Este miembro participó en las siguientes discusiones
This is just to add a little more to the great effort of SFS draft 1.0.
Interconnected policy-making: Enabling decisions related to sustainable food system together with agriculture and its products marketing, labour laws, land holding, rural development etc.
The above is just what I could conceptualised on my own.
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Good evening from India!
Agro-ecological zoning separates areas into the region at the apex level and agro-eco unit at the bottom. The agro-ecological region identifies the natural resources in terms of problems, potentialities and constraints and their extent with respect to land utilization types and groups them in uniform units. Digital database in GIS and application of logic through decision support system (DSS) further enhance the process and precession of agro-ecological delineation. The sub agro ecological regions are further subdivided into agro-ecological zones based on landforms, soil association and land use. The agro ecological zones have further taken down to sub zones depending on terrain characteristics, parent materials, soil texture, depth, salinity, surface and ground water potentiality and cropping pattern.
Also we may think for overlaying vulnerability map with such agro ecological zones to create polygons in GIS and use the same to predict food security as well as systems need to be followed in long run for food sustainability.
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I would like to provide the following info:
Traditional Knowledge based Solution to address water scarcity: Climate change is a defining moment of our time with major negative implications on ecology, human culture, livelihoods and food security. The IPCC advocates to search local solutions for climate change adaptations; however, its report does not recognize the breadth and strength of century tested traditional knowledge in combating climate change. Major water concerns are (1) Most critical resource for Indian agriculture; (2) The resource is shrinking; (3) Increased competition from other sectors; (4) Decline in water table; (5) Water-logging and salinity; (6) Increased pollution; (7) Environmental change to affect availability; and (8) Reduction in river flow. The emerging scenario from different parts of the globe suggests that neither the scientific technologies alone nor the traditional knowledge exclusively can completely solve the threats of food and nutritional security challenges emanating from climate change, however, a fusion of the two can. Traditional Knowledge can be defined as the collectively owned non-formal intellectual property comprised wisdom, knowledge and teaching developed by local and indigenous communities over time in response to the needs of their specific local environment and integral to the cultural or spiritual identity of the social group in which it operates, preserved and many-a-time orally transmitted for generations. Traditional water management practices include Stone Bunding, Stones-cum-Earthen Bunding, Stone-cum-Vegetative bunding, Brushwood Waste Weir, Grassed Waterways and Spur Structure. The planners and policy makers have yet another tool and dimension to initiate participatory action plan involving tribal farmers and their rich reserve of traditional knowledge in order to develop adoptable technology that will enable mitigation of water scarcity and problem of climate change for financial inclusion and mainstreaming of indigenous population. The study described in the paper conclusively proved that planners and policy makers have yet another tool and dimension to initiate participatory action plan involving tribal farmers and their rich reserve of traditional knowledge in order to develop adoptable technology that will enable mitigation of water scarcity amd problem of climate change for financial inclusion and mainstreaming of indigenous population. Moreover, region-specific amalgamated technological prescriptions refined with targeted policy analysis are required for effective implementation and obtaining positive outcomes within a finite time horizon.
Reference: Dey, P. and Sarkar, A.K. (2011). Revisiting indigenous farming knowledge of Jharkhand (India) for conservation of natural resources and combating climate change. Indian J. Traditional Knowledge 10(1): 71-79.
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Management of Potassium (K) bearing fertilisers requires to consider the following approach:
Balancing external application of potassium (K) fertilizers and utilization of soil reserve K is an important aspect of plant K-nutrition as rapid depletion of soil reserve K has negative consequences on soil quality and crop productivity. The critical limit of exchangeable K varies for soil to soil and crop to crop although K-rating limits are irrespective of crops or soils. Moreover, supply of soil K to plants is a complex phenomenon involving dynamic equilibrium among its various chemical forms. The K response in vertisols is often anomalous. These limits in Vertisols are not only higher but differ considerably from crop to crop and location to location. It was found the range of critical limit as 451-799 kg/ha, the lowest being for oilseed crops and highest for vegetable crops. The critical limits obtained from LTFE experiments is at around 315 kg K/ha for some Vertisols. The higher critical limits from soil test crop response experiments are because of the higher yield targets taken in calculating the critical limits. Such higher yield targets are seldom obtained in LTFE trials. Also, there is a difference in the way the calculations are made. The critical limit for rice is 553 kg/ha (range 250-796 kg/ha). There is ample opportunity to increase rice yield in Vertisols if K fertilization is done based on soil test. Experiments done under AICRP (STCR) have shown that the fertilizer K requirement is 34 kg K2O/ha at a soil test value of 350 kg/ha for achieving the yield target of 50-60 q/ha for rice, and this requirement changes to 26 kg, and 19 kg if the soil test values are 400, and 450 kg/ha, respectively. Wheat requires almost similar K fertilization as rice. The K fertilizer requirement for maize crop is much less though. It is only 16 kg K2O/ha at a soil test value of 400 kg/ha and 11 kg K2O/ha at a soil test value of 350 kg/ha. The recommendations for cotton is 38 kg K2O/ha. The K requirement is very high in Maharashtra, and almost nil in Karnataka. Such results are difficult to interpret only on the basis of exchangeable K. Vertisols have also been categorized on the basis of non-exchangeable K content.
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Crop cultivation is a complex process and involves a set of activities like land preparation, planting, pest control, irrigation, nutrient management, harvesting, marketing, etc. The entire cycle of crop production requires multitude of information by the farmers. Despite many efforts over the years to disseminate and transfer agriculture knowledge to the stakeholders, large amounts of expertise and knowledge are still out of reach to most of them. Agriculture knowledge may be contained in the corporate database, or it may reside undocumented inside the brain of the researchers or even stored in locations unknown to the majority of the people in the organization. Large sections of the farming community, particularly the rural folk, do not have access to the huge knowledge base acquired by agricultural universities, extension-centers and businesses. In this respect the main challenge is to find this knowledge and apply it to the decision making process involved in agriculture development. The main issue now is for organizations to recognize, locate and utilize this specialized knowledge; currently embedded in organizational databases, processes and routines as a distinct factor of production to increase productivity and competitiveness. Knowledge management is one of the tools for organizations to achieve the capabilities mentioned above to enable them to remain competitive in this fast changing world.
Knowledge Management Requirements in Agriculture
While formulating Third National Agricultural Policy in 1999, Ministry of Agriculture of Malaysia opined that knowledge is a fluid mix of contextual information, values, experience and rules. Knowledge Management (KM) is a term applied to techniques used for the systematic collection, transfer, security and management of information within organizations [Gerhard, 2006]. Process consists of collecting, organizing, classifying and disseminating information throughout an organization, so as to make it purposeful to those who need it [Albert, 1998]. Knowledge management in general tries to organize and make available important know-how, wherever and whenever it’s needed. This includes processes, procedures, patents, reference works, formulas, best practices, forecasts and fixes. Function of knowledge management is to allow an organization to leverage the information resources it has and to support purposeful activity with positive definable outcomes.
To apply these strategies in agriculture domain, there is need to have idea about what are information requirements of the grower, which are not handy and requires application of knowledge management. Information need of farmers during entire cycle of crop production may be broadly categorized [Hasan and Isaac, 2008] into Input procurement and marketing, Strategic Information, Past Trends, and Government Policies.
Input Procurement and Marketing
Farmers frequently seek information regarding various inputs needed in their field such as seed, fertilizers, pesticides, labour, transport, etc in terms of cost, quality, availability and possible sources. Once crop gets ready for harvesting, need arises for its marketing. The questions like; where to sale, when to sale, how to sale and whom to sale mesmerizes the farmers. At this point of time, information provision related to marketing and transportation is must, which may help farmers in decision-making of agriculture product marketing.
There are several stages where farmer requires information to strengthen the planning and minimizing risk of cultivation. Information related to cultivation practices such as varietal characters, fertigation schedule, pest control methods, irrigation schedule, mechanization, planting and harvesting schedule, inter-cropping, crop rotation, etc may be classified under strategic information. Information about most suitable production and protection technologies is required for optimum and sustainable crop production.
Information on past trends regarding area, production, productivity, consumption, utilization, pest attack, climatic conditions, environmental concerns, fertigation, etc are of immense use in making decision in crop production. For example, past trends in climatic conditions may help growers in scheduling cultivation activities for optimum production and control of stresses.
Government Policy decisions
Government decisions related to agriculture and its products marketing, labour laws, land holdings, rural development etc is also important factors while taking decision. All such information must reach to the farmers at the earliest, so that one may take right decision for high production and maximum return. Many IT tools are available to record and disseminate information for decision support. Making available the information about government policies and support facilities to the farmers in time will empower the farmers in the way to their prosperity.
Harnessing the indigenous technical knowledge
Farmers in different parts of the world especially in poor and marginal indigenous groups of south Asia and Africa are experimenting with the agricultural adaptation measures in response to climatic variability for centuries. There is a wealth of knowledge for a range of measures that can help in developing agri-technologies to overcome climate vulnerabilities. Research works from plateau region clearly demonstrate that indigenous people and their knowledge are central to the adaptive changes for sustainable agriculture using available natural resources essential to face the world’s changing climate (Dey and Sarkar, 2011). There is a need to harness and manage such knowledge and fine-tune them to suit the modern needs.
ICT Tools and Techniques for Knowledge Management
Information and communications technologies are an important ingredient of virtually every successful knowledge management program. Sadaan  has identified five essential categories of technology requirement in agricultural research and development for knowledge management viz. business intelligence, collaboration, knowledge transfer, knowledge discovery and expertise location. A variety of ICT tools are available for knowledge management in agriculture. An effective knowledge management in crop production and protection will involve an integrated approach of various ICT tools and techniques. Here we discuss some of key ICT technologies considered for knowledge management in crop cultivation.
Database & Data Warehouse
Database and data warehouse technologies [Chaudhari et al. 2001; Hipsley, 1996; Humpshires, 1999; Ralph, 1998] are used to store and retrieve large amount of data (both text and image) efficiently at affordable cost. Temporal / historical data on crop production, protection and utilization statistics, meteorological facts and pest / disease survey data and other useful data may be managed using these repositories for further analysis and decision support.
Data Mining, OLAP and analytical techniques
Data Mining and OLAP techniques [Ganti et al. 1999; Humpshires, 1999; Monte, 2001; Ralph, 1998] make it possible to extract new finding and meaningful patterns from large historical database. Based on these analytical techniques useful advices can be developed for farmers.
An Expert System is an intelligent computer program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solution. Expert in crop production and protection are the modern extension tools for decision support at farmer level. It can suggest suitable variety, method of field preparation & sowing, irrigation, fertilizer application, etc. Disorder diagnosis and treatment are one of oldest application of expert system.
GIS / GPS
A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, globes, reports, and charts. Major application of GIS in agriculture includes land use analysis, thematic mapping, demographic analysis, socio-economic studies and environment management.
Internet / Intranet
Internet technology [Agarwal, 1999; Bennett, 1996] has revolutionized the world of information communication. With this the information dissemination to farming community can be made instantaneously in parallel. Further this technology provides a powerful collaboration mechanism for knowledge sharing using WWW, Email, Chatting, News Group, etc.
Simulation and Modeling
Modeling and simulation technology can be used to model an ideal crop situation and predict its growth through extrapolation and other techniques by considering a specific crop environment. Crop Simulation Models [Singh, 1994] can be developed for environmental characterization, optimizing crop management, pest / disease management, impact study of climate change, yield forecasting, effective crop scheduling, etc.
Multimedia means many media – text, video, narrated sound, music, graphics, animations, special effects, etc. which are controlled, coordinated and integrated by a computer. Multimedia is simply multiple forms of media integrated together. Multimedia based Instructional Tools, Encyclopedia, Tutorials, Videos, etc not only give enhancement over text only messages but also improves understanding and retention of information.
Knowledge management initiatives in agriculture domain
The USDA Forest Service and Environmental Protection Agency have cooperatively developed a knowledge base for assessment and monitoring of ecological states and processes in sixth-code watersheds. The knowledge base provides a formal logical specification for evaluating watershed processes, patterns, general effects of human influence, and specific effects on salmon habitat. The system integrates geographic information system and knowledge base system technologies to provide an analytical tool for environmental assessment and monitoring. The basic objective is to improve the quality and completeness of environmental assessments and the efficiency with which they are performed [Reynolds et al. 2000].
FarmNet is a network of rural people and supporting intermediary organizations, such as extension services, using ICTs and conventional communication media to facilitate the generating, gathering and exchanging of knowledge and information. Operated by farmers and their organizations, FarmNet (http://ftp.fao.org/sd/farmnet.pdf) links farmers to each other and to the resources and services that they need to improve their livelihoods through agricultural productivity, profitability and food security.
aAQUA is an online multilingual, multimedia Agricultural portal for disseminating information from and to the grassroots of the Indian agricultural community. aAQUA simultaneously addresses two major challenges in farmer outreach programs - geographic reach and customized delivery. It answers farmers queries based on the location, season, crop and other information provided by farmers. Agricultural content repositories (Digital Library), Agri-price information (Bhav Puchiye), farmer schemes and various operations support databases (aAQUA-QoS) have also emerged from the experience of aAQUA deployments. aAQUA's large scale deployment provides avenues for researchers to contribute in the areas of knowledge management, cross-lingual information retrieval, and providing accessible content for rural populations [Ramamritham, 2006].
Wen  presents a knowledge-based intelligent e-commerce system for selling agricultural products. The KIES system not only provides agricultural products sales, financial analysis and sales forecasting, but also provides feasible solutions or actions based on the results of rule-based reasoning. The intelligent system integrates a database, a rule base and a model base to create a tool of which managers can use to deal with decision-making problems via the Internet. For offering convenient delivery and user-friendly services to customers, an e-map combined with a GPS is used.
LPCUBE Wise Agri KM™ is an innovative knowledge management solution designed for the agriculture industry. It enriches research and helps researchers to share knowledge and reuse the lessons learned. The collective knowledge base built using this platform can be used to disseminate right knowledge to the farmers at the right time. It enriches farming and ultimately improves agriculture productivity.
Agricultural Information Management Standards (AIMS), website http://www.fao.org/aims/index.jsp, is a portal whose main objectives are: to facilitate collaboration, partnership and networking among partners by promoting information exchange and knowledge sharing; and to harmonize the decentralized efforts currently taking place in the development of methodologies, standards and applications for management of agricultural information systems; consequently, providing a 'one-stop' access to system designers and implementers.
Agarwal, P.K. 1999. Building India's national Internet backbone. Communications of the ACM, 42 (6): 53-58.
Albert, S. 1998. Knowledgement Management: Living up to the hype? Midrange Systems, 11(13): 52.
Bennett, F. 1996. The Internet Roadmap, 3rd Edition, Sybex/BPB Publication, San Francisco.
Chaudhuri, S., Dayal, U. and Ganti V. 2001. Database Technology for decision support systems, Computer, 34: 48-55.
Dey, P. Hasan, S.S. and Kumar, Sanjeev (2013). Strategies for Knowledge Management in Agriculture Domain. In: Information and Knowledge Management: Tools, Techniques and Practices (Ed. A.K. Roy), ISSN No. 978-93-81450-62-8. New India Publishing Agency, New Delhi, pp. 455-461.
Dey, P. and Sarkar, A.K. (2011). Revisiting indigenous farming knowledge of Jharkhand (India) for conservation of natural resources and combating climate change. Indian J. Traditional Knowledge 10(1): 71-79.
Ganti, V., Gehrke, J. and Ramakrishnan, R. 1999. Mining very large databases, In: Proc. IEEE Computer, pp. 38-45.
Gerhard, M. 2006. Knowledge Management as a useful tool for implementing projects. Proc. FIG Workshop on eGovernance, Knowledge Management and eLearning, Budapest, Hungary, pp. 215-222.
Hasan, S.S. and Isaac, R.K. 2008. ICT for Sugarcane Farmers, Information for Development (i4d), March, pp. 27-28.
Hipsley, P. 1996. Developing Client / Server Applications with Oracle Developer / 2000, Tech Media, Sams Publishing, USA.
Humpshires, H. 1999. Data Warehouse Architecture & Implementation, Prentice-Hall Publication, New Jersey.
Ralph, K. 1998. Data Warehouse Lifecycle Toolkit, Wiley Computer Publishing, New York.
Ramamritham, K., Bahuman, A., Duttagupta, S., Bahuman, C. and Balasundaram, S. 2006. Innovative ICT Tools for Information Provision in Agricultural Extension. Proc. 15th international conference on World Wide Web 2006, Edinburgh, Scotland May 23 - 26, Berkeley, CA, pp. 34-38.
Reynolds, K.M., Jensen, M., Andreasen, J. and Goodman, I. 2000. Knowledge-based assessment of watershed Condition. Computers and Electronics in Agriculture, 27: 315–333.
Rhonda, D. and Monte, H. 2001. Data Mining Explained, Digital Press, New York.
Saadan, K. 2001. Conceptual Framework for the Development of Knowledge Management System in Agricultural Research and Development, Asia Pacific Advanced Network Conference 2001, Penang, Malaysia.
Singh, A.K. 1994. Crop Growth Simulation Models. IASRI, New Delhi, pp. 497-509.
Wen, W. 2007. A knowledge-based intelligent electronic commerce system for selling agricultural products. Computers and Electronics in Agriculture 57: 33–46.
Pulses, mostly grown as rainfed crops, are important for protein security and soil revitalisation properties due to symbiotic nitrogen fixtion throughout the world. Major pulses include chickpea or Bengal gram (Cicer arietinum), urdbean or black gram (Vigna mungo), lentil (Lens culinaris), pigeonpea or red gram (Cajanus cajan), mungbean or green gram (Vigna radiata), lablab bean (Lablab purpureus), moth bean (Vigna aconitifolia), horse gram (Dolichos uniflorus), pea (Pisum sativum), grass pea or khesari (Lathyrus sativus), cowpea (Vigna unguiculata), broad bean or faba bean (Vicia faba) and kidney bean or Rajma (Phaseolus vulgaris). Given below are seven point strategies to improve pulse production.
- Availability of quality seeds: Availability of quality seeds of improved cultivars in a village seed bank concept will enhance the productivity.
- Plant nutrition: Pulses generally respond very well to starter dose of nitrogen (20 kg/ha) for enhancing plant uptake when roots are small and thereby promoting early vigor. Placing phosphorusand potassium in the root zone as per STCR approch of yield tagetting based on soil test values (http://www.iiss.nic.in/downloads/stcr%20Crop%20wise%20Recommendations.pdf) will help in realising yield based on resource endowment of farmers.
- Check runoff losses: In water scarcity areas, yield of pulses is sensitive to runoff losses. Reducing runoff through mulch and other water conservation approach to enhance the residency period of water in a parcel of land will help in improving pulse production.
- Capacity building: Smallholder farmers, especially women, should be central to all capacity building pogramme for improving pulse production technology.
- Disease and pest: A 2x2 approach by addressing two diseases viz., wilt and root rots and two pests pod borers and pod fly is very important.
- Being mostly grown as rainfed crop, the high risk in production due to vulnerability to weather as well as abiotic and biotic stresses, weather-based price insurance for pulses is a must to encourage farmers to go for pulse production.
- Encouragring PPP in pulse production and introduction of low cost dal mill in a cluster mode will be helpful.
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Soil health is often intricately related with spread of invasive alien species which also should be a factor to recon with. International Union for Conservation of Nature and Natural Resources (IUCN) defines Invasive Alien Species as an alien species which becomes established in natural or semi-natural ecosystems or habitat, an agent of change, and threatens native biological diversity. These invasive species are widely distributed in all kinds of ecosystems throughout the world, and include all categories of living organisms. Invasive species are good at exploiting bare soil and empty niches. Invasive species are generally non-natives that infest natural ecosystems, including forest, rangelands, and pastures. One way to avoid invasive species is to choose the ones that are native to the area. Natives often are adapted to a specific environmental niche, and have natural controls that keep them in balance. Invasive species, on the other hand, are tolerant against environmental extremes and possess greater flexibility for survival in wide range of conditions with high water, light and nutrient use efficiencies. Some of the invasive species also exhibit fire resistance besides better competitive ability and
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Nutrient management in India over time has specific syndrome which can be summarised by abuse of nitrogen, disuse of potassium, and generally coupled with overuse of phosphorus. It suggests inherent flaws in fertilizer application practices adopted by farmers that probably promotes imbalance in nutrient applications. The ICAR project on soil test crop response (AICRP-STCR) has used the multiple regression approach to develop relationship between crop yield on the one hand, and soil test estimates and fertilizer inputs on the other, can be effectively used to tackle such flaws. The future line of work should include, development of soil health assessment and management protocols on the basis of farming systems after superimposing agro-ecological regions, soil type, yield targeting and resource availability with broader commitment of improving soil health and reducing carbon-footprint; development of decision support tool which can be used for judicious agricultural resource management and periodic soil quality monitoring; evaluation and propagation of customized and speciality fertilizers, nano plant nutrient products; development and calibration of soil sensors for soil test crop response. Resudue burning need to be addressed holistically including energy consideration and dynamics of active / resistant pool of soil organic cabon. For salt affected soil, controlled drainage-subirrigation systems for recycling nitrate leaching from the soil profile and reduce nitrate lost in tile drainage may be advocated to all land reclamation corporation. Also there is a need to harness and manage the indigenous technical knowledge and fine-tune them to suit the modern needs. Notwithstanding the uncertainty over Kyoto commitments and instruments, the twin aspect of devising strategies for leveraging resources to tackle the challenge of low carbon transformation and strategies to enhance soil health and carbon sequestration will help in combating climate change without compromising economic development.
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Moisture conservation enhances soil organic carbon by increasing period of vegetative cover, vegetative input to the soils and microbial population. This altogether leads to increase water stable aggregates that offer protection mechanism for longer residence time to soil organic carbon. In situ moisture conservation including inter row water harvesting, field bunding, mulching, deep ploughing and other agronomic practices such as drought tolerant cultivars, optimum plant density, and proper sowing time, balance fertilization, use of sprinklers and drips for irrigation on the undulated topography may have beneficial effect on soil organic carbon build up. Integrated and balanced use of nutrient and adoption of conservation agriculture also helps in soil carbon sequestration. Gene mining for drought avoidance is another aspect which helps in soil carbon sequestration. There are several species which have very extensive root system for mining water from large volume of soils and can survive very low water, such as Prosopis Juliflora surviving in the rainfall zone ranging from of 200 mm in Bhuj to 1000 mm around Ramnathpuram of east coast. Genetically modified plants can manage a biotic stress of droughts, salinity, heat and cold waves and such attempts may be beneficial for averting the impact of fallowing on soil organic carbon depletion. Finally, adoption of agroforestry system of land use combining agriculture, forestry, horticulture, livestock management and agrostology increases total productivity of food, feed and fuel and thereby reducing the risk of farming besides improving soil carbon sequestration. Further, region-specific amalgamated technological prescriptions refined with targeted policy analysis are required for effective implementation and obtaining positive outcomes within a finite time horizon.
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A high aggregation on account of increased silt and clay protects SOC from decomposition by trapping them between the aggregates. Soil organic carbon is essential for enhancing soil quality, sustaining and improving food production, maintaining clean water, reducing CO2 in the atmosphere and an effective soil quality indicator. Its concentration influences physical, chemical and biological qualities of soils, quality and quantity of biological produce. Soil organic carbon (SOC) is the predominant parameter that affects other physical, chemical, and biological properties of soils. Cultivation generally depletes one third to half SOC, depending upon soil texture, erosion, and vegetative cover, management regime, initial concentration, period of fallowing and inorganic carbon accumulation. Available phosphorus and potassium were reported to increase with the stability of organic carbon and vice versa. Sodium adsorption on clay complex increased with SOC depletion. Thus soil organic carbon is dynamic and a widely accepted indicator, changing with land use and management history.
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