AgPractices&Domains platform

An Integrative System of Information and Modelling for Recommendations Domains of Agricultural Best Management Practices and Technologies

Asi@Connect 2019 WP5: Deployment of Specialized Network Products, Services and Applications and Associated Capacity Development

Food and nutrition security is vulnerable in most SouthEast Asia countries where rice is the staple food for the majority of the population. Rice production occupies more than half of the cropping areas and relies mostly in smallholding farming systems. It is growing in different ecosystems that are favorable and vulnerable with different potential of production. These ecosystems are challenged by changing variable climatic conditions, increasing pest and disease pressure and the decreasing availability of resources for production as land and water. Rice crop loss due to drought , salinity and flood are increasing every year across tropical Asia for instance this year, rice crop loss was estimated about 150 000 ha in the Philippines. In Myanmar about the same areas are affected by drought and flood while Salinity is affecting more than 500 000ha of rice areas. Yield loss to pest and disease are less reported but available estimate were of 10-15% over rice growing areas in tropical Asia. Sheath blight and blast were identified the most prominent responsible for yield reductions of more than10%. To ensure sustainable food production, research and development programs are required to innovate constantly and to deliver up to date recommendations to address these challenges. We propose in this project to develop and test a web-application tool, Agpractices and domains, to facilitate and accelerate the evaluation of integrated crop management options that can be tailored and targeted to actual farmers potential and risk of production.

The Agpractices and domains application will use innovative approaches coupling modeling and geospatial modeling to evaluate technologies and options in crop management. It will take advantages of the advances in information and communication technologies to facilitate the technologies transfer between agricultural researchers to deliver and target existing science based technologies that are available to reduce risk of rice-based cropping systems in stress prone areas of production.

We selected to focus on two countries the Philippines and Myanmar that have recently invested efforts in open internet and in improving connectivity in remote areas. Furthermore, the diverse and large rice ecosystems in these two countries are an ideal case study for implementing and evaluating Agpractices and domains to accelerate information processing and in generating meaningful information for impact.

Several efforts have been invested to improve resilience and productivity of farming systems in Myanmar among them are research and development programs aiming to evaluate constraints and potential of the main rice growing areas in the dry zone and in the delta (LIFT 2013,, similarly the closing rice yield gap in the country (CORIGAP, and the integrated rice-fish project for diversification and food and nutrition security (Rice-Fish project, Similarly in the Philippines the PRISM project ( has developed a first of its kind system of information for rice monitoring, providing accurate rice areas mapping and extreme weathers impact evaluation. The ongoing next phase of PRISM project is working as well in establishing pest and disease monitoring for evaluation and management. These programs objectives are the development and the dissemination of technologies and options that adopted will improve farmers’ livelihoods. These interventions rely on local experimental fields and surveys as well as drawing on the experiences of different countries as Indonesia, Vietnam, Thailand, India, Bangladesh and China. These research and development programs have collected larger information that are for the time being analysed only for the project purposes such as yield gap analysis, recommendations domains of technologies and options for adaptation to climate variability.

We propose to leverage the methodology developed by these programs to evaluate constraints and potential of productivity. AgPractices&Domains will provide a one stop shop access of these information to researchers for cross sites and cross countries learning that will enable quantification of biotic stresses contribution to yield gaps and targeting integrated pest and disease management in most vulnerable and risky areas.

Addressing pest and disease management has been less explored due to limited resources and the lack of systematic and repeatable approach for evaluation, in this project we will aim then to fill that gap by providing reproducible research approach in pest and disease monitoring and technologies evaluation that are tailored based on spatial distribution of risk across regions of study.


The aim of this project is to improve and build the capacity of agriculture researchers in Myanmar and in the Philippines to use data from different sources to target integrated pest and disease management options through the use of platform as AgParctices&Domains.
Among objectives are then:

  • to develop the AgPractices&Domains platform as a web portal of data sharing and access and data product delivery to support research activities and technologies impact evaluation;
  • to train of researchers in how to access modelling and data analytics tools that will allow them to define target domains and combinations of technologies that are locally adapted . During the project we target to reach about 50 direct users and potential trainers that will support network of users in their respective Institute and we aim to reach out to about 200 users accessing the platform.
  • to facilitate the development of technologies and options improving productivity and reducing biotic and abiotic risks associated to climate variability in rice-based food systems. As outputs delivered by the platform are target areas with high risk of pest and disease, the availability of this information to researchers are expected to improve their efficiency in monitoring the risk and as well in evaluating options that are available helping to minimize its impact. About 100 farms survey will be then conducted using the targeted location at high risk considering current practices and optimum practices generated by the platform.

With the use of the platform researchers will be expected to be able to generate valuable country specific information to improve the farmers’ economy in their areas of study and at scale for their country. And in partnership with the Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA) and the local university partners in Myanmar (University of Computer Sciences Yangon, UCSY) and in the Philippines (University of the Philippines Los Banos, UPLB), we will build a network of rice cropping systems monitoring that are using combined survey and modeling tools facilitating learning and exchanges between partners and countries of the project.

The use of AgPractices&Domains platform will increase as well the use of NREN Asi@Connect network by continuously collection and delivery of information through the open access web portal of the platform. AgPractices&Domains will facilitate and enable collaboration between researchers where they can contribute/source data and access an open workflow for cross sites and /or countries learning. The access and use of these NREN (TEIN) internet facilities will accelerate information dissemination. During the project more than 200 views are expected on the platform by the end of the project with about 50 actual use at its first release and about 100 clicks of data upload will be complete at the of the project.

Information on the applicants

  • Ando Mariot Radanielson, University of Southern Queensland, Australia
  • Pr Adam Sparks, University of Southern Queensland, Australia
  • Pr Glenn Gregorio, Southeast Asian Regional Center for Graduate Study and Research in Agriculture- SEARCA, Philippines
  • Dr. Mie Mie Thet Thwin, University of Computer Studies, Yangon (UCSY), Myanmar
  • Dr. Ruben Lampayan, University of the Philippines of Los Banos, Philippines
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