RiceMoRe: Digital rice activity monitoring and reporting system

A digital solution for monitoring and reporting rice activities

RiceMoRe is a web- and mobile-based digital system for managing and monitoring rice production data across farmers, cooperatives, and production units. It uses standardized digital forms to record production progress, farming practices, varieties, yields, and other field-level information, with georeferenced records consolidated across production networks. The system enables users to track and compare farming practices and production performance, visualize data through maps, charts, and tables, and generate structured reports. For private-sector actors working with rice producers or production networks, these capabilities can provide structured, location-specific visibility into production activities and performance, supporting operational monitoring and decision-making. Farm-level activity data can also be connected through an API to the SECTOR GHG Calculator to support GHG emission estimation.

This technology is pre-validated.

8•9

Scaling readiness: idea maturity 8/9; level of use 9/9

2018–2024 Timeline

Co-created, tested, and implemented in Vietnam

2020–2021 Timeline

Initial piloting in Can Tho province

IP

Open source / open access

Problem

Fragmented production data: Difficulty consolidating and managing information from multiple farms, farmers, cooperatives, or production units within an organization.
Manual data collection and reporting: Time-consuming collection, compilation, and reporting of production data, particularly across large numbers of farmers or fields.
Limited performance benchmarking: Difficulty tracking and comparing farm activities and production performance against organization-specific standards, targets, or sustainability requirements.
Limited geographic visibility: Lack of georeferenced production data makes it difficult to locate production areas, monitor specific locations, and identify production patterns across supply networks.
Limited GHG data: Difficulty quantifying GHG emissions from farm-level activities and generating traceable data for sustainability reporting, MRV, and climate-related projects.

Solution

Centralized production data management: A centralized digital platform consolidates production data from individual farms, farmers, cooperatives, or production units, providing a structured view of production activities across an organization.
Mobile field data collection: A user-friendly mobile application enables field-level data collection, with information automatically aggregated across farms and production units, reducing manual compilation and reporting.
Performance benchmarking: Customizable benchmarks enable users to track and compare production activities and performance against organizational standards, sustainability criteria, quality requirements, or other targets.
Production traceability: Georeferenced and synchronized records provide greater visibility into production locations and activities across supply networks, supporting operational monitoring and decision-making.
GHG emissions estimation: Farm-level activity data can be connected through an API to the SECTOR GHG Calculator, supporting GHG emissions estimation for sustainability reporting, MRV, and climate-related initiatives.

Key points to design your business plan

RiceMoRe can be used by different actors involved in rice production and value chains, from individual farmers and cooperatives to companies managing larger production networks. The way the system is used and configured will depend on the scale of operations, number of users, type of production data to be collected, reporting requirements, and level of data management needed.

For organizations considering RiceMoRe, it is therefore important to first identify the main users and their specific monitoring needs, and then define the appropriate data collection, reporting, and management arrangements. The following points highlight the main considerations for different types of private-sector users and can help organizations assess how RiceMoRe could fit into their existing operations.

Individual farmers

RiceMoRe is relevant for rice farmers who need to record and track their farming activities, particularly farmers working with companies, cooperatives, or sustainable production projects.

Simple digital data collection: Farmers can record farming activities through predefined digital forms designed for field-level use.
Tracking of farming practices: Farmers can maintain records of their production activities and practices throughout the cropping season.
Benchmarking against defined targets: Where benchmarks are established by a company, cooperative, or project, farmers can compare their practices or performance against these criteria.
Access and support: Deployment should be organized through the relevant company, cooperative, project, or RiceMoRe technical team, including user access, training, and technical support.

Cooperatives

RiceMoRe is relevant for rice cooperatives that need to manage and monitor production activities across their members and consolidate farm-level information at cooperative level.

Digital data collection: Cooperative staff and members can record farming activities using standardized digital forms.
Member and farm monitoring: Cooperatives can organize information on member farmers and monitor farming activities across participating farms.
Automatic data consolidation: Data collected from individual farms can be aggregated to provide a consolidated view of production activities and performance at cooperative level.
Performance benchmarking: Cooperatives can compare farming practices and performance against cooperative targets, sustainability requirements, or other predefined criteria.
Reporting and traceability: Standardized and georeferenced farm-level records can support internal management, reporting to companies or projects, and traceability of production activities.

Rice-producing and contracting companies

RiceMoRe is relevant for companies producing rice or working with contracted farmers and cooperatives that need to monitor production activities across multiple farms and production areas.

Manage production networks: Companies can organize information on contracted farmers, cooperatives, farms, and production areas within a centralized system.
Customize data collection: Data fields, reporting forms, indicators, and benchmarks can be adapted to the company’s production, quality, sustainability, or agroecological requirements.
Consolidate production data: Farm-level information can be aggregated across farmers, cooperatives, production units, and geographic areas to support operational monitoring.
Monitor performance and compliance: Companies can track farming practices and compare performance against company standards, targets, or sustainability requirements.
Support traceability and sustainability reporting: Georeferenced production records and farm-level activity data can support traceability, sustainability monitoring, and GHG emissions estimation.
Plan deployment and technical requirements: Companies should define the required users, reporting structure, data fields, indicators, database and hosting arrangements, and technical support needed for implementation.

Positive impacts: 8

Target Group	Positive Impacts
Women smallholder farmers with low digital literacy	Greater visibility of farming activities: Standardized records can make women farmers’ production activities and practices more visible within farm, cooperative, project, or institutional monitoring systems. Accessible participation in data collection: User-friendly predefined forms can facilitate participation in farm-data reporting without requiring advanced digital skills.
Smallholder farmers with low digital literacy in areas with limited internet connectivity	More structured participation in reporting: Standardized, user-friendly forms simplify the recording of farm-level information such as cultivated area, varieties, production progress, practices, and yields. Inclusion in wider production monitoring: Farm-level records can be aggregated through existing reporting structures, allowing participating smallholders to be represented in broader production monitoring.
Smallholder farmers with low digital literacy and weak access to collective support structures	Structured farm records: Standardized forms provide a simpler and consistent way to record production activities and practices, including water, fertilizer, and straw management. Access to selected public functions: Some RiceMoRe functions, including GHG emission estimation, can be accessed by public users without requiring an account.
Smallholder farmers with limited internet connectivity and weak access to collective support structures	Spatial visibility of production areas: Georeferenced records allow participating farms and production areas to be represented in spatial agricultural monitoring. Integration into wider monitoring: Farm-level production and practice data can be consolidated across geographic or administrative levels, increasing the representation of participating production areas in broader monitoring systems.

More...

Unintended impacts: 8
Mitigations: 8

Barriers: 11
Mitigations: 11

Climate adaptability: Highly adaptable

The system is online and flexible, so it can be used in any climate setting

Farmer climate change readiness: Significant improvement

Informs government, extension agencies, cooperatives to provide suitable climate advisories to farmers.

Biodiversity: No impact on biodiversity

Carbon footprint: Much less carbon released

Supports MRV for emission reduction.

Environmental health: Moderately improves environmental health

Supports extension to provide advisory related to environment and projects/enterprises to monitor farming practices that have environmental impacts such as pesticide or fertilizer management.

Soil quality: Not yet estimated

Technical Characteristics of RiceMoRe

1. System Architecture & Platform

Open-Source Infrastructure: Built on open-source web and mobile technologies, incurring zero software licensing fees and offering a low-cost, highly replicable system.
Multi-Platform Access: Features both a web-based management portal and mobile applications for Android and iOS devices.
Flexible Database & System Integration: Allows data storage in local, cloud, or custom organizational databases. It incorporates APIs to connect farm-level activity data with independent greenhouse gas (GHG) calculation engines and enables data exchange with existing Ministry systems.

2. Spatial & Temporal Resolution

Spatial Granularity: Operates at the field and commune unit level, utilizing georeferenced administrative boundary maps (compatible with GIS tools such as QGIS for polygon management).
Temporal Frequency: Supports weekly, bi-weekly, seasonal, and annual data collection, monitoring, and reporting schedules.

3. Hierarchical Data Flow & Approval Workflows

5-Tier Administrative Hierarchy: Links workflows structured directly across Commune, District, Province, Region/Zone, and National levels.
Automated Data Aggregation: Automatically consolidates records from commune level up to district, province, region, and national scales, eliminating manual compilation while preserving traceability back to original commune entries.
Multi-Stage Validation Protocol: Implements status-tracked review and approval workflows (e.g., Draft, Submitted, Approved, or Rejected) where upper-level officials validate entries before they are committed to the national database.

4. Core Data Modules & Functional Indicators

7 Standardized Reporting Modules: Features structured modules for Production Planning, Planting Progress, Growth Stages, Harvesting Progress, Technical Practice Application (e.g., seed rates, fertilizer reduction, water-saving techniques), Mechanization, and Yield Loss/Damage (from natural disasters or pests).
Customizable Forms: Supports customizable survey forms, indicators, and criteria tailored to contracted farming, company standards, or specific project targets.

5. GIS Mapping & Visual Analytics

3 Base Map Options: Integrates Google Terrain, Google Satellite, and Bing Maps.
6 Thematic Production Layers: Generates spatial maps for planting progress, growth stages, harvesting progress, technical application, mechanization, and damage/yield loss tracking.
Interactive Spatial Tools: Provides administrative area filters, seasonal query tools, map legends, and interactive map navigation (zooming and panning).

6. Automated GHG MRV Engine

Activity-Based Emission Calculation: Translates field management data (such as fertilizer application, straw management, and water regimes) into automated GHG emission estimates to support national Measurement, Reporting, and Verification (MRV).
Public Accessibility: Features an open-access GHG calculation tool accessible to public users and farmers without requiring a user login.

7. User Management & Security

Role-Based Access Control (RBAC): Manages permissions based on administrative levels or organizational units.
Granular Action Permissions: Controls specific functional rights for viewing, adding, editing, deleting, and importing/exporting Excel data.
Audit Logging & Security: Tracks login history and user operations in real-time, supported by phone/email account management and OTP password recovery.

Scaling Readiness describes how complete a technology's development is and its ability to be scaled. It produces a score that measures a technology's readiness along two axes: the level of maturity of the idea itself, and the level to which the technology has been used so far.

Each axis goes from 0 to 9 where 9 is the “ready-to-scale” status. For each technology profile in the e-catalogs we have documented the scaling readiness status from evidence given by the technology providers. The e-catalogs only showcase technologies for which the scaling readiness score is at least 8 for maturity of the idea and 7 for the level of use.

The graph below represents visually the scaling readiness status for this technology, you can see the label of each level by hovering your mouse cursor on the number.

Scaling readiness score of this technology

Maturity of the idea 8 out of 9

Uncontrolled environment: tested

Level of use 9 out of 9

Common use by intended users, in the real world

Maturity of the idea										Level of use
9
8
7
6
5
4
3
2
1
	1	2	3	4	5	6	7	8	9

Positive impact 8

Target Group	Positive Impacts
Women smallholder farmers with low digital literacy	Greater visibility of farming activities: Standardized records can make women farmers’ production activities and practices more visible within farm, cooperative, project, or institutional monitoring systems. Accessible participation in data collection: User-friendly predefined forms can facilitate participation in farm-data reporting without requiring advanced digital skills.
Smallholder farmers with low digital literacy in areas with limited internet connectivity	More structured participation in reporting: Standardized, user-friendly forms simplify the recording of farm-level information such as cultivated area, varieties, production progress, practices, and yields. Inclusion in wider production monitoring: Farm-level records can be aggregated through existing reporting structures, allowing participating smallholders to be represented in broader production monitoring.
Smallholder farmers with low digital literacy and weak access to collective support structures	Structured farm records: Standardized forms provide a simpler and consistent way to record production activities and practices, including water, fertilizer, and straw management. Access to selected public functions: Some RiceMoRe functions, including GHG emission estimation, can be accessed by public users without requiring an account.
Smallholder farmers with limited internet connectivity and weak access to collective support structures	Spatial visibility of production areas: Georeferenced records allow participating farms and production areas to be represented in spatial agricultural monitoring. Integration into wider monitoring: Farm-level production and practice data can be consolidated across geographic or administrative levels, increasing the representation of participating production areas in broader monitoring systems.

Unintended impact 8

Target group	Potential unintended impacts	Mitigation measures
Women smallholder farmers with low digital literacy	Reduced participation in data management: If data entry is handled mainly by more digitally skilled household members or field actors, women may have less direct involvement in recording and reviewing their farming activities. Underrepresentation in monitoring: Lower participation in digital reporting could result in women's activities being less completely represented in aggregated data.	Ensure direct participation: Include women directly in training, data entry, review, and validation activities. Monitor representation: Check participation and completeness of records by gender and address identified gaps.
Smallholder farmers with low digital literacy and limited internet connectivity	Incomplete or delayed records: Difficulties entering or transmitting digital data may result in incomplete or delayed production records. Underrepresentation in monitoring: Farmers unable to report as regularly as better-connected users may become less visible in aggregated and spatial monitoring.	Use existing reporting lines: Where direct farmer reporting is difficult, use established local reporting structures to support data collection, review, and transmission. Monitor reporting coverage: Identify persistent gaps in reporting and provide targeted support to poorly represented users or areas.
Smallholder farmers with low digital literacy and weak access to collective support structures	Dependence on intermediaries: Farmers requiring assistance may become dependent on other actors to enter or manage their production information. Unequal data visibility: Farmers receiving less organizational or technical support may generate less complete records than farmers integrated into stronger reporting networks.	Maintain farmer involvement: Use assisted data entry where necessary while allowing farmers to participate in and review the information recorded about their farms. Extend participatory implementation: During deployment, involve farmers outside strong collective structures in adapting reporting arrangements and identifying support needs.
Smallholder farmers with limited internet connectivity and weak access to collective support structures	Geographic data gaps: Less regular reporting from poorly connected and weakly supported production areas may create gaps in georeferenced datasets. Bias in data-based decisions: Persistent geographic gaps could cause monitoring and planning to reflect better-represented production areas more strongly.	Address coverage gaps: Use existing local reporting structures or other appropriate collection arrangements to improve data coverage in poorly connected areas. Check representativeness: Assess geographic coverage and data completeness before using aggregated information for planning and targeting.

Barriers 11

Target group	Adoption barriers	Mitigation measures
Women smallholder farmers with low digital literacy	Limited digital skills: Limited familiarity with web/mobile tools may constrain independent use despite RiceMoRe's user-friendly design. Unequal access to devices or training: Limited access to digital equipment or technical training may reduce direct participation.	Provide targeted practical training: Complement RiceMoRe's simplified interface with hands-on onboarding and continued support adapted to users' skills. Ensure inclusive access: Include women directly in training and deployment and provide shared or institution-supported equipment where needed.
Smallholder farmers with low digital literacy and limited internet connectivity	Limited digital skills: Even with standardized and user-friendly forms, some users may still require assistance with digital data entry. Limited connectivity: Weak or unstable internet can constrain regular transmission of production data. Limited access to digital equipment: Some smallholders may not have regular access to suitable smartphones or computers.	Provide practical user support: Use hands-on onboarding and assistance while taking advantage of RiceMoRe's predefined and customizable forms. Use existing reporting structures: Where direct transmission is difficult, organize data collection and transmission through established local reporting lines. Facilitate equipment access: Provide shared or institution-supported devices where individual access is limited.
Smallholder farmers with low digital literacy and weak access to collective support structures	Limited digital skills: Farmers may still require assistance to use the system despite its simplified data-entry design. Limited access to technical support: Farmers weakly connected to cooperatives, extension services, or institutional networks may have less access to onboarding and troubleshooting. Limited reach of organized deployment: Farmers outside established reporting networks may be harder to include when RiceMoRe is deployed through institutional structures.	Provide adapted training: Use RiceMoRe's flexible forms together with practical onboarding appropriate to users' digital skills. Extend support beyond organized groups: Make extension or other field-level technical support accessible to farmers outside cooperative networks. Use participatory deployment: Identify and involve weakly connected farmers when adapting RiceMoRe to a new implementation context.
Smallholder farmers with limited internet connectivity and weak access to collective support structures	Limited connectivity: Poor network coverage can constrain regular transmission and use of web/mobile functions. Limited access to support: Weak links to cooperatives or institutional structures may reduce access to assistance when technical or reporting problems occur. Implementation costs: RiceMoRe has no software licensing fees, but access to equipment, connectivity, training, hosting, and technical support may still require resources.	Adapt reporting arrangements: Use existing reporting lines or other locally appropriate arrangements where direct digital transmission is unreliable. Establish accessible support: Ensure technical assistance reaches users outside strong cooperative or institutional networks. Budget beyond licensing: Plan resources for equipment, connectivity, training, hosting, and technical support despite the absence of software licensing fees.

Countries with a green colour: Tested & adopted
Countries with a bright green colour: Adopted
Countries with a yellow colour: Tested
Countries with a blue colour: Testing ongoing

Countries where the technology is being tested or has been tested and adopted
Country	Testing ongoing	Tested	Adopted
This technology has not been tested or adopted in any country.

This technology can be used in the colored agro-ecological zones. Any zones shown in white are not suitable for this technology.

Agro-ecological zones where this technology can be used
AEZ	Subtropic - warm	Subtropic - cool	Tropic - warm	Tropic - cool
Arid	–	–	–	–
Semiarid	–	–	–	–
Subhumid	–	–	–	–
Humid	–	–	–	–

Source: HarvestChoice/IFPRI 2009

The United Nations Sustainable Development Goals that are applicable to this technology.

Goal 2: zero hunger

Supports effective agricultural planning and monitoring through timely, standardized rice production data.

Goal 9: industry, innovation and infrastructure

Provides digital infrastructure for agricultural data collection, management, GIS-based monitoring, and reporting.

Goal 12: responsible production and consumption

Supports monitoring and benchmarking of sustainable, low-emission, and agroecological farming practices.

Goal 13: climate action

Supports GHG emissions estimation and MRV for low-emission rice production.

Goal 17: partnerships for the goals

Supports data sharing and collaboration among government, research, development, farmer, and private-sector actors.

RiceMoRe is used to collect and manage rice production information throughout the cropping season, with data collected weekly, every two weeks, or at other intervals depending on monitoring needs.

Set up: Define what information needs to be collected, when it should be collected, and how it will be reported.
Collect data: Collect production information directly from the field, farms, cooperatives, projects, or other production units using digital forms.
Store and manage: Store and manage the collected information securely in a centralized system, either on the organization’s own infrastructure or in a trusted cloud environment.
Consolidate and analyze: Automatically bring data together across farms, locations, reporting periods, and administrative levels to identify production trends and performance.
Visualize: View and explore the information through maps, charts, and tables, making it easier to understand where activities are taking place and how production is performing.
Report and act: Export data and generate reports that provide evidence for planning, monitoring, decision-making, and follow-up actions.

Downloads

RiceMore - User Manual_compressed-1-25.pdf (PDF, 1.11 MB)
RiceMore - User Manual_compressed-26-50.pdf (PDF, 1.24 MB)
RiceMoRe for CGSpace_compressed.pdf (PDF, 435.03 KB)
RiceMoRe_training.pdf (PDF, 1.3 MB)

Last updated on Sep 24, 2026

International Rice Research Institute (IRRI)
Yen Bui

Commodities

Rice

Sustainable Development Goals Details ›

public.components.sdgs.motre

Subcategory

Crop management

Value chain step

Production

Solution to

Limited Access to Inputs & Services

Tested/adopted in Details ›

Countries with a green colour: Tested & adopted
Countries with a bright green colour: Adopted
Countries with a yellow colour: Tested
Countries with a blue colour: Testing ongoing

Target groups

Farmers Governments Advisory and Extension Services Cooperatives and Agribusinesses

RiceMoRe: Digital rice activity monitoring and reporting system

2018–2024 Timeline

2020–2021 Timeline

IP

Problem

Solution