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This paper analysed the baseline productive efficiencies of the cereal–legume farmers in the Sudan Savanna of Nigeria. The paper also investigated the factors that affected the technical efficiency of the sampled farmers. Baseline data collected on cereal-legume farmers who belong to four Innovation Platforms were used for analysis. Results showed that sorghum-legume farmers obtained higher crop output, which is higher than the average for the total sample. There is decreasing return-to-scale in farming operations in the study area, however, unit increases in cultivated area, seed use and fertilizer/chemical application will improve the output by 17%, 20% and 29%, respectively. The mean technical efficiencies for the maize-legume, sorghum-legume farmers and for the pooled sample were found to be 85%, 74% and 79%, respectively. The frequencies of occurrence of the predicted technical efficiencies indicate that the highest number of farmers (for the total sample) have technical efficiencies between 80% and 90%. The sample frequency distribution indicates a clustering of technical efficiencies in the region of 0.8-0.9 efficiency range, implying that the farmers are fairly efficient. Given the variation in the level of technical efficiency, there appears to be considerable room for effecting improvements in the technical efficiencies of the farmers in the study area. Factors influencing technical inefficiency of farmers in the study area are age of farmers, farming experience, credit access, extension contact and interaction with other farmers and farmers' groups, implying that being an IP member will help improve productive efficiencies. The results of this study have clearly demonstrated that almost all the hypothesized factors affecting the productive efficiencies of the sampled farmers are significant; an improvement in farmers' productivity will be recorded if a reinforcement of the IP activities that are aligned with the findings here is ensured. This will increase the potential of the IAR4D to help in improving the productive efficiencies of the farmers, which is one of its key objectives. ; European Union ; Department for International Development, United Kingdom ; Government of Italy ; Government of Norway ; Peer Review

To address the problem of the continued deterioration of livelihood and food security in the sub Saharan Africa, the Forum for Agricultural Research in Africa (FARA) through the sub Saharan Africa Challenge Programme (SSA CP) is implementing the Integrated Agricultural Research for Development (IAR4D). The IAR4D is a multistakeholder agricultural research approach which is currently being implemented at Pilot Learning Sites (PLSs) in three regions of Africa: (I) the Kano-Katsina-Maradi (KKM) PLS in West Africa, (2) the Lake Kivu (LK) PLS in East and Central Africa and (3) the Zimbabwe-Malawi-Mozambique (ZMM) PLS in Southern Africa. The objective of this paper was to employ some baseline data of the Sudan Savanna Task Force of the KKM PLS in West Africa, in a linear discriminant analysis to investigate some of the factors that characterised the farmers based on some starting conditions. The study was also to show whether the farmers that have been baselined have common characteristics that can hypothetically separate them on the basis of belonging to three distinct groups for the implementation of the IAR4D. The sampled respondents were initially classified into three groups of baseline farmers. The grouping was done on the basis of whether the farmers are IAR4D (intervention) or conventional (ARD) or clean sites farmers. This is necessary for the end line survey and for the impact evaluation of the programme. Data on a sub-sample of 300 baselined respondents were used for analysis (92-IAR4D/intervention farmers, 96-ARD/conventional farmers and 112-clean farmers). Results indicated an overall rate of 99% of farmers correctly classified into their respective sites. A number of indicative baseline variables (about 67% of the hypothesized variables) which can be regarded as those which distinguish farmers into those which predictably belong to IAR4D/intervention farmers, ARD/conventional farmers and clean farmers were identified to be significantly important. The different villages chosen for the program evaluation are also correctly identified within their groups. Therefore, three distinct categories of villages are available for evaluating the programme impact. ; European Union ; Department for International Development, United Kingdom ; Government of Italy ; Government of Norway ; Peer Review