The Agriculture Technology Program for Turkmenistan (AgTech), funded by USAID and implemented by Weidemann Associates, Inc., aims to increase and develop private enterprises, and improve productivity of private, small and household farms. The project has two key components: the improvement of genetics, education and organization as a means of increasing the incomes of private agribusiness involved in livestock; skills building for private producers, processors and marketers of fruits and vegetables.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
ICARDA scientists along with CGIAR LIVESTOCK developed a cloud-based genetic database platform to boost breed improvement programs in community-based livestock breeding programs in Ethiopia.
Genetic improvement on local breeds kept by small farmers in developing countries is challenging. Even though good pedigree and performance recording is crucial and an important component of breeding programs, it remain difficult or next to impossible under conditions of subsistence livestock farming. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
Breeding programs for local breeds kept by small farmers in developing countries are a major challenge. Animal recording of pedigree and performance under conditions of subsistence livestock farming is remain difficult or next to impossible. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
- Lack of automated data capture systems affects timely feedback and accuracy of information for breeding decisions.
- CGIAR researchers and national research partners have adopted a digital genetic database, Dtreo, that is enhancing genetic improvement by providing timely and accurate animal ranking information to communities.
- Dtreo is a digital genetic database that is flexible and easy to use, that allows users to capture and save data offline. Data is uploaded to the database once an internet connection has been established.
This Working Paper summarizes the key activities and achievements of the HSAD-Iraq program Harmonized Support for Agriculture Development 2013-2014. It was compiled from reports and technical information documenting project work in sites in Southern, Central and Northern Iraq. The main topics covered by the training courses were: Integrated Pest Management; Water Management; Biotechnology; Information and Communication Technology; Capacity Building; Livestock Management and Tools & Technologies
Capacity development interventions in support of agricultural innovation are more effective when based on systematic and participatory assessments of existing skills and capacity needs. Recognizing that, an instrument has been developed in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. It consists of a capacity scoring tool that allows assessing innovation capacities, identifying strengths and weaknesses and monitoring capacity changes over time. This paper describes the scoring tool and provides guidelines on how to apply it successfully.