https://github.com/agrdatasci/documentation
https://agrdatasci.github.io/documentation/
Science Score: 26.0%
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○Scientific vocabulary similarity
Low similarity (10.0%) to scientific vocabulary
Repository
https://agrdatasci.github.io/documentation/
Basic Info
Statistics
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 3
- Releases: 0
Metadata Files
README.md
The on-line guide for product use testing in agriculture
The tricot approach (triadic comparison of technology options) is a participatory method designed for product use testing in agriculture. It has been applied in on-farm trials, consumer testing, concept evaluation, and iterative product development. The approach leverages citizen science to generate robust, scalable insights across diverse environments and user contexts. Here's how it integrates into different aspects of product use testing:
- On-Farm Testing
Farmers receive three randomly assigned technology options (e.g., seed varieties, fertilizers) and independently evaluate their performance under local conditions. No direct supervision is required, making it cost-effective and scalable, especially in remote areas. Data collection focuses on farmer-reported outcomes such as yield, resilience, and preference, linked to environmental metadata (e.g., soil, climate), socio-economic metadata (e.g., market preferences, household dynamics, management practices) and DNA metadata.
- Consumer Testing
Tricot integrates consumer preferences for end-use products (e.g., taste, cooking quality, shelf life). Farmers and end-users assess outputs from tested options (e.g., crops, processed goods) to ensure alignment with market demands. The approach helps bridge the gap between agricultural production and consumer needs by combining field performance with end-user satisfaction.
- Concept Testing
Tricot can be used to evaluate broader concepts, such as innovative farming practices, new varieties and agroforestry designs. Participants compare three alternatives in usability, practicality, or benefits, ensuring the development of context-specific solutions. This iterative testing phase supports refining ideas before large-scale implementation.
- Farmer-Centric Data and Decision Support
By empowering farmers as co-researchers, tricot generates farmer-driven data, enriching breeding programs and product development pipelines. Insights into environmental interactions and user preferences guide demand-driven breeding and agricultural innovation. The ClimMob Platform enable real-time data collection, analysis, and visualization to inform decision-making.
- Scaling and Adaptation
Tricot's simplicity allows broad implementation across geographies, crops, and technologies. The model is adaptable to low-resource settings, supporting smallholders while enabling private sector product testing. It also fosters inclusivity, involving women, youth, and marginalized groups in the innovation process.
- Outcomes and Impact
Enhances crop diversity and resilience by tailoring recommendations to local needs. Increases adoption rates by aligning product characteristics with farmer and consumer preferences. Supports sustainable and climate-adaptive agriculture by integrating real-world testing with robust scientific analysis. In summary, the tricot approach is a dynamic, end-to-end solution for product use testing in agriculture, integrating farmer trials, consumer insights, and conceptual testing. It drives innovation by prioritizing user needs, ensuring product relevance, and enabling resilient and inclusive agricultural systems.
Online Reading
You can read this book on-line at the following link:
https://agrdatasci.github.io/documentation/
License
See LICENSE for details.
Owner
- Name: AgrDataSci
- Login: AgrDataSci
- Kind: organization
- Email: k.desousa@cgiar.org
- Location: France
- Repositories: 8
- Profile: https://github.com/AgrDataSci
We develop methods and tools to support sustainable food systems, rural development and digital inclusion
GitHub Events
Total
- Issues event: 1
- Watch event: 2
- Delete event: 1
- Issue comment event: 3
- Push event: 71
- Pull request event: 53
- Create event: 4
Last Year
- Issues event: 1
- Watch event: 2
- Delete event: 1
- Issue comment event: 3
- Push event: 71
- Pull request event: 53
- Create event: 4
Committers
Last synced: over 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Marie-Angélique Laporte | m****e@g****m | 20 |
| kauedesousa | k****a@i****o | 16 |
| Rachel Chase | r****e@c****g | 11 |
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 1
- Total pull requests: 43
- Average time to close issues: N/A
- Average time to close pull requests: about 3 hours
- Total issue authors: 1
- Total pull request authors: 3
- Average comments per issue: 1.0
- Average comments per pull request: 0.12
- Merged pull requests: 41
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 43
- Average time to close issues: N/A
- Average time to close pull requests: about 3 hours
- Issue authors: 1
- Pull request authors: 3
- Average comments per issue: 1.0
- Average comments per pull request: 0.12
- Merged pull requests: 41
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- kauedesousa (1)
Pull Request Authors
- kauedesousa (24)
- rachel-chase (14)
- marieALaporte (5)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- actions/checkout v4 composite
- actions/deploy-pages v4 composite
- actions/setup-node v4 composite
- actions/upload-pages-artifact v3 composite
- 1087 dependencies
- @docusaurus/module-type-aliases 3.1.1 development
- @docusaurus/types 3.1.1 development
- @docusaurus/core 3.1.1
- @docusaurus/preset-classic 3.1.1
- @mdx-js/react ^3.0.0
- clsx ^2.0.0
- prism-react-renderer ^2.3.0
- react ^18.0.0
- react-dom ^18.0.0