Based on three rounds of panel data (2007, 2009, and 2012) on indigenous households, this study assessed the impacts of Integrated Aquaculture-agriculture value chain participation on the welfare of marginalized poor indigenous rural households in Bangladesh. We also examined the distributional impacts of IAA value chain
The field of precision agriculture increasingly utilize and develop robotics for various applications, many of which are dependent on high accuracy localization and attitude estimation. Special attention has been put towards full attitude estimation by low-cost sensors, in relation to the development of an autonomous field robot. Quaternions have been chosen due to its continuous nature, and with respect to applications in the pipeline with on other platforms.
Le Tuy, province de l'Ouest du Burkina Faso est une région soudanienne à forte pression démographique et pastorale où se posent avec acuité des problèmes de fertilité des sols. Face à la dégradation des ressources naturelles, opter vivre dans son milieu natal et s'assurer une bonne production agropastorale nécessite de la part des acteurs des actions concertées. Le projet Fertipartenaires aide les producteurs de cette province à se concerter, à réfléchir à leurs problèmes, proposer et expérimenter des solutions et les évaluer afin d'améliorer leur sécurité alimentaire.
This workshop paper relates to the consultation organized by the Global Forum for Agricultural Research (GFAR), FAO of the UN (FAO), Asia-Pacific Association of Agricultural Research Institutions APAARI), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT). Consultation held at ICRISAT, Hyderabad, India, in December 2009. The paper focuses on the application of the ICTS in agriculture and agricultural development and includes the summary of workshop outputs and pre-workshop Think Pieces.
The present study considered the current state of internet of things in Nigeria, future prospects and challenges to the usage of the technology in Nigerian Agriculture. In Nigeria, IoT has been used to dispense feed and water to chicks, virtual fences for monitoring farmlands and forest trees, cashless sales and purchases of farm produce and input, monitoring and management of staff performances on the farm and e-wallet for input, loan and information accessibility on agricultural issues.
This paper introduces a practical e-learning system, identified as Knowledge Exchange E-learning System (abbr. KEES), for knowledge distribution in rural areas. Particularly, this paper is about providing a virtual teaching and learning environment for small holders in agriculture in those rural areas.
This research is dedicated to illuminating the relationship between knowledge and innovation within agrifood supply chains (ASCs) – although insightful and informative – is marked by conceptual and methodological issues that restrict our ability to understand the ways knowledge affects innovation and vice versa. In this work, adopting a systems approach to ASCs and synthesizing literature from different fields of study, we discuss the metaphors that guide research in this area, and we propose an alternative conceptualization of ASCs
In direct agri-food chains (DAFCs), farmers and consumers are brought together with the aim of shortening, localizing and synergizing an agri-food chain. As food moves from the farm to the fork, all the economic activities are performed by farmers/producers or consumers, and none intermediary is required to handle an agri-food product before it is consumed. Any DAFC form provide a sort of liminal space for social learning and for local lay knowledge exchange, through face-to-face interactions.
Este artículo explora, partiendo de la base de una perspectiva de “sistemas de innovación”, algunas oportunidades promisorias para los especialistas en información y comunicación.
In this paper, a novel method to collect symptoms of the disease, as observed by the farmers, using a mobile phone application has been presented. A cumulative composite risk index (CCRI) obtained from more than one existing disease forecast models is validated from the actual late blight queries received from the farmers. The main contribution of the paper is a protocol that combines the symptoms based diagnostic approach along with the plant disease forecasting models resulting in detection of Potato late blight with higher accuracy.