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.