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Collecting meaningful data on labor use and farm size for economic analysis associated with onfarm trials in subSaharan African
On-farm research alms at examining the effects of physical, biological, and socioeconomic factors on the performance of different farming systems as well as testing the acceptability or adoptability of new technology by farmers. Gomez (1977) distinguished these aims as technology development and technology adoption research. Researcher-managed on-farm trials play a more significant role in technology development research, while in the case of technology adoption research, farmer-managed trials become more important. Inland-abundant economies, such as those found in most of sub-Saharan Africa, labor is the most important input in farming systems and the key to development of its agricultural economies (Mellor and Johnson 1984). An accurate estimation of labor productivity is, therefore, vital in the economic assessment of existing technologies as well as the adoption of new technologies in sub-Saharan Africa. In order to make such estimates one needs accurate measures of farm size, the actual labor input (e.g, man-hours/ha). as well as accurate estimates of crop yields. Much of the literature on the design of on-farm experiments is dominated by agronomic features relevant to the estimation and measurement of yield. Most experiments are conducted on small plots, the data from which are extrapolated to the per hectare basis. Little attention is paid to the accurate estimates of farmers' labor use and farm sizes. If we could accurately estimate labor use/ha for small experimental plots (usually less than 100m), we could theoretically obtain all the information necessary for the calculation of the economic profitability of a new technology. However, there are many difficulties involved in using small plots for estimation of labor use at the farm level. This paper discusses the need for estimating labor data from a range of plot sizes, and the accuracy of different methods of estimating farm/plot size in sub-Saharan Africa.