quality controls
For other developing countries that are still in the
early stage of developing and deploying ICT based
agriculture information dissemination systems,
China’s experience, lessons learned and best practice
can be considered and adapted. The most important
lessons in China can be summarized as the
following:
Government investment and support
Top-down approach
Branding and raising awareness, e.g. 12316 has
been well-know name for Agriculture
Information Service.
Motivating farmers to adopt the service, e.g.
free services, opportunities to report fraud and
illegal products, etc.
Government and enterprise collaborations
Effective use of village based networks and
designated information officers
Looking forward, with the popular use of 3G and
4G technologies, we can expect improved
functionality and enhanced user experience in
agricultural information dissemination. For example,
3S (GPS, Remote Sensing, and GIS) technologies
will also be widely applied in agricultural
informatization. Agricultural information in its
nature has a spatial component, so 3S technologies
which deal with spatial data would be very useful in
enhancing agricultural information service. We have
already seen many effective agricultural information
systems where 3S technologies are integrated in
China, e.g. intelligent fertilizer formulation system.
In the future, all of these emerging ICT will play a
significant role in agricultural informatization.
Having reviewed and analysed the current ICT-
based information service models in China, the
following suggestions can be provided for future
development and research:
Consolidating and harvesting the investment
made in the last decades
Transforming agriculture sector into the
modern digital agriculture to further improve
social and economical benefits
Further improving the digital access by farmers
with technological advances and skills
improvement
Adopting the Internet of Things in agriculture
sector, e.g. GPS, GIS, RFID, Remote sensing,
Smart device for precision agriculture,
sustainability, environment, food safety, etc.
Exploring and utilizing Big Data and
Agriculture Analytics Clearly indicate
advantages, limitations and possible
applications.
ACKNOWLEDGEMENTS
This research is funded by Agriculture Technology
Transfer Programme (AgriTT) by the UK
Department For International Development (DFID).
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