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Phenotypic ranking experiments in identifying breeding objective traits of smallholder farmers in northwestern Ethiopia.

ABSTRACT: We executed two live animal ranking experiments, own-flock and group-animal ranking, to identify the breeding objectives of Arab and Oromo goat keepers in northwestern Ethiopia as a preliminary step towards designing sustainable breeding programs for two goat populations. In the own-flock ranking experiment, a total of 147 households, out of which 46 were Arab and 101 were Oromo goat keepers that live in semi-arid and sub-humid agroecologies respectively, were visited at their homesteads and were asked to choose their first best, second best, third best and the most inferior does from their own flock. The reasons of ranking and life history of the does (age, previous production and reproduction information) were inquired and recorded; live body weight and some linear body measurements were taken. In the group-animal ranking experiment, 12 breeding does and 12 breeding bucks from Arab goats and the same number of animals from Oromo goats were randomly selected. Life history of selected does and bucks (age, birth type, libido and temperament) were inquired from the owners. The selected animals were randomly grouped into four in Arab goats (three animals per group) and the same was applied in Oromo goats. Twelve farmers for Arab goats and the same number of farmers for Oromo goats who have not known the experimental animals were invited to do the ranking. Each person ranked the three animals in each group as 1st, 2nd and 3rd, giving reasons of ranking. After a first round of ranking, s/he was then provided with the history of each individual animal and asked whether s/he would consider re-ranking them. This procedure was continued eight times until a person covered all groups of does and bucks. It was found out that in own-flock ranking experiment, keepers focus on productive, reproductive and behavioral traits (such as body size, mothering ability, twinning rate, kidding interval and temperament) while in group-animal ranking experiment, there was a general tendency to focus on observable physical traits like coat color, body size and body conformation. Simultaneous use of both own-flock and group-animal ranking experiments is advisable to identify breeding objective traits in production systems where record keeping is absent.

SUBMITTER: Sheriff O

PROVIDER: S-EPMC7993801 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The aim of this study was to identify breeding practices and trait preferences for indigenous sheep in three districts (Estie, Farta and Lay Gayient) located in the northwest highlands of Ethiopia. Questionnaire survey and choice experiment methods were used to collect data from 370 smallholder farmers. Respondents were selected randomly among smallholder farmers who own sheep in the aforementioned districts. A generalized multinomial logit model was employed to examine preferences for sheep attributes, while descriptive statistics and index values were computed to describe sheep breeding practices. Having the highest index value of 0.36, income generation was ranked as the primary reason for keeping sheep, followed by meat and manure sources. The average flock size per smallholder farmer was 10.21 sheep. The majority of the smallholder farmers (91%) have the experience of selecting breeding rams and ewes within their own flock using diverse criteria. Given the highest index value of 0.34, body size was ranked as a primary ram and ewe selection criteria, followed by coat color. Furthermore, choice modeling results revealed that tail type, body size, coat color, growth rate, horn and ear size have shown significant influences on smallholder farmers' preference for breeding rams (P<0.01). The part-worth utility coefficients were positive for all ram attributes except ear size. For breeding ewes, mothering ability, coat color, body size, lambing interval, growth rate, tail type and litter size have shown significant effects on choice preferences of smallholder farmers (P<0.05). Moreover, significant scale heterogeneity was observed among respondents for ewe attributes (P<0.001). Overall, the results implied that sheep breeding objectives suitable for the northwest highlands of the country can be derived from traits such as linear body measurement, weight and survival at different ages, and lambing intervals. However, selection decisions at the smallholder level should not only be based on estimated breeding values of traits included in the breeding objective but instead, incorporate ways to address farmers' preference for qualitative traits.

Project description:BackgroundDue to its climate-sensitive agricultural system and low adaptive capacity of the subsistence farmers, Ethiopia is cited among the countries experiencing frequent drought and highly vulnerable to climate change associated impacts. Micro level vulnerability assessment, in the context of a changing climate, has a paramount significance in designing policies addressing climate change induced effects. Assessing vulnerability to climate change is important for defining the risks posed by the change and it provides a starting point for the determination of effective means of promoting remedial actions to minimize impacts by supporting coping strategies and facilitating adaptation options targeted at specific context.MethodsWe employed cross-sectional survey research design has to examine the extent of livelihood vulnerability of 384 randomly selected smallholder farmers from three agroecologies which was supplemented by interviews. Livelihood vulnerability index, using integrated indicator approaches and principal component analysis, has been used. Chi-square test, F-test and t-test were used to examine association and mean differences among three agroecologies and between cropping types in terms of different attributes.FindingsOverall, smallholder farmers living in kolla agroecology were found to be the most vulnerable to climate change induced hazards followed by dega. In terms of type of cropping season, belg dominated areas were relatively more vulnerable than those residing in meher dominated areas. Different biophysical and socio-economic attributes contributed their own role both for exposure, sensitivity and adaptive capacity differences among smallholder farmers farming in different agroecologies and different types of cropping seasons.ConclusionWe recommend that interventions undertaken to lessen the impact of climate change should be targeted to the factors which contribute to high extent of sensitivity and for those which could enhance the adaptive capacity of smallholder farmers. Specifically, we suggest that resilience-building adaptation interventions like expansion of small-scale irrigation, accessing of microfinance service, early warning and timely information, extension support, non-farm sources of income, training and skill development, expansion of infrastructure have to be promoted thereby increase the adaptive capacity of subsistence rainfed-dependent farmers to withstand the vagaries of the climate variability risk. Moreover, disparities in the same agroecology have to be addressed properly in livelihood vulnerability discourse.

Project description:BackgroundBreeders and geneticists use statistical models to separate genetic and environmental effects on phenotype. A common way to separate these effects is to model a descriptor of an environment, a contemporary group or herd, and account for genetic relationship between animals across environments. However, separating the genetic and environmental effects in smallholder systems is challenging due to small herd sizes and weak genetic connectedness across herds. We hypothesised that accounting for spatial relationships between nearby herds can improve genetic evaluation in smallholder systems. Furthermore, geographically referenced environmental covariates are increasingly available and could model underlying sources of spatial relationships. The objective of this study was therefore, to evaluate the potential of spatial modelling to improve genetic evaluation in dairy cattle smallholder systems.MethodsWe performed simulations and real dairy cattle data analysis to test our hypothesis. We modelled environmental variation by estimating herd and spatial effects. Herd effects were considered independent, whereas spatial effects had distance-based covariance between herds. We compared these models using pedigree or genomic data.ResultsThe results show that in smallholder systems (i) standard models do not separate genetic and environmental effects accurately, (ii) spatial modelling increases the accuracy of genetic evaluation for phenotyped and non-phenotyped animals, (iii) environmental covariates do not substantially improve the accuracy of genetic evaluation beyond simple distance-based relationships between herds, (iv) the benefit of spatial modelling was largest when separating the genetic and environmental effects was challenging, and (v) spatial modelling was beneficial when using either pedigree or genomic data.ConclusionsWe have demonstrated the potential of spatial modelling to improve genetic evaluation in smallholder systems. This improvement is driven by establishing environmental connectedness between herds, which enhances separation of genetic and environmental effects. We suggest routine spatial modelling in genetic evaluations, particularly for smallholder systems. Spatial modelling could also have a major impact in studies of human and wild populations.

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Phenotypic ranking experiments in identifying breeding objective traits of smallholder farmers in northwestern Ethiopia.

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