Forum global sur la sécurité alimentaire et la nutrition (Forum FSN)

Dear FSN Forum members,

Please find in attachment my contribution. 

Kind regards

Stella

Dear All,

It is an interesting topic. Basically, ICT is not cheap for the poor and agriculture sector. But it will reduce risk and loss of agriculture sector as  well as save resources. 

Please imagine that: ICT will provide connection between farmers, distributor and consumer in APEC, provide services of agriculture production and processing including insurance, R@D, value chains, marketing as well as custom, etc

Best regards,

KIEN

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Mr. Nguyen Van Kien

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Plant Genebank Management Division

Plant Resources Center (PRC)

Address: An Khanh, Hoai Duc, Hanoi, Vietnam

Thank you for sharing all these interesting insights!  My name is Andrea and I work as part of the Dimitra Team at FAO: http://www.fao.org/dimitra/dimitra-clubs/en/

I have read with great attention other comments and I would like to add an important perspective to this conversation which is gender and people’s empowerment in the design and implementation of development initiatives that focus on ICTs.  

The agenda 2030 focuses on “leaving no one behind”, including in the area of ICTs. Unfortunately the gender gap in ICTs is still a major concern worldwide. Constraints such as high costs, social norms and illiteracy hinder women’s chances to take full advantage of these enablers.

In Sub-Saharan Africa, for example, 64% of women, representing over 300 million, do not own a mobile phone. Even when women have access to mobile phones, their devices tend to be less sophisticated than those of men and their usage is less frequent as most of the time women tend to borrow mobile phones rather than owning them for self-use.

ICTs are great enablers for prosperity and economic growth but should not be considered as a development objective in itself. This means their usage in development initiatives should be accompanied by empowering processes of change that are inclusive and gender-responsive.  

I just wanted to make sure this gender dimension is not forgotten when addressing ICTs in rural development. And also mention another geographical context (sub-Saharan Africa) in which FAO has been promoting a gender-transformative participatory communication approach called the Dimitra Clubs. These clubs are groups of rural women and men who meet, discuss their daily challenges and identify solutions together to overcome them. Access to information and networking is facilitated by the use of solar powered radios paired with mobile phones connected into a fleet.   Thanks to these clubs, rural women and men and entire rural communities take their own development in hands by identifying their own priorities and implementing local solutions to improve their livelihoods.  

An important element of this approach, worth sharing here, is that by combining capacity development processes with the use of ICTs the Dimitra Clubs greatly contribute to people’s empowerment, women’s leadership, collective action, social cohesion and gender equality.

Today, there are over 45,000 members (two thirds being women) in the 1,530 existing Dimitra Clubs in six countries of Sub-Saharan Africa (Burundi, DR Congo, Ghana, Mali, Niger and Senegal). It is estimated that over one million rural people benefit from the activities of the clubs.

I would like to share a link to some Dimitra videos (in French and English) showcasing the impact of this approach in different areas. http://www.fao.org/dimitra/dimitra-clubs/en/

The case study of introducing a new ICT technology through cell phone seems to improve efficiency in agricultural marketing in Mali. In fact,first generation of market information systems did not meet the expectations of their promoters. The information produced and made available to users was not reliable enough and reduces its usefulness. It is disseminated without sufficient knowledge of the actors' request for information. The beneficiaries consider that conventional broadcast channels (radio, television, and paper) provide generic and often inadequate information. The USSD platform of the Sénèkela project tries to remedy this problem by giving access to quasi-personalized market information. At this stage, it registers between 50 and 60 000 monthly subscribers, following its launch in April 2014. However, despite pricing, which is below actual costs, the service carries a risk of excluding low-income users. This pricing principle also threatens the sustainability of the platform.

Based on the African context especially in rural areas whereby there are no internet infrastructures, IT immediately can not have a contribution in agriculture development. Therefore, a certain country must invest in IT technology in rural areas to enable development of agriculture.

English translation below

Les technologies de l’information et de la communication permettent un contact direct rapide entre producteurs et consommateurs dans le secteur agricole.

Elles facilitent l’accès au marché et permet aux agriculteurs d’évacuer rapidement leurs productions en ce sens les nouvelles technologies de l’information et de la communication sont un outil que les agriculteurs peuvent utiliser pour avoir en temps réels toutes les informations sur le marché et adapter leurs produits aux exigences du marché ou des consommateurs.

Les technologies de l’information permettent aussi aux agriculteurs de détecter tôt les maladies des plantes ou autres, d’entrer en contact rapidement avec des spécialistes pour traiter de leurs problèmes ; elles leurs permettent aussi de faire la promotion de leurs produits, de moderniser leurs activités.

Les nouvelles technologies de l’information sont en train de transformer le monde et l’agriculture ne devrait pas rester en dehors de ce changement !

Information and communication technologies allow a fast direct contact between producers and consumers in the agricultural sector.

These technologies facilitate access to the market and allow farmers to send off their harvests quickly, in this sense the new information and communication technologies are a tool that the farmers can use to have, in real time, all the market data and adapt their products to the demands of the market or the consumers.

Information technologies also enable farmers to detect early plant or other diseases, and to make quick contact with specialists to treat their problems; these technologies also allow users to promote their products and modernize their activities.

These new information technologies are transforming the world and, agriculture should not be excluded from this change.

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.

Strategic Information

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.

Past Trends

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 [2001] 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.

Expert System

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 Tools

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 [2007] 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.

References

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.

The "APEC Wisdom Agriculture development and application workshop" was held successfully from Nov. 23 to 25 in Yinchuan, Ningxia (China). The workshop invited more than 120 experts and scholars from 8 APEC economies, 5 Observing countries, 5 international organization and different provinces in China. Experts from Greece, Korea, Spain, and Canada gave wonderful speeches on wisdom agriculture, precision agriculture, internet & agriculture, and agricultural product traceability. Chinese experts gave speeches on wisdom plant, precision forest, wisdom animal husbandry, crop modelling and wisdom orchard respectively. Experts from different economies showed the research and application progress in their economies, exchanged information on the advanced technologies and achievements.

The workshop has yielded a series of achievements, mainly along four points.

1. Create an APEC wisdom agriculture cooperation network, build a communication and exchange platform for experts. The information and technologies have been commonly applied in agriculture, and wisdom agriculture has gotten more attention from APEC and other regions in the world. The economies and regions faced some common problems regarding wisdom agriculture and there exist also some differences in wisdom agriculture development and application due to regional variations. The creation of an APEC wisdom agriculture network can help share information, integrate and optimize resources, and promote cooperation and communication.

2. Strengthen long-term project cooperation in wisdom agriculture for APEC regions.

The APEC wisdom agriculture workshop can build bridges for researchers and organizations in APEC and other regions in the world, strengthen related cooperation. It also can help apply funds and projects for wisdom agriculture in APEC regions, collectively carry out research in wisdom agriculture, and push the development and application of wisdom agriculture in APEC and other regions.

3. Create expert database, and promoting multilateral cooperation.

An expert database in wisdom agriculture can collect the related information of agricultural experts to supply support and help for the researchers in wisdom agriculture while strengthening multilateral cooperation in different APEC regions.

4. Promote the research level and application ability of related researchers in wisdom agriculture.

The workshop invited international leading experts in wisdom agriculture to give presentations on the internet of things, big data, intelligent agent, the agricultural product traceability system, the plant growth model, digital orchard, and presented good international application cases of wisdom agriculture in different APEC economies. The workshop supplied advanced knowledge on technologies, helped share good cases, and promoted the research level and application ability of related researchers.

In order to expand the influence of the workshop, this online discussion was held to allow experts from across the world to exchange on wisdom agriculture. This discussion has been very successful in debating some crucial questions and for collecting examples from around the world.

On behalf of agriculture information institute of CAAS, I thank the staff from FAO responsible for the online discussion, thank Dr. Bi for her support, thank YPARD for joining the discussion actively, thank the colleagues from the Agriculture Information Institute of CAAS for their help, thank our partners from Ningxia Foreign Affairs Office and finally and especially thank Mr. Max Blanck for his hard and careful work. I appreciate you all for what you have done for the on-line discussion, without which it would not have achieved success.

The visual for using ICTs in agriculture is becoming increasingly granular - any farmer (in particular smallholders) can have mobile access to detailed, precise information about their farm, and receive specific advise on how to maximize yields. This has the potential to increase yields and production comparable to what the green revolution did in many parts of the world.

With that vision, the obstacles to achieving it are also starting to become known. An important part of it is how to 'chop up' services and information that needs certain agricultural scale in order to be feasible. Creating business models that allow for smaller farms to benefit from high-tech, high investment agri services is a critical part of the puzzle.

If it's relatively easy to identify this as a problem, finding solutions that actually work is a lot harder. The agri world has been working for decades on ways of grouping small farmers together. The current state of most cooperatives does not suggest that this has been cracked yet. Another clear obstacle is finding ways to motivate small farmers to pay for yield-enhancing services. While some countries have made great strides in this area, significant parts of the developing world still work on a 'minimal cash outlay' farming system.

It goes too far - and is probably too early - to start promoting definitive solutions in this area. IFC is working on a number of topics in ICT for agri, which cover traceability, farmer extension, benchmarking and GIS/precision ag. As so often, the real question of success may be shaped more by who is most successful in getting their services adopted, rather than who has the technically most elegant solution.

It is likely to be years (or never) before there is a sufficient, predictable, reliable monetary benefit accrusing to smallholder Farmers from traceability itself; the benefit is likely to be outside of traceability (perhaps from information coming back from the data, perhaps from linking to a buyer, perhaps from linking to transport, etc). 

Smallholder Farmers will benefit from agricultural product traceability systems when their return on the investment of time and money that they have put into the system are considered.  Understanding why and how they would use a system is a first step.