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Adaptation and Adoption of Agricultural Sensors, Information Communication Technologies, and Smart Supply Chains to Support Smallholder Farmers



Smart and resilient agriculture is essential to address future disruption and challenges, such as climate change, COVID-19 pandemic, large scale floods, and droughts. During the pandemic, the agriculture sector in countries like Indonesia can still maintain its growth despite challenges in people and goods mobility. Small-medium enterprises and smallholder farmers are still dominant, especially in the Asia-Pacific, with key factors of low technology adoption and low productivity. These factors are challenging and problematic for making farming more efficient. Solutions are necessary among others through the support from advances in technologies such as agricultural sensors, other Information Communication Technologies (ICTs), including Internet of Thing (IoT), blockchain, computer vision, big data, artificial intelligence (AI), automation, robotics and assistive devices, and unmanned aerial vehicles (UAV), etc.  However, considering variabilities in existing farming systems and business, adaptation processes are required in order to be effectively adopted by smallholders considering local culture as well as existing practice and policy. Taking advantage of experiences on the development of adaptation and adopting of smart agriculture and supply chain from FFTC member countries, an international seminar was planned.


  • To exchange knowledge and experiences on adaptation and adoption of agricultural sensors and other ICT technologies in smallholders (e.g. advances in smart agriculture technologies).
  • To strengthen international cooperation among stakeholders for wider adoption of technology and smart supply chain management (e.g., collaboration for impactful use of agricultural sensing and other ICT technologies and shorter supply chain).
  • To increase the public's level of awareness on the use of technology for securing sustainable agriculture (e.g., science - policy/practice interface).


Session 1: Advances of agricultural sensors and other ICTs in smart farming

Session 2: Successful cases of smart farming systems and supply chains (crops, livestock, aquaculture)

Session 3: Support policies and public private partnership

Program highlights

The workshop concept was initially proposed by IPB. The workshop was jointly organized by FFTC and IPB University. Webex Event program (up to 1,000 participants) was used for this workshop. The virtual meeting was hosted at IPB University and livestreamed on the FFTC Facebook page. 

Thirteen experts from six countries (Indonesia, Japan, Malaysia, Taiwan, Korea, Philippines) shared their knowledge and perspectives from the public, private sectors and academics. The presentation materials include 12 PPTs, a proceeding including 10 papers and 2 abstracts, and a Facebook livestreamed video.

Workshop video can be watched at:

Facebook video:

More workshop information can be viewed at:

Workshop website:

Key takeaways were summarized by presentation:

Keynote S0-1: The Institute of Research and Community Services of IPB University introduced the university newly adapted research agenda named Agro-Maritime 4.0.  Higher research productivity in terms of number of publications, patterns and policy was achieved for those research units adopted the Agro-Maritime 4.0 compared to other research schemes.

Keynote S0-2: Plant growth behavior is strongly influenced by genetic and environmental factors. High throughput phenotyping technology using image processing and integration of IoT and AI is an powerful tool to illustrate the complexity of biological, physiological, and ecological features of plants. The system is very expensive that limits its application. Kyushu University professor from Japan demonstrated an affordable and effective system of his design with lower-input IoT devices and opensource software.  

Session 1: Advances of agricultural sensors and other ICTs in smart farming

S1-1: Crop production requires weed control. Small UAV (unmanned aerial vehicles or drone) have been introduced in site-specific weed management (SSWM) as an affordable option for small farming. The image resolution can be further improved. JIRCAS scientist, Japan, designed a small UAV with simple linear iterative clustering (SLIC) and random forest (RF) to improve image resolution for weed detection and tested it in the upland rice fields in Laos. The results showed the design meets SSWM with acceptable image accuracy.

S1-2: Portable Vis/NIR spectrometer is a promising technique for in situ quality monitoring and assessment of agro-food products along the supply chain. IPB professor demonstrated the applications of the portable Vis/NIR in quality assessment of fruits, meat, aromatic oils, egg freshness, and adulteration of fresh milk in the supply chains.

S1-3: Sugarcane harvesting machines are well developed, highly efficient but usually the size is big, thus not suitable for small farms. The speaker from University of the Ryukyu, Japan presented the innovations with ICT to optimize machine efficiency and applicability in designing the sugarcane harvesting mechanization for small farms in Okinawa.  

S1-4: MARDI scientist, Malaysia presented their work on ICT and sensors toward Agriculture 4.0. The technologies were proved to enhance agricultural productivity and efficiency. MARDI is now focusing on the integration of cyber-physical technologies along the agri-food value chain to attract young generation’s involvement in the industry.  

Session 2: Successful cases of smart farming systems and supply chains (crops, livestock, aquaculture)

S2-1: Ageing of agricultural workforce is a serious problem in Taiwan and other Asian countries as well. Scientist from Taiwan Livestock Research Institute introduced several successful cases of utilizing digital livestock farming that can attract young farmers to join, for examples, (1) using ICT for higher fertility rate of ovulated eggs in native chicken breeding, (2) installing box-type milking robots to double the productivity and reduce workload, (3) digital auction of breeding boars to make informed decision and improve farm productivity.    

S2-2: RDA Scientist introduced Korea’s three generations of smart farms from current year to 2040. The focuses of each generation are: (1) remote facility control and improved convenience, (2) precise growth management by improving productivity, and (3) full cycle automatic management using cutting-edge communication technology, robotics, big data and artificial intelligence.

S2-3: The speaker from IPB, Indonesia presented a multi-sectoral collaborative project using system-approach to develop a farmer-welfare oriented agricultural system. The project collaborates with government, bank, insurance company, input supplier, business, and other stakeholders in the agri-food supply chains, aiming to improve farmers’ productivity, increase access to markets and ensure fair price.

S2-4: The UPLB professor, the Philippines presented a project on early warning system that addresses in-time response to climate changes and natural disasters. The project aims to establish a national crop forecasting and monitoring network and provide early warning to help farmers making informed decisions on better water/ soil management and to help policymakers developing strategies to strengthen local agriculture system.

Session 3: Support policies and public private partnership

S3-1: Speaker from Ministry of Agriculture, Indonesia, indicated the importance of technology transfer for R&D impacts. Major transfer channels in Indonesia include: (1) technology dissemination to end users through public domain, and (2) commercial agreement. Accelerating technology transfer is required and enhancing research and industry linkage could be an effective solution.

S3-2: Native chicken market in Taiwan is shrinking over the years as the introduction of the standardized procedures and advanced farm management of white broiler chickens.  Manager of Kai Shing Co., Ltd shared their experience in applying SOP, ICT, IoT and branding in the breeding and farm management of Taiwan native chicken in recent years. He showed the potential and competitiveness of native chicken production and market in Taiwan and possible oversea markets.

S3-3: National Taiwan University professor highlighted human resource development, a key factor in developing smart agriculture (SA) and recommended: (1) SA policy integrates ICT, digital technology into farming practices and business management; (2) Cultivate a sufficient number of smart farmers; (3) Develop priority policy favoring smallholder farmers to adopt SA technologies; and (4) Provide continuous and systematic training courses to farmers.

Suggestions and conclusions

  • Document and promote successful cases of smart farming systems and supply chains like the use of digital livestock farming and ICTs for native chicken to attract the younger generation of farmers to join such activities.
  • Emphasize the importance of technology transfer for R&D impacts, the benefits of applying SOPs, ICTs, and IoTs in branding, breeding and farm management.
  • Highlight the value of human resource and capacity development in smart agriculture in agricultural meetings.
  • Disseminate the merits of the advances in agricultural sectors and other ICTs in smart farming like the use of small UAVs in site specific weed management, the use of portable Vis/NIR spectrometer in quality assessment of fruits, meats, etc.
  • Integrate the use of smart agriculture ICTs and digital technologies into farming practices and business management.
  • Provide continuous and systematic training courses and develop a sufficient number of successful smart farmers to inspire others.


A total of 687 people registered in the workshop, including participants from Indonesia (~350), the Philippines (~200), Malaysia (~50), Taiwan (~25), Vietnam (~25), India (18), Thailand (13) and other 10 more countries. The actual number of participants on the Webex meeting room was about 180-200 during workshop time. A feedback survey form was sent to all participants the day after the workshop. A total of 192 participants responded to the survey; over 95% of them requested certificate of attendance. About 76-90% of the respondents joined all the sessions. The majority of the respondents (>90%) were very satisfied with the workshop in all aspects (logistics, content, and relevance). About 62-75% of respondents also provided their takeaways, and additional comments and suggested future workshop topics.

Related news

Nov. 10, 2021 FFTC-IPB videoconference tackles advances in agricultural sensors and other ICTs




Implementing Agro-Maritime 4.0 Research Agenda: Linking Science and Policy
Dr. Ernan Rustiadi
IPB University, Indonesia
Plant phenotyping technology to enhance smart farming
Dr. OKAYASU Takashi
Kyushu University, Japan
Weed mapping with low-cost, small UAV for smallholder farming
Dr. KAWAMURA Kensuke
Portable near infrared spectrometers for point-of-need quality assessment of agro-food products
Prof. Y. Aris Purwanto
IPB University, Indonesia
Improvement of subtropical agriculture of sugarcane cultivation using ICT in Okinawa, Japan
Prof. SHIKANAI Takeshi
University of the Ryukyu, Japan
Application of advanced agricultural sensors and ICT in smart farming towards the Agriculture 4.0
Dr. Siti Noor Aliah Binti Baharom
MARDI, Malaysia
Utilization of digital livestock farming for young farmers in Taiwan
Dr. Wu, Ming-Che
Livestock Research Institute, COA, Taiwan
Smart Farm R&D status and future direction in Korea
Dr. Hyunjong Kim
RDA, Korea
Best Practice of Agri-tech Start-up for Farmers’ Welfare: Agri-Tech and Agribusiness Integration to Support Agricultural Ecosystem in Indonesia
Dr. Bayu Dwi Apri Nugroho
Gadjah Mada University, Indonesia
Future-proofing Philippine Agriculture with SARAI Technologies
Dr. Roger A. Luyun. Jr.
University of the Philippines Los Baños, Philippines
Management of agricultural technology transfer In IAARD Indonesia
Dr. Ketut Gede Mudiarta
Ministry of Agriculture, Indonesia
Application of Information Communication Technology (ICT) and Automation in Jin Da Chicken Breeding
Dr. Hsueh-Kai Teng
Kai Shing Co., Ltd. Taiwan
Human Resource Development for Smart Agriculture in Taiwan
Dr. Jiun-Hao Wang
National Taiwan University, Taiwan


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