One study was undertaken during 2010 and 2011 in 35% of the households in the Sahel area of Mali dispersed as follow: 98 in the site of Boussin, 71 in Djenné, and 80 in Timissa. Its objective was to point out pearl millet fertilization practices in farmer categories and to analyze reasons behind these practices. Results have shown 4 farmer categories (method of Barbara, 1988). Rich farmers are representing 5, 25 and 2% of households in Boussin, Djenné and Timissa respectively. Medium farmers are representing 4% of households in Boussin, 26% in Djenné and 29% in Timissa. Poor farmers involving more farmers are 91, 59 and 69% of households in Boussin, Djenné, Timissa respectively. The very poor farmers the last category identified in Boussin was representing 3% of households.  Farmers have many practices of fertilizer applying in their fields. In Boussin, all the 4 categories of farmers are using manure in their fields. Rich farmers are applying in more, recommended rates of mineral fertilizers. Medium and poor farmers are applying micro dose of mineral fertilizers. Yield in rich and medium farmers’ fields was 1 200 kg/ha. Poor farmers have produced 25% less than this group and the very poor 43% less than the poor. In Djenné, rich farmers are applying manure and recommended rates of mineral fertiliezrs that yielded 1 600 kg of grain/ha while medium and poor are applying manure and mineral fertilizer microdose. Medium and poor farmer have produced 56% less than the rich farmers. In Timissa, rich and medium farmers are using manure and mineral fertilizer microdose that yielded 1 500 kg of grain/ha. While poor farmers are using mineral fertilizer microdose only for 1 000 kg/ha. These results have moreover shown the increasing cost of fertilizer practices from poor to rich farmers. Rich farmers are expending more money in mineral fertilizers. While poor and very poor farmers are expending more in manure. Farmers are not endowed with factors and means of production like: number of active labors, bullock, land, fertilizers, education level and access to market. There are correlations between these different factors showing the vast intervention area of extension agencies.

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