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Rural households depends on agriculture for their livelihood and agriculture is not able to provide adequate and sufficient livelihood to the growing population so rural people have to supplement or to find alternative practices to protect their livelihood security. Self Help Group and Micro finance creates an impact on the rural livelihood by reducing poverty and empowering women. Social and economic empowerment leads to development and the development relieves people from poverty. This paper discuss about the status of Self Help Group in India, Tamil Nadu and Vellore District in the first section and next section covers the sustainable alternative livelihood practice followed by the members of the Self Help Groups with the guidance of Non Governmental Organisations/Voluntary Associations and banks in Vellore District. This new alternative livelihood activities supplemented some family’s main income and it became the main source of livelihood to some families. This article explains the diverse and diversified sources of livelihood in Vellore District.

Indian society in multifaceted to an extent perhaps unknown in any other of the world’s great civilizations. Urban-rural differences can be immense. About 74 percent of India’s population like in villages, with agriculture providing support for most of these rural residents, and the socio economic status of rural India are not so good. Maximum number of people in village lives under poverty line. So research is very necessary for rural India. To know the status of villages. Through research Government or private organization known the problems of rural India. Indian Village life is a mixture of tranquility, sensitive, quietude and innocence. And the primary occupation of the people living in the villages is agriculture and is therefore reckoned as an unchangeable part of the village culture. Villages face many problems in their daily life. Current paper focuses on rural household revenuers and their expenditure.

South Sudan faces serious problems of food insecurity due to low per capita levels of domestic food production, periodic droughts, widespread poverty, political unrest, and since late 2013, renewed armed conflict. Agricultural productivity is low, and the country is highly dependent on private-sector imports of cereals (maize, sorghum, wheat, and rice) from Uganda to supply domestic markets. National household survey data indicate substantial diversity in consumption of cereals across households, and our econometric estimates suggest highly price- and income-inelastic demand for the two major cereals, sorghum and maize. Drawing on a review of international experience and the constraints facing South Sudan, we conclude that a national food security reserve (NFSR) system with a small national food security stock is feasible for South Sudan. Cereal stocks would be kept mainly for targeted safety nets and emergency distribution, and market interventions would be limited in scope, in keeping with a long-run goal of market development. Nonetheless, even with a functioning NFSR, promotion of private-sector domestic and import trade will remain crucial for ensuring adequate supplies of grain and food security

AbstractThis paper assesses key issues in the dispute over the United States’ claim that for certain grains China exceeded its limits on domestic support under the Agreement on Agriculture (AoA) during 2012–2015. The panel first determined that the base years for the reference price in calculating China's market price support were 1996–1998, rather than 1986–1988 as stipulated in the AoA, and that production in the geographic regions where the support programs operated, not the smaller quantities purchased at administered prices, constituted eligible production. The panel then found China had exceeded its limits in each of the four years for wheat, Indica rice, and Japonica rice. The possibility was left open that a government can determine eligible production by setting maximum purchases at support prices in its regulatory framework. China used this option to claim that its programs for 2020 implemented the recommendations and rulings of the DSB. We argue that use of outdated fixed external reference prices to measure the price gap and to define eligible production by limits on purchases, distance calculation under the AoA from economic support measurement. The measurement issues compound the discord among Members over levels of agricultural support.

Pseudoamblystegium subtile (Hedw.) Vanderp. & Hedenäs. CONTRIBUTORS: R. Gabriel, M. Kubová, C. Sérgio and I. Soares Albergaria. PORTUGAL, AZORES: Terceira Island, Angra do Heroísmo, municipal garden ‘Jardim Duque da Terceira’, 38° 39′ 24.0′′N, 27°13′ 05.99′′W, 31 m a.s.l, on the base of a shrub, in acidic conditions, 7 April 2017, leg. Michaela Kubová s.n. (AZU). A new understanding of the pleurocarpous moss species Pseudoamblystegium subtile was proposed by Vanderpoorten and Hedenäs (2009). The new genus is separated from the other Amblystegiaceae primarily due to its phylogenetic consistency and is characterised by the possession of leaves with a very short nerve, and erect capsules (Vanderpoorten and Hedenäs 2009). (excerpt) info:eu-repo/semantics/publishedVersion

In inclusive population growth, providing food and water is the toughest challenge that most of the countries are facing today. Changing climate conditions leads to challenges in agriculture production and food security all around world. Most of African countries facing savior challenges in agriculture production and climate change will be likely to reduce the length of growing season as well as force large regions of marginal agriculture out of production. Projected reductions in yield in some countries could be as much as 50% by 2020 and crop net revenues could fall by as much as 90% by 2100, with small-scale farmers being the most affected. This would adversely affect food security in the continent. About 25% of Africa’s population (about 200 million) is currently experiencing high water stress and it could increase by 75-250 million and 350-600 million by 2020’s and 2050’s respectively. Similarly, in Asia there is 2.5 to 10% and 5 to 30% decrease in crop yield in 2020’s and 2050’s as compared with 1990 level without CO2 effects. Food security and water stress in most of the continent can become the cause of geopolitical peace conflict. At the local level, policies could help to solve these global challenges. The Gandhian concept of 'Gram Swaraj' advocated self-sufficient village republics, which produce their own food and cloth, remain independent of the neighbors for vital wants, and yet interdependent for other needs. Conservation practices in villages will have its own waterworks, ensuring clean water supply which provides about 10% conservation into water as well as food. This paper explains the relevant concepts from simple Gandhian principles and practices which leads to Jal Swaraj (Water Sovereignty) and Beej Swaraj (Seed Sovereignty).

International audience; The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregon, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with mid-century climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments. (C) 2012 Published by Elsevier B.V.

Smart cities use technology to enhance living, to reduce costs and resource consumption, and to mingle more effectively and actively with their citizens. Smart sectors include transport, energy, health care, education, social programs, water and waste. Smart city is a term we are going to be hear a lot more of in the future. It’s thought that by 2020 we will be spending lots of money in a year building them. This paper gives a brief explanation about the applications of IoT and Big data in building Smart cities.

The assessment of harvest yield is finished utilizing the information got from satellite pictures and the verifiable information about the yield. At first the satellite pictures of the yields are gotten by choosing the time and date of the pass of satellite on the investigation territory and afterward getting the pictures from satellite of harvest in the examination region this should be possible utilizing satellite like LANDSAT, SENTINEL, IKONOS, and so forth The satellite pictures should be preprocessed to eliminate commotion and undesirable regions. With the assistance of GPS (Global Positioning System) the preparation tests or Ground Truth Points are chosen which is needed for Supervised Classification. To characterize the satellite picture the product utilized is GIS (Geographical Information System). QGIS is a high level variant of GIS device which is utilized to chip away at satellite pictures. The satellite pictures are broken down utilizing QGIS and the information, like NDVI (Normalized Difference Vegetation Index), Rainfall, Temperature, and so on, are removed or estimated from satellite pictures. Python is utilized to deal with the information got from the satellite pictures and furthermore on the information of harvest yield from bygone eras to eliminate any inconsistencies or excess information. Presently, to anticipate the yield of harvest for quite a long time 2020 and 2021the Machine Learning Algorithm of Regression Modeling is executed on both the information from satellite pictures and the verifiable yield of yield in the investigation region. The anticipated yield of both satellite information and recorded information is looked at and the general exactness is found.