DGO; COM | Booklet | IFPRI2; | Non-PR

Non-PR | IFPRI4

Agricultural research in marginal dry areas can contribute to reducing poverty through the development of technological, institutional and policy options for poor farmers. Such research should address diversified opportunities and development pathways. This article analyses the diversity of livelihood strategies of rural people living in the Khanasser Valley in northwestern Syria, an area that is typical of marginal drylands. It proposes an operational classification of households based on their different livelihood strategies, applying an integrated methodology within a Sustainable Livelihoods framework. Households are classified into three clusters: agriculturists, labourers and pastoralists. The article examines the diversity of livelihoods involved, and considers where and how research should be directed to have greatest impact on poverty. Given that rural households are not homogeneous but dynamic entities, with diverse assets, capabilities and opportunities, the definition of household typologies can help to target development research. The article concludes that while agriculturists benefit most, poor labourers with enough land can also gain from pro-poor agricultural research. The poorest households with little land, and pastoralists, benefit little or only indirectly.

The objective of this study was to estimate genetic parameters of reproduction traits of pure Fogera cattle at Metekel Ranch. Metekel cattle Breeding and Improvement Ranch has so far been engaged in maintenance of Fogera cattle population outside their adapted environment (ex-situ conservation). The breeding program has two components: selection and crossbreeding. The establishment of the pure breed unit is meant for the improvement of the Fogera breed and for providing heifers to cross- breed to exotic dairy sires (by Artificial insemination). In cross breeding program; crossbred animals are produced through artificial insemination of Fogera cows with Friesian semen. Around three to six months of pregnancy, the F1 cross heifers are sold to farmers for milk production (Melaku et al., 2011a, b). Very recently the ranch started to distribute non pregnant F1 cross heifers. WOMBAT software was used to estimate genetic parameters. The variance components and heritability were estimated using a Uni-variate animal model using four models which fitted direct additive, dam genetic and permanent environmental effect as a random effect and the fixed effects (year, season, sex and parity). Parameter of age at first calving (AFC) were estimated using Model 1 (Y= Xb + Z1a + e), Model2 (Y= Xb + Z1a + Z3c + e), Model3 (Y= Xb + Z1a + Z2m + e (cova, m = 0), and Model4 (Y= Xb + Z1a + Z2m + Z3c + e (cova, m = 0) whereas parameters of reproductive traits including gestation length (GL), calving interval (CI) and days open (DO) were estimated using model 2 and 4 which fit permanent environmental effect due to repeated records per cow. Correlations (genetic and phenotypic) among the different traits were estimated from bi--variate analysis by using model 1 for growth traits and AFC and model 2 to estimate the correlation between CI, GL and DO and birth weight (BWT) and GL. Correlation between birth weight and gestation length were estimated by treating gestation length as a trait of calf. Due to record limitation correlation between AFC with other reproductive traits were not estimated. Estimates of direct heritability of reproductive performance traits from the best model were 0.003 ± 0.05 for AFC, 0.00 ± 0.03 for GL and CI and 0.013 ± 0.03 for DO. The phenotypic correlations between reproductive traits were 0.003 ± 0.034 for CI and GL, 0.37 ± 0.041 for CI and DO and 0.167 ± 0.036 for DO and GL and the genetic correlation between reproductive traits ranged from -0.94 ± 0.2 for DO and GL to 0.83 ± 0.579 for CI and DO. Genetic correlation between growth and AFC ranged from 0.77 ± 0.24 for BWT and AFC to 0.87 ± 0.03 for pre-weaning average daily gain (PADG) and AFC. The phenotypic and genetic correlations between BWT and GL were 0.03 ± 0.05 and -0.84 ± 0.013 respectively. The results of genetic correlation between considered traits was ranged from moderate to high and it indicates that selection for one trait would have a significant effect on the other traits not considered however selection must be done with caution. The heritability estimates confirmed the presence of high environmental effect among the study population and it masks the individual animal genetic difference. Given the low heritability estimates obtained, effective improvement in reproduction performance of Fogera cattle could be achieved by improving the production conditions and through crossbreeding.