Optimizing yield of improved varieties of millet and sorghum under highly variable rainfall conditions using contour ridges in Cinzana, Mali

Low productivity of cereals, the staple food, in Sahelian zone of Cinzana in Mali is caused by a range of factors including but not limited to inherent low soil fertility, and insufficient and inadequate distribution of the rainfall due to high climate variability. In addition, the small amount of rain falls as heavy storms in very short periods of time leading to water losses by runoff which in turn causes a lot of erosion. The two phenomena therefore call for a combination of both strategic (combating erosion) and tactical (coping with inter- and intra-annual rainfall variability) measures to cope with the production uncertainties in such risk-prone environment. As opposed to most farmers’ practice of using the same variety, a tactical solution of using varieties of different cycles for different rainfall amounts/patterns was thought to be worth testing. Varieties of different cycles for different rainfall amounts/patterns were combined with a well-known soil and water conservation practice which is the contour ridge tillage (CRT). The combined effects of the two measures on the production of different varieties of sorghum and millet as well as on soil water content were assessed in on-farm participatory trials in five villages. The experiment was run during three consecutive years (2012, 2013 and 2014). Results A key finding of this research is that regardless of the yearly rainfall amount and provided CRT is used, there were large differences in yields between improved varieties and local ones. This is a result of higher soil water conservation and better response of the improved varieties. Conclusion The use of CRT increases considerably the yields of improved varieties of the most important staple crops of the Cinzana commune which are millet and sorghum. Thus, the use of these early maturing improved varieties, along with CRT, could be an accessible adaptation strategy to climate variability by farmers.