Women empowerment through increasing the access of resources in local situation is the highlighted issue in the present context. Women involve in different types of activities in agricultural sphere and shoulder the responsibility in playing the roles of different actors in agricultural innovation system. The dimension of agricultural innovation always prefers to go along with the concepts of the dynamics around different activities and roles that poor women communities engaging towards addressing their social and economic needs through agricultural production system.
Global technology education is largely dominated by Western universities. Students from developing countries face an enormous challenge when moving from their local education system into the competitive international education market. Their local knowledge gets lost in a foreign education system where the students are required to acquire a new set of skills. This paper presents a survey among international technology students that highlights the differences.
This publication contains twelve modules which cover a selection of major reform measures in agricultural extension being promulgated and implemented internationally, such as linking farmers to markets, making advisory services more demand-driven, promoting pluralistic advisory systems, and enhancing the role of advisory services within agricultural innovation systems.
This brochure presents startup profiles, an incubatee coffee table book which captures the brief profile of agriculture startups being incubated at a-IDEA, the Technology Business Incubator of National Academy of Agricultural Research Management (ICAR-NAARM) supported by Department of Science & Technology of India. The incubation centre at NAARM is providing a conducive environment for growth of startups in agriculture.
The impact of the COVID-19 pandemic will vary for different groups of rural population, with the highest impact expected to be on farmers and other vulnerable groups, especially women and youth. Targeted support is feasible only by activating a network of actors or organizations within agricultural innovation systems (AIS) and promoting customized technologies and practices suitable for location specific contexts.
Due to the increasing gap between input costs and the final prices they receive for their produce, Indian farmers have been increasingly affected by the current agrarian crisis. It is within this context that Zero Budget Natural Farming (ZBNF) - a farming method promising low to zero input costs - has been gaining momentum.
Zero Budget Natural Farming (ZBNF) is a set of farming methods, and also a grassroots peasant movement, which has spread to various states in India. It has attained wide success in southern India, especially the southern Indian state of Karnataka where it first evolved. The movement in Karnataka state was born out of collaboration between Mr Subhash Palekar, who put together the ZBNF practices, and the state farmers association Karnataka Rajya Raitha Sangha (KRRS), a member of La Via Campesina (LVC).
In the light of ongoing debates about the suitability of proprietary seed technologies for smallholder farmers, this paper analyzes the adoption and impact of hybrid wheat in India. Based on survey data, we show that farmers can benefit significantly from the proprietary technology. Neither farm size nor the subsistence level influences the adoption decision, but access to information and credit does. Moreover, willingness-to-pay analysis reveals that adoption levels would be higher if seed prices were reduced.
This article adds to the literature about the impact of social networks on the adoption of modern seed technologies among smallholder farmers in developing countries. The analysis centers on the adoption of hybrid wheat and hybrid pearl millet in India. In the local context, both crops are cultivated mainly on a subsistence basis, and they provide examples of hybrid technologies at very different diffusion stages: while hybrid wheat was commercialized in India only in 2001, hybrid pearl millet was launched in 1965.
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.