- 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.
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.
The aim of this paper is to propose an innovative operational framework that couples life cycle assessment (LCA) and a participatory approach to overcome these issues. The first step was to conduct a progressive participatory diagnosis of the socio-ecological structure of the rural territory and to characterise the main cropping systems. The results of the diagnosis and other data were progressively triangulated, validated and consolidated with the stakeholders at the territorial level. The paper discusses the quality and validity of data obtained using a participatory approach.
Learn about the Women’s Empowerment Farmer Business Schools (WE-FBS) implemented in Kenya through FAO’s Flexible Multi-Partner Mechanism (FMM). The approach prompts men and women to reflect critically on their roles, resources, and activities in farming, and to develop strategies that are needed to maximize their commercial potential.
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.
The first part of the working document on the global strategy brings together the ideas of some 40 experts involved in gender and participatory research who took part in the workshop ‘Repositioning Participatory Research and Gender Analysis in Times of Change’ in Cali, Colombia (June 16–18, 2010).The workshop participants firmly believe that gender responsive participatory research (GRPR) offers some of the most powerful and useful approaches for achieving sustainable development, including alleviating poverty, improving well being, achieving sustainable levels of natural resource use, and
The Guide to Effective Collaborative Action is built on the foundation of 10 years' experience in transforming food and agricultural commodity systems by UNDP's Green Commodities Programme. It is broadening the application from support to commodity production to the transformation of food systems. The four building blocks of putting systems change into practice, integrated with backbone support and essential practices for stakeholder actions, provide a framework for Changing Systems through Collaborative Action.
During May 2010 the International Centre for Tropical Agriculture (CIAT) hosted two events related to knowledge management (KM): The Knowledge Share Fair for Latin America and the Caribbean, funded by the Food and Agriculture Organization of the United Nations (FAO), and a regional meeting of the Knowledge Management for Development (KM4Dev) community. The Fair was attended by 200 professionals from more than 70 organizations and 18 countries and showcased more than 40 experiences related to KM in agriculture, development and food security.
Fall Armyworm (Spodoptera frugiperda), or FAW, is an insect native to tropical and subtropical regions of the Americas. In the absence of natural controls or good management, it can cause significant damage to crops. It prefers maize, although it can feed on more than 80 additional species of crops including rice, sorghum, millet, sugarcane, vegetable crops and cotton.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.