jointly by the Sustainable Agriculture Society and Nebraska- Extension in early 1990. The objectives of the trials and methods were described, tables or figures presented, and the meeting turned over to farmers to interpret the data and derive results. A lively discussion ensued about results from the trials and how to apply them to specific fields. The university staff present were valuable as resource people, helping to explain why or why not crops were responding in specific situations. But the farmers were deriving their own recommendations, and the extension specialists were able to empower the producers to make these decisions. During the next summer of 1990, many of the trial fields were used for field tours and discussions on site. Farmers were in charge of describing what happened. These are both examples of participatory extension practices.
Should the farmer put more confidence- in- results.from his or her own field trial, or from the aggregate analysis across sites? It is usually appealing to have one's own data from a field on the farm, where the cultural practices are known and the results appear to uniquely fit that farm. Whether these are. the best data to use to predict next year's results depends on the similarity of cultural practices, hybrids, and soil conditions across the range of sites, and how likely those sites represent the potential range of possible rainfall events that may occur over a number of years. Since rainfall is-.the most limiting factor in most Nebraska Sites each year in rainfed -crop culture, it is possible that the mean performance over several similar sites will be a better predictor of next year's situation than the results from the single farm. We are seeking data and a method to analyze this situation. The decision by an individual fanner at the moment is a judgement call, and the best that we can do is to provide tools to help improve that judgement.
RESEARCH-EXTENSION AGENDA: LARGE AND SMALL FARMERS
The approach and examples. presented in this chapter illustrate the potential of an emerging paradigm, or shift in patterns of research and extension activities. This applies to both large and small farmers. Efficient research of the type' being discussed here-depends on recognition and full representation of the research domain or inference space. Scientists need to recognize that onstation trials are useful for research and development, but limited for surfacing knowledge about production realities. Both large and smaU farmers need to recognize that they represent these realities, and in a major way can contribute to their identification and solution.
Once the inference space is well understood, it is possible to follow with carefully designed activities to solve the problems associated with the primary constraints to sustainable production using resources and information from both large and small farms. Data gathered in-situ is critical, and on-farm- trials- that include- the widest possible variety of farms are essential. Failure to include.