Global Forum on Food Security and Nutrition (FSN Forum)

This is a great initiative. In agriculture food system technologies, innovations, adoption and disseminating is a major issue particularly for small-scale farmers/producers particularly in Africa. In my observation scaling up and adoption of technologies and innovations from start-up entrepreneurs seem to be inefficient due to budget limitation. In addition, limted incentives iare alocate  for technological advancement and innovation in develping countries. indigenous knowledge should also be given much attention.

Nature-based solutions have been acknowledged as essential to transforming food systems. It is therefore important that agrifood-systems technologies and innovations be clustered on a biogeographical basis since environmental characteristics determine to a great extent locally-relevant solutions.

https://www.regionsunies-fogar.org/en/media-files/opinion-articles/867-moving-towards-territorial-food-systems-where-are-we-at

It is also important that they contribute to revitalize local economies for sustainable development and resilience https://www.uncdf.org/article/7177/territorial-food-systems-for-sustainable-development-issue-brief-for-un-food-systems-summit

Finally it would be important that the social and environmental impact of each technology/innovation be assessed with a view to ensure accountability.

Dear ATIO Team,

FSN Consultation 
Contribute to shaping the design of the Agrifood System Technologies & Innovations Outlook (ATIO) Knowledge Base 
Submission by:  Suleymen Abdureman Omer (MA Candidate in Public policy & Management) is BSc and MSc in Rural Development & Agricultural Extension (Rural Development stream) from Haramaya University, Ethiopia.

What is Crowdsourcing? 
To fulfil the demands of a growing population, agriculture must provide food and feed that is healthy, high-quality, and safe in an efficient, sustainable manner. Because of climate change and the necessity to preserve local agricultural production, food production will encounter challenges in the future. As a result, sustained effort is required to grow crops with higher and more reliable yields.
The current agricultural production system is based on low diversity and high chemical inputs, which undermines the long-term sustainability of food systems and the essential ecosystem services. The transition to diversified and sustainable production systems is essential and urgent, and depends on our ability to harness the transformative power of agricultural biodiversity. Such transitions, coupled with improved conservation practices, will reduce pressure on terrestrial and marine ecosystems by protecting productivity, restoring ecosystem services and improving ecological connectivity between protected areas. 
To improve crop productivity in regions where formal seed systems do not exist and a number of participatory techniques to variety development and transmission have been developed to target the diverse environments, crops, and varieties for Ethiopian farmers. Crowdsourcing, community seed banks, seed fairs, participatory variety selection and participatory plant breeding have all been utilized to promote innovation, access to seeds, and diversity in informal seed systems.  
Crowdsourcing is the process of enlisting a group of people to work toward a common objective or resolve a current issue, particularly to ensure the sustainable growth of agricultural operations. It has modern technology and social network. Social network is a source of information and concepts, which pushes contemporary businesses to utilize crowdsourcing and discover how to get the most out of it, including acquiring new knowledge. By using crowdsourcing, it is feasible to select the finest ideas submitted by a large number of responders as opposed to depending just on the credentials and experience of one individual. 
It is now simpler than ever for people to get together and offer ideas, time, experience, or money to a project or cause on many different levels and across many different industries. Crowdsourcing is the communal mobilization in action. It is a method of using people or groups of people, paid or unpaid, who are connected with one another through a shared interest to advance powerful increased results through their aggregated actions or activities. 
The crowdsourcing methodology is an alternative to conventional practices because it supports farmers’ on-farm selection of varieties based on seed performance in different agroecological and climatic zones of a given location. This way, the farmers got an opportunity to access different varieties of different crops. This has improved the informal seed system, through exchange and purchase of the varieties among farmers. 

Why Crowdsourcing? 
For many rural households around the world, access to new crop types, agricultural supplies, and expertise is essential. But discovering new technology frequently faces challenges: For instance, access may be hampered by the difficulty of reaching some isolated rural regions, the lack of established markets for seeds and crop inputs, or the lack of knowledge about new crop inputs or varieties. Due to insufficient inputs, the same cultivars are frequently cultivated year after year. 
Crowdsourcing is quickly becoming a popular innovation platform for organizations. The crowd appears to have a solution for every innovation issue; they can think up concepts for novel toys and provide answers to urgent scientific difficulties. In actuality, the crowd has great potential: a large, diverse group, consisting of experts and non-experts from over the globe, ought to have new viewpoints to provide ground-breaking ideas on a particular issue. Organizations may engage their participants and generate their interest in addition to accessing amazing ideas. 
By turning to an oversized cluster of individuals for ideas and solutions, crowdsourcing will generate plenty of advantages over internal thinking processes. 
Among the benefits of crowdsourcing is:  
➢  The ability to find unexpected solutions by involving a broader cluster of individuals in resolution a haul, an organization will gain access to hundreds or perhaps thousands of various approaches to come to  resolution. 
➢  Greater diversity of thinking  
➢  Reduced management burden 
➢  Faster problem solving 
➢  A rich source of data 
For agricultural sector, the crowdsourcing approach has been very effective  to disseminate seeds that match farmers needs in a very short period as after 2 years already several hundred farmers have the potential to use better adapted material, with a large snowball effect potential. With a significant potential for a snowball effect, the crowdsourcing technique has been very successful in rapidly disseminating seeds that are tailored to farmers' needs. After only two years, several hundred farmers are already able to use more suitable materials.
Crowdsourcing approach demonstrates how landraces can offer an immediate solution for reducing climate -related hazards and calls for greater use of the genetic resources preserved in gene banks; suggests that in order to sustainably manage these resources, local seed systems must be st rengthened;It demonstrates how farmers can offer extremely useful scientific data that can be applied to other fields of research as well as development outcomes. 
Crowdsourcing approach for variety selection using tricot improve seed systems through enriches variety recommendations, improves on-farm testing, engages and empowers farmers, contributes to a diversification of seed systems, supporting scaling of on-farm agricultural research, enables women to do their own variety selection, offers business opportunities for farmers, women and young people, gets researchers to learn farmers’ variety preferences.  
In this case, varieties are grown on  farmers' fields as  trial plot it has an additional advantage because it allows a larger number of farmers to participate. This helps to  collect extra data on performance at various altitudes or in various climatic conditions. 
They provide their input in an easy-to-read format, rating each package for several characteristics as "best, midrange, or worst". These farmer-generated data are then merged with socioeconomic and environmental variables and ranked using particular, cutting-edge statistical techniques. It has been feasible to show how varieties are differentially suited to various growth circumstances across broad areas using the tricot technique. Additionally, it enables a lot more farmers to take part in participatory trials, which directly impacts the spread of varieties. 
This strategy enables farmers serve as local scientists, testing, observing, contrasting, and trying novel agricultural methods and crop rotations to find what works best for them in terms of yield as well as resiliency, nutrition, taste, and resistance to pests and diseases. 
Generally, as part of their routine duties, development agents monitor the farmers throughout the process and offer advice. They can learn with farmers about how various kinds fare in various soils and micro-ecologies in this way. 
The crowdsourcing methodology supports the scalability of on-farm agricultural research, which enhances seed systems. Because seed distribution and evaluation are significantly simpler, information-based tasks can now be scaled to new levels that were previously impractical thanks to the tricot technique. Larger sets of types can be compared by providing farmers with alternative, partially overlapping combinations of technologies.
The method can engage a large number of farm households, which can help to get beyond the limited scalability and free-rider issue in existing participatory methodologies. As a result, it is possible to scale on-farm agricultural research using a crowdsourcing approach. 
Seed-based innovation must concentrate on the variety of crops that make up farmers' fields and diets if it is to provide food for the most vulnerable households. 
By adapting crop varieties to various production situations and diversifying their portfolio to reduce risks, a variety of crop species and varieties aid farmers in coping with environmental limitations. For instance, scientists found convincing evidence that increasing varietal diversity boosts agricultural output in the highlands of Ethiopia in a properly planned study.
When rainfall levels were low, the effect was considerably more pronounced. However, independent of production, crop and varietal diversity may also have immediate nutritional impacts. There is strong proof that dietary diversification and micronutrient intake are related. It is reasonable to anticipate that increasing crop diversification for farmers with limited resources will significantly improve the food security of their households. Therefore, the major strategy for improving nutrition for small-scale households is to enhance diversity through crowdsourcing approach. 
Validate varieties and enhance availability by distributing them through crowdsourcing approaches  
Main purpose/ core deliverables 
➢  The world is affected by climate change and consequently affecting agricultural productivity, that led farmers to be unsecured and vulnerable. The bad thing about climate change is its unpredictability. Therefore diversifying agriculture at species/variety level will secure farmers from the total loss of harvest.  
➢  Crowd sourcing approach uses multiple superior varieties (genotypes) that are tested by the community themselves after selection from diversity block as best in bad season and others best in good season. Then since the climate is unpredictable, when the season is bad the farmer will harvest  genotype that suits bad condition and if the season is good he/she will have a chance to get premium production from all genotypes. Therefore, diversifying varieties/genotypes is a means for food security at household level sustainably. These tool will enable to reach large farmers in few resources in short period of time. 
➢  Using diversified genotypes and/or species is also help farmers to be resilient from sporadic outbreak of diseases and pests. Since the genetic makeup of different genotypes and species is different, they will not be attacked by one time appearing disease or pest race all at the same time.

Suitability and adaptability of crowdsourcing to local knowledge         
The use of crowdsourcing approaches is strongly tied to traditional knowledge. The farmer preferred varieties identified in the previous step are distributed to farmers in small batches and tested under their own management practices and soil conditions. 
A big advantage of this approach is that growers can test varieties throughout the growing season and not just for one day. So they can really appreciate the seed's potential for uses that are important to them. , they can truly understand them.  
This approach makes it possible to reach out to a larger number of farmers and involve them fully in the assessment compared to traditional approaches. The costs to farmers are much lower because the extension or research system does not have to administer the trials themselves. 
Main land use and agro ecology for crowdsourcing approach 
There are specific crops and varieties that can be employed in each area and agro-ecology to increase production and resilience as well as offer new opportunities for a livelihood. 
Although using diverse crops, the crowdsourcing approach is appropriate for all agroecologies and soil types.
How to carry out crowdsourcing? 
Description of the technology 
The application of diversity agriculture in conjunction with other technologies is possible. A tricot plot design can be used as a manner of demonstrating and scaling out a crowdsourcing approach to rich an infinite number of farmers quickly. Diversity agriculture can be integrally used with other technologies. As a way of demonstration and scaling up a crowdsourcing approach can be used to rich uncountable number of farmers in short period. 
Innovation has produced a practical method for the field evaluation of varieties that might also be applied in the field of agricultural research.
Farmers participate in Tricot's crowdsourcing strategy as "citizen scientists," helping researchers with data generation and collection. The technique enables the split of large tasks into smaller, more manageable ones that may be distributed across a wide number of individuals through the use of an incomplete block design. The planting material is randomized into incomplete blocks of three varieties. Each farmer gets a package of seeds with three varieties that are coded to plant and score in their own field. 
The principles of tricot can be applied equally to other agricultural technologies, like fertilizers, compost, and other inputs, or post-harvest techniques.
Summary of  the Crowdsourcing 
Crowdsourcing is a method of enlisting a group of people to work toward a common objective or solve a pressing issue, notably to ensure the sustainable expansion of agricultural activities. By using crowdsourcing, it is feasible to select the finest suggestions made by a large number of responders as opposed to depending simply on the credentials and experience of one individual. By seeking ideas and solutions from a broad group of individuals, crowdsourcing is superior to internal thought processes in many ways.
This technique for variety selection improves seed systems by enhancing variety recommendations, enhancing on-farm testing, engaging and empowering farmers, aiding in the diversification of seed systems, supporting the scaling up of on-farm agricultural research, allowing women to make their own variety selections, supplying business opportunities for farmers, women, and young people, and helping researchers learn farmers' variety preferences. 
The primary techniques for putting crowdsourcing into practice include component identification, identifying farmers who are receiving various mixtures of varieties, seed preparation, site selection and planting, cultivation, measurements and observations, and proper harvesting.

1. Given the description of the ATIO KB, how do you think it can help you and users like you? Describe one or more specific use cases that you wish the KB would address, like “I imagine I would be able to find innovative products that support farmers with access to credit and insurance specifically for one country, and I would be able to see information on their readiness and how they fare against adoptability criteria” or “I would like to use statistics to show a correlation between level of inclusivity / codesign of the solutions and their levels of adoption”. 

Overall, for private companies in the agri-food sector, the ATIO KB can serve as a critical tool for decision-making, product development, market analysis, and investment prioritization, enabling to leverage science, technology, and innovation effectively. 
Use Case 1: Identifying Innovative Products for Specific Regions 
As a company involved in the agrifood system, the ATIO KB can be a useful resource for identifying innovative products tailored to specific regions. For instance, if we are looking to introduce a new product in a particular country, the ATIO KB can provide detailed information on existing similar products, their readiness levels, and how they fare against adoptability criteria such as profitability, accessibility, acceptability, and sustainability. This information can help companies make informed decisions about market entry and product development. 
Use Case 2: Correlating Inclusivity and Adoption Rates 
Another use case is utilizing the ATIO KB's statistical data to analyze the correlation between the level of inclusivity or co-design of solutions and their adoption rates. By accessing structured data on various innovations, we can identify patterns and insights that demonstrate the impact of inclusive and participatory approaches on the success of agricultural technologies. This can guide companies’ strategies for developing and promoting products that are more likely to be adopted by diverse user groups. 
Use Case 3: Access to Grassroots Innovations 
The ATIO KB's focus on grassroots innovations is particularly relevant for the training programs implemented by companies for their costumers (e.g. farmers, processors, retailers, consumers, etc). By accessing information on customer-led innovations and their contextual applications, companies can incorporate these grassroots solutions into their training modules, thus promoting locally relevant and sustainable practices. For example, companies might find innovative irrigation techniques developed by local farmers that can be scaled and adapted to other regions. 
Use Case 4: Investment and Research Prioritization 
The comprehensive data in the ATIO KB can help companies identify gaps and investment opportunities in the agrifood sector. By analyzing the lifecycle coverage of various technologies and innovations, we can prioritize research and development efforts in areas with high potential for impact and scalability. This strategic approach can enhance the companies’ product portfolio and contribute to the transformation of agrifood systems. 

2. What do you make of concepts like policy innovation and social innovation? Can you think of examples? Is it useful for you to be able to find such content? In which form do you expect to find them? How would you use them? 

Policy Innovation refers to the development and implementation of new and effective policies that address existing problems or improve upon current policies. In the context of agrifood systems, policy innovation could involve creating regulations and policies that support sustainable agricultural practices, promote the adoption of new technologies, or enhance food security. For example, a policy innovation might be the introduction of subsidies for farmers who adopt climate-resilient crops or the establishment of new frameworks for carbon farming initiatives. 
Social Innovation involves the creation and implementation of new strategies, concepts, ideas, and organizations that meet social needs and foster social relationships and collaborations. In agrifood systems, social innovations could include community-supported agriculture (CSA), where consumers directly support local farmers, or the establishment of cooperatives that empower small-scale farmers and improve their market access. Another example could be the development of digital platforms that connect farmers with buyers, reducing intermediaries and ensuring fair prices for agricultural products.

Usefulness of Finding Such Content: 
For a private company, being able to find content on policy and social innovations is highly useful. These innovations can provide insights into successful strategies and models that can be adapted or replicated in different contexts. Understanding policy innovations can help companies align their operations and solutions with local regulations and take advantage of government incentives. Social innovations, on the other hand, can guide companies in developing initiatives that create shared value for both the companies and the communities that they serve. 
Expected Form of Content: We would expect to find content on policy and social innovations in several forms: 
Interactive Databases: Searchable databases that allow users to filter and browse through different types of policy and social innovations. These databases should include metadata such as the geographical location, target beneficiaries, and the specific issues addressed by the innovations. 
Reports and Publications: Comprehensive reports that analyze the impact of various policy and social innovations on agrifood systems. These reports should provide data and evidence to support the effectiveness of these innovations. Case Studies: Detailed descriptions of specific policy or social innovations, including their objectives, implementation processes, challenges faced, and outcomes. Case studies should highlight best practices and lessons learned. Infographics and Visual Summaries: Visual representations of key information related to policy and social innovations. Infographics can make complex information more accessible and easier to understand at a glance. Webinars: Interactive sessions where experts and practitioners share their experiences and insights on policy and social innovations. These sessions can facilitate knowledge exchange and networking among stakeholders. 
Usage of Content: We would use the content on policy and social innovations in several ways: 
Strategic Planning: Integrate successful policy and social innovation models into the companies’ strategic plans to enhance their operations and community engagement efforts. 
Product Development: Develop new products or services that align with innovative policies or address social needs identified through social innovations. Advocacy and Partnerships: Advocate for supportive policies and collaborate with stakeholders to implement social innovations that benefit the agrifood sector. 
Training and Capacity Building: Incorporate insights from policy and social innovations into the company’s training programs for farmers and other stakeholders to promote best practices and sustainable development. 
3. How important is it to feature grassroots innovations? Looking at some records of grassroots innovations in the prototype, what would you like to see in the descriptions that you don’t see? Which dimension should we capture? What is most useful for grassroots use/application of innovations?  
Grassroots innovations are crucial for several reasons. They often emerge from the practical experiences and needs of local communities, making them highly relevant and context-specific. These innovations can offer sustainable and affordable solutions that are tailored to the local environment and socio-economic conditions. By featuring grassroots innovations, the ATIO KB can ensure that the knowledge base is inclusive and representative of diverse innovation sources, thereby promoting a more equitable and holistic approach to agrifood system transformation. 
Desired Descriptions for Grassroots Innovations: 
When looking at records of grassroots innovations in the prototype, it is essential to include comprehensive descriptions that capture the following dimensions: Context and Origin: Detailed background information on the local context where the innovation was developed, including geographical, cultural, and socio-economic factors. This helps in understanding the relevance and applicability of the innovation in similar contexts. Problem Addressed: Clear explanation of the specific problem or challenge that the innovation aims to solve. This should include the impact of the problem on the community and how the innovation addresses it effectively. Development Process: Information on how the innovation was developed, including the role of local knowledge, experimentation, and collaboration among community members. Highlighting the participatory nature of the development process can demonstrate the innovation's inclusivity and adaptability. 
Implementation and Adoption: Details on how the innovation was implemented, including any pilot projects, trials, or scaling efforts. Information on adoption rates and feedback from users can provide insights into the innovation's effectiveness and potential for wider application. 
Impact and Benefits: Quantitative and qualitative data on the benefits and impact of the innovation, such as improved yields, cost savings, environmental sustainability, and social benefits. This should include testimonials or case studies from users and community members. 
Challenges and Lessons Learned: Discussion of any challenges faced during the development and implementation of the innovation, as well as lessons learned. This can provide valuable insights for others looking to replicate or adapt the innovation. 
Scalability and Replicability: Assessment of the innovation's potential for scaling and replicability in other regions or contexts. This should include any necessary adaptations or considerations for different environments. Sustainability: Information on the long-term sustainability of the innovation, including environmental, economic, and social dimensions. This can help in evaluating the innovation's viability and contribution to sustainable development goals. 
Most Useful Dimensions for Grassroots Use/Application of Innovations: For grassroots use and application of innovations, the most useful dimensions to capture are: Accessibility: Information on how easily the innovation can be accessed and adopted by local communities, including cost, availability of materials, and required skills or knowledge. Cultural Acceptability: Understanding of how well the innovation fits within the local cultural practices and values. Innovations that align with cultural norms are more likely to be accepted and adopted. 
Scalability: Potential for the innovation to be scaled up or adapted to different contexts. This includes identifying any barriers to scaling and strategies to overcome them. Environmental Impact: Assessment of the innovation's impact on the environment, including any benefits or potential negative effects. Sustainable innovations that protect or enhance the environment are highly valuable. 
Economic Viability: Analysis of the economic benefits of the innovation, such as cost savings, increased income, or improved productivity. This helps in understanding the financial feasibility and attractiveness of the innovation. Community Involvement: Degree of community involvement in the development and implementation of the innovation. Innovations that involve and empower local communities are likely to be more sustainable and impactful. 
By capturing these dimensions, the ATIO KB can provide a comprehensive and valuable resource for grassroots innovators, policy makers, and other stakeholders, enabling them to identify, assess, and adopt effective and sustainable innovations. 

4. How do you think branded commercial products should be featured on the ATIO KB? Data sources of technology-related information often feature individual models of technologies (for instance, different models of solar-powered irrigation pumps). Should the ATIO KB feature models? What is the “innovation” unit you expect to find? 

The ATIO KB should encompass both broader categories of innovations and individual models of technologies (including branded commercial products). By featuring both individual models and broader categories of innovations with detailed, holistic information, the ATIO KB can provide a valuable resource for policy makers, investors, innovators, and potential adopters, helping them make informed decisions and promote the adoption of appropriate and sustainable technologies in the agrifood sector. 
The knowledge base should include: 
Categories of Innovations: Broader categories that group similar technologies or innovations together, providing an overview of the types of solutions available for a particular problem or application. This helps users understand the landscape of available innovations and identify trends and patterns. 
Individual Models: Detailed profiles of specific models of technologies, including technical specifications, performance metrics, cost, and user reviews. This helps users compare and select the most appropriate model for their needs. Branded commercial products should be featured on the ATIO KB to provide a comprehensive view of available, real-world technologies and innovations in the agrifood sector. Including commercial products can help users compare different solutions, understand market trends, and make informed decisions based on a wide range of options. It also allows for the identification of gaps and opportunities for new product development. 
The ATIO KB should provide holistic information on each innovation, including: Technical Specifications: Detailed technical data such as capacity, efficiency, energy consumption, and other relevant metrics. 
Use Cases: Examples of how the technology has been used in different contexts, including case studies and testimonials from users. Adoptability Criteria: Information on the readiness, accessibility, acceptability, profitability, and sustainability of the technology. This includes any required complementary inputs and the socio-economic impact of adopting the technology. Environmental and Social Impact: Assessment of the environmental footprint and social implications of the technology, including its impact on gender, minorities, and local communities. Scalability and Replicability: Analysis of the potential for scaling the technology and replicating it in different regions or contexts. 
Partnerships and Collaborations: Information on partnerships and collaborations that have supported the development and deployment of the technology, including funding sources and supporting organizations. 

5. Here are two of the main taxonomies used in the prototype: types of innovations and use cases. Considering that there is no agreed standard for these categorizations, and that we are aligning them to those used in similar projects, are these “good enough” to start? Which major problems do you see? Please suggest changes or volunteer to help us improve them in the next months. Other taxonomies are here. 

The taxonomies “types of innovations” and “use cases” are a good starting point. They provide a basic structure for organizing the information and make it easier for users to navigate the knowledge base. However, there are potential improvements and considerations to enhance their effectiveness: 
Potential Limits and Suggestions for Improvement: 
Granularity and Specificity: The current taxonomies might be too broad or too narrow in certain areas. It is essential to strike a balance between granularity and specificity to ensure that users can find relevant information without being overwhelmed by too many categories. We suggest conducting a thorough analysis of user needs and feedback to refine the categories and subcategories. This could involve creating more specific subcategories under broader categories to capture the diversity of innovations and use cases. 
Dynamic and Evolving Nature: Innovations and their applications are continuously evolving. Static taxonomies may become outdated quickly. We suggest implementing a dynamic taxonomy system that can be regularly updated based on new insights, emerging trends, and user feedback. This could involve using AI-assisted routines to identify and incorporate new categories and subcategories as they emerge. 
Interdisciplinary and Cross-cutting Innovations: Some innovations may span multiple categories or use cases, making it challenging to classify them under a single category. It is suggested to allow for multiple categorizations or tagging of innovations to capture their interdisciplinary and cross-cutting nature. This can help users find innovations that may not fit neatly into a single category but are relevant to multiple areas. 
Alignment with Existing Standards: While there are no universally agreed standards, aligning with existing classifications used by similar projects can enhance interoperability and consistency. We suggest continuing aligning the taxonomies with those used in similar efforts by FAO and other international stakeholders. Engage in consultations with stakeholders and experts to ensure the taxonomies are relevant and useful. 
Other Taxonomies: 
In addition to types of innovations and use cases, other taxonomies that could be considered include: 
Stage of Development and Readiness Level: Categorizing innovations based on their development stage, such as concept, prototype, pilot, or commercialized. 
Accessibility Features: Categorizing innovations based on their accessibility to different user groups, including cost, availability, and ease of use. 
Impact Dimensions: Classifying innovations based on their impact on various dimensions, such as environmental sustainability, social equity, economic viability, and gender inclusivity. 
By incorporating these additional taxonomies, the ATIO KB can provide a more comprehensive and nuanced view of agrifood systems innovations, helping users make better-informed decisions and promoting the adoption of appropriate and sustainable solutions. We are open to volunteering to help improve the taxonomies over the next months. This could involve participating in consultations, providing feedback based on the private sector’s expertise and user experiences, and collaborating with the ATIO KB team to refine the classification systems. 

6. We are developing a chatbot-like search capability. Do you prefer the classic filterbased search or the chatbot search? Or the possibility of choosing either? Tell us how we can improve the search experience. 

Classic Filter-Based Search: 
The classic filter-based search allows users to narrow down their search results by applying various filters such as categories, tags, or specific criteria. This method is straightforward and efficient for users who know exactly what they are looking for and prefer a structured approach to finding information. It provides a clear and systematic way to explore the database, making it easy to compare different entries based on selected attributes. Advantages: 
Precision: Users can precisely narrow down results using specific filters. 
Structure: Provides a clear and organized way to browse through information. 
User Control: Users have full control over the filtering criteria and can adjust them as needed. Chatbot Search: 
A chatbot-like search capability offers a more interactive and conversational approach to finding information. Users can ask questions in natural language, and the chatbot can provide relevant answers, suggest related topics, and guide users through the knowledge base. This method is particularly useful for users who are not sure how to formulate their search queries or prefer a more guided and dynamic search experience. Advantages: 
User-Friendly: Offers a more intuitive and conversational way to search for information. 
Guidance: Can help users refine their queries and suggest related information. 
Accessibility: Makes it easier for users with varying levels of expertise to find relevant information. 
Combination of Both: 
Given the diverse needs of users, offering both classic filter-based search and chatbot search capabilities would be the ideal solution. This hybrid approach allows users to choose the method that best suits their preferences and specific needs at any given time. 
Expert Users: May prefer the precision and control of the filter-based search. Novice Users: May benefit from the guidance and ease of the chatbot search. Suggestions: Advanced Search Features: For the filter-based search, include advanced search features such as Boolean operators, proximity searches, and wildcard searches to enhance search capabilities. Seamless Integration: Ensure that users can easily switch between the filter-based search and the chatbot search within the same interface. For example, the chatbot could suggest filters to apply based on the user's queries, and vice versa. Contextual Assistance: Implement contextual assistance within the chatbot to help users understand how to use filters effectively. The chatbot could provide tips and examples of how to refine searches using filters. Personalization: Allow users to save their search preferences and frequently used filters. The chatbot could learn from user interactions and offer personalized suggestions based on past queries and behaviors. 
Feedback Mechanism: Include a feedback mechanism for users to rate the effectiveness of search results and provide suggestions for improvement. This feedback can be used to continuously refine both the filter-based and chatbot search functionalities. Comprehensive Help Section: Provide a comprehensive help section that explains how to use both search methods, with tutorials, FAQs, and example queries. This can help users become more proficient in using the knowledge base. By offering both classic filter-based search and chatbot search, and continuously improving these features based on user feedback and technological advancements, the ATIO KB can provide a versatile and user-friendly search experience that caters to a wide range of user needs and preferences. 

7. We use Artificial Intelligence (AI) to enrich and automatically categorize the records: you will see an AI stamp at the end of descriptions that have been generated by AI: how good is the text generated? Is AI enriching the records in a meaningful way? 

The AI-generated text in the ATIO KB has the potential to significantly enrich the records and provide meaningful insights to users. However, it is crucial to ensure that the AI-generated content is accurate, relevant, and of high quality. A robust human review process, continuous improvement of AI algorithms, and user feedback mechanisms are essential to achieving this goal. By leveraging AI effectively, the ATIO KB can become a comprehensive, dynamic, and user-friendly resource for agrifood systems innovations. 
Benefits of using AI in ATIO KB: 
Efficiency: AI can significantly enhance the efficiency of data processing and content generation. By automating the categorization and initial description of records, AI can handle large volumes of data quickly, ensuring that the ATIO KB remains up-to-date and comprehensive. 
Comprehensiveness: AI can help identify patterns and connections within the data that might be overlooked by human curators. This can lead to more comprehensive and holistic records that capture the full spectrum of information relevant to each innovation. 
Scalability: The use of AI allows the ATIO KB to scale its operations effectively. As more data sources are integrated and more innovations are documented, AI can manage the increased workload without compromising on quality. Continuous Improvement: AI systems can learn and improve over time based on user interactions and feedback. This means that the quality of AI-generated content can continuously improve, becoming more accurate and insightful as the system evolves. Contextual Information: AI can enrich records with contextual information that enhances their usefulness. This includes linking related innovations, providing background information on the socio-economic context, and highlighting key adoption criteria. 
User-Centric Insights: AI can tailor the content to the needs of different user groups. For example, policy makers might need information on regulatory impacts, while farmers might be more interested in practical implementation tips. AI can generate content that addresses these diverse needs. Interactive Features: AI can support interactive features such as chatbots and dynamic filtering, making it easier for users to find relevant information and insights. This enhances the overall user experience and makes the knowledge base more accessible. 
The quality of AI-generated text should be assessed based on: 
Accuracy and Relevance: The AI-generated text should be accurate, relevant, and context specific. The information provided must align with the actual data and insights from the sources it draws upon. The AI should be capable of understanding the nuances of agrifood systems and the specific needs of the ATIO KB users. 
Clarity and Readability: The text generated by AI should be clear, concise, and easily understandable. It should avoid technical jargon unless necessary and should be written in a way that is accessible to a broad audience, including policy makers, researchers, and farmers. Depth and Insight: The AI-generated content should provide meaningful insights and not just surface-level information. It should capture the complexity and multifaceted nature of innovations, including technical specifications, use cases, and socio-economic impacts. 
Consistency: The AI should generate text that is consistent in style and tone with the rest of the content in the ATIO KB. This ensures a cohesive user experience and maintains the credibility of the knowledge base. 
Evaluation Process: To evaluate the quality of AI-generated text, it is essential to have a human review process in place. Experts in agrifood systems should review the AI-generated content to ensure its accuracy, relevance, and quality. Feedback from these reviews can be used to improve the AI algorithms. 
 

Key Technologies and Innovations
1. Precision climate smart agriculture and Agricultural mechanization, urban agriculture
2. Genomics and Genetic Engineering: Improved breeding programs and disease resistance.
3. Artificial Intelligence (AI) and Machine Learning (ML): Predictive analytics, automated monitoring, and optimization.
4. Internet of Things (IoT): Real-time monitoring, automation, and data collection.
5. Blockchain: Transparent supply chain management and traceability.
6. Vertical Farming and Aquaculture: Sustainable, space-efficient production.
7. Synthetic Biology: Novel feed supplements and nutrient-enhanced products.
Grassroots Innovations
1. Community-based climate smart agriculture  programs: Localized, adaptive breeding strategies.
2. Indigenous knowledge sharing: Traditional practices integrated with modern technology.
3. Farmer-led research and development: Participatory approaches to innovation.
4. Mobile apps for farmers: Accessible, user-friendly tools for decision-making.
Global Initiatives and Collaborations
1. FAO's (Food and Agriculture Organization) Animal Production and Health Division: Global standards and guidelines.
2. World Organisation for Animal Health (OIE): International cooperation on animal health.
3. Global Alliance for Livestock Veterinary Medicines (GALVmed): Accessible veterinary medicines.
4. Haramaya University  and others: Research and development partnerships.
5. Agrifood innovation hubs: Regional centers facilitating collaboration and knowledge sharing.
Innovation Life Cycle
1. Research and Development: Basic and applied research.
2. Prototyping and Testing: Validation and refinement.
3. Pilot Scaling: Small-scale implementation.
4.Commercialization: Large-scale adoption.
5. Diffusion and Adoption: Global dissemination.
6. participatory varity selection and crowdsources 
Relevant Use Cases
1. Sustainable climate smart agriculture production: Environmental sustainability and climate resilience.
2. Improved animal welfare: Enhanced health and well-being.
3. Increased productivity: Efficient breeding, nutrition, and health management.
4. Enhanced food safety: Traceability and quality control.
5. Market access and trade: Global market integration.
6. Climate change mitigation: Reduced greenhouse gas emissions.
7. Nutrition and health: Biofortified products and nutrient-rich foods.
Future Directions
1. Integration of AI and biotechnology: Enhanced precision and efficiency.
2. Circular economy approaches: Waste reduction and valorization.
3. Inclusive and equitable innovation: Empowering small-scale farmers.
4. Global knowledge sharing: Collaborative research and development.
5. Policy and regulatory frameworks: Supporting innovation and sustainability.

Best Regrads,

Suleymen Abdureman Omer (MA Candidate in Public policy & Management) is BSc and MSc in Rural Development & Agricultural Extension (Rural Development stream) from Haramaya University, Ethiopia
Email: [email protected] ,  [email protected]
Mobile: +251920268645
https://www.linkedin.com/in/suleymen-abdureman-omer-63b091126
ORCID ID: https://orcid.org/0000-0001-7565-5851
https://www.researchgate.net/profile/Suleymen-Omer-4
https://scholar.google.com.au/citations?user=Jn3515AAAAAJ&hl=en

Dear ATIO team

Please, find attached my submission on behalf of Bayer Crop Science for the FSN Consultation on the ATIO Knowledge Base. I appreciate the opportunity to contribute and look forward to any feedback or further discussions.

Best regards,
Stefano Marras
Director, Global Partnerships – UN Affairs
Bayer Crop Science

• Product Development: Develop new products or services that align with innovative policies or address social needs identified through social innovations.
• Advocacy and Partnerships: Advocate for supportive policies and collaborate with stakeholders to implement social innovations that benefit the agrifood sector.
• Training and Capacity Building: Incorporate insights from policy and social innovations into the company’s training programs for farmers and other stakeholders to promote best practices and sustainable development.

3. How important is it to feature grassroots innovations? Looking at some records of grassroots innovations in the prototype, what would you like to see in the descriptions that you don’t see? Which dimension should we capture? What is most useful for grassroots use/application of innovations?

Grassroots innovations are crucial for several reasons. They often emerge from the practical experiences and needs of local communities, making them highly relevant and context-specific. These innovations can offer sustainable and affordable solutions that are tailored to the local environment and socio-economic conditions. By featuring grassroots innovations, the ATIO KB can ensure that the knowledge base is inclusive and representative of diverse innovation sources, thereby promoting a more equitable and holistic approach to agrifood system transformation.

Desired Descriptions for Grassroots Innovations:

When looking at records of grassroots innovations in the prototype, it is essential to include comprehensive descriptions that capture the following dimensions:

• Context and Origin: Detailed background information on the local context where the innovation was developed, including geographical, cultural, and socio-economic factors. This helps in understanding the relevance and applicability of the innovation in similar contexts.
• Problem Addressed: Clear explanation of the specific problem or challenge that the innovation aims to solve. This should include the impact of the problem on the community and how the innovation addresses it effectively.
• Development Process: Information on how the innovation was developed, including the role of local knowledge, experimentation, and collaboration among community members. Highlighting the participatory nature of the development process can demonstrate the innovation's inclusivity and adaptability.
• Implementation and Adoption: Details on how the innovation was implemented, including any pilot projects, trials, or scaling efforts. Information on adoption rates and feedback from users can provide insights into the innovation's effectiveness and potential for wider application.
• Impact and Benefits: Quantitative and qualitative data on the benefits and impact of the innovation, such as improved yields, cost savings, environmental sustainability, and social benefits. This should include testimonials or case studies from users and community members.
• Challenges and Lessons Learned: Discussion of any challenges faced during the development and implementation of the innovation, as well as lessons learned. This can provide valuable insights for others looking to replicate or adapt the innovation.
• Scalability and Replicability: Assessment of the innovation's potential for scaling and replicability in other regions or contexts. This should include any necessary adaptations or considerations for different environments.
• Sustainability: Information on the long-term sustainability of the innovation, including environmental, economic, and social dimensions. This can help in evaluating the innovation's viability and contribution to sustainable development goals.

Most Useful Dimensions for Grassroots Use/Application of Innovations:

For grassroots use and application of innovations, the most useful dimensions to capture are:

• Accessibility: Information on how easily the innovation can be accessed and adopted by local communities, including cost, availability of materials, and required skills or knowledge.
• Cultural Acceptability: Understanding of how well the innovation fits within the local cultural practices and values. Innovations that align with cultural norms are more likely to be accepted and adopted.
• Scalability: Potential for the innovation to be scaled up or adapted to different contexts. This includes identifying any barriers to scaling and strategies to overcome them.
• Environmental Impact: Assessment of the innovation's impact on the environment, including any benefits or potential negative effects. Sustainable innovations that protect or enhance the environment are highly valuable.
• Economic Viability: Analysis of the economic benefits of the innovation, such as cost savings, increased income, or improved productivity. This helps in understanding the financial feasibility and attractiveness of the innovation.
• Community Involvement: Degree of community involvement in the development and implementation of the innovation. Innovations that involve and empower local communities are likely to be more sustainable and impactful.

By capturing these dimensions, the ATIO KB can provide a comprehensive and valuable resource for grassroots innovators, policy makers, and other stakeholders, enabling them to identify, assess, and adopt effective and sustainable innovations.

4. How do you think branded commercial products should be featured on the ATIO KB? Data sources of technology-related information often feature individual models of technologies (for instance, different models of solar-powered irrigation pumps). Should the ATIO KB feature models? What is the “innovation” unit you expect to find?

The ATIO KB should encompass both broader categories of innovations and individual models of technologies (including branded commercial products). By featuring both individual models and broader categories of innovations with detailed, holistic information, the ATIO KB can provide a valuable resource for policy makers, investors, innovators, and potential adopters, helping them make informed decisions and promote the adoption of appropriate and sustainable technologies in the agrifood sector.

The knowledge base should include:

• Categories of Innovations: Broader categories that group similar technologies or innovations together, providing an overview of the types of solutions available for a particular problem or application. This helps users understand the landscape of available innovations and identify trends and patterns.
• Individual Models: Detailed profiles of specific models of technologies, including technical specifications, performance metrics, cost, and user reviews. This helps users compare and select the most appropriate model for their needs. Branded commercial products should be featured on the ATIO KB to provide a comprehensive view of available, real-world technologies and innovations in the agrifood sector. Including commercial products can help users compare different solutions, understand market trends, and make informed decisions based on a wide range of options. It also allows for the identification of gaps and opportunities for new product development.

The ATIO KB should provide holistic information on each innovation, including:

• Technical Specifications: Detailed technical data such as capacity, efficiency, energy consumption, and other relevant metrics.
  • Use Cases: Examples of how the technology has been used in different contexts, including case studies and testimonials from users.
  • Adoptability Criteria: Information on the readiness, accessibility, acceptability, profitability, and sustainability of the technology. This includes any required complementary inputs and the socio-economic impact of adopting the technology.
  • Environmental and Social Impact: Assessment of the environmental footprint and social implications of the technology, including its impact on gender, minorities, and local communities.
  • Scalability and Replicability: Analysis of the potential for scaling the technology and replicating it in different regions or contexts.
  • Partnerships and Collaborations: Information on partnerships and collaborations that have supported the development and deployment of the technology, including funding sources and supporting organizations.

5. Here are two of the main taxonomies used in the prototype: types of innovations and use cases. Considering that there is no agreed standard for these categorizations, and that we are aligning them to those used in similar projects, are these “good enough” to start? Which major problems do you see? Please suggest changes or volunteer to help us improve them in the next months. Other taxonomies are here.

The taxonomies “types of innovations” and “use cases” are a good starting point. They provide a basic structure for organizing the information and make it easier for users to navigate the knowledge base. However, there are potential improvements and considerations to enhance their effectiveness:

Potential Limits and Suggestions for Improvement:

• Granularity and Specificity: The current taxonomies might be too broad or too narrow in certain areas. It is essential to strike a balance between granularity and specificity to ensure that users can find relevant information without being overwhelmed by too many categories. We suggest conducting a thorough analysis of user needs and feedback to refine the categories and subcategories. This could involve creating more specific subcategories under broader categories to capture the diversity of innovations and use cases.
  • Dynamic and Evolving Nature: Innovations and their applications are continuously evolving. Static taxonomies may become outdated quickly. We suggest implementing a dynamic taxonomy system that can be regularly updated based on new insights, emerging trends, and user feedback. This could involve using AI-assisted routines to identify and incorporate new categories and subcategories as they emerge.
• Interdisciplinary and Cross-cutting Innovations: Some innovations may span multiple categories or use cases, making it challenging to classify them under a single category. It is suggested to allow for multiple categorizations or tagging of innovations to capture their interdisciplinary and cross-cutting nature. This can help users find innovations that may not fit neatly into a single category but are relevant to multiple areas.
• Alignment with Existing Standards: While there are no universally agreed standards, aligning with existing classifications used by similar projects can enhance interoperability and consistency. We suggest continuing aligning the taxonomies with those used in similar efforts by FAO and other international stakeholders. Engage in consultations with stakeholders and experts to ensure the taxonomies are relevant and useful.

Other Taxonomies:

In addition to types of innovations and use cases, other taxonomies that could be considered include:

• Stage of Development and Readiness Level: Categorizing innovations based on their development stage, such as concept, prototype, pilot, or commercialized.
• Accessibility Features: Categorizing innovations based on their accessibility to different user groups, including cost, availability, and ease of use.
• Impact Dimensions: Classifying innovations based on their impact on various dimensions, such as environmental sustainability, social equity, economic viability, and gender inclusivity.

By incorporating these additional taxonomies, the ATIO KB can provide a more comprehensive and nuanced view of agrifood systems innovations, helping users make better-informed decisions and promoting the adoption of appropriate and sustainable solutions.

We are open to volunteering to help improve the taxonomies over the next months. This could involve participating in consultations, providing feedback based on the private sector’s expertise and user experiences, and collaborating with the ATIO KB team to refine the classification systems.

6. We are developing a chatbot-like search capability. Do you prefer the classic filter-based search or the chatbot search? Or the possibility of choosing either? Tell us how we can improve the search experience.

Classic Filter-Based Search:

The classic filter-based search allows users to narrow down their search results by applying various filters such as categories, tags, or specific criteria. This method is straightforward and efficient for users who know exactly what they are looking for and prefer a structured approach to finding information. It provides a clear and systematic way to explore the database, making it easy to compare different entries based on selected attributes. Advantages:

• Precision: Users can precisely narrow down results using specific filters.
• Structure: Provides a clear and organized way to browse through information.
• User Control: Users have full control over the filtering criteria and can adjust them as needed.

Chatbot Search:

A chatbot-like search capability offers a more interactive and conversational approach to finding information. Users can ask questions in natural language, and the chatbot can provide relevant answers, suggest related topics, and guide users through the knowledge base. This method is particularly useful for users who are not sure how to formulate their search queries or prefer a more guided and dynamic search experience. Advantages:

• User-Friendly: Offers a more intuitive and conversational way to search for information.
  • Guidance: Can help users refine their queries and suggest related information.
  • Accessibility: Makes it easier for users with varying levels of expertise to find relevant information.

Combination of Both:

Given the diverse needs of users, offering both classic filter-based search and chatbot search capabilities would be the ideal solution. This hybrid approach allows users to choose the method that best suits their preferences and specific needs at any given time.

• Expert Users: May prefer the precision and control of the filter-based search.
• Novice Users: May benefit from the guidance and ease of the chatbot search.

Suggestions:

• Advanced Search Features: For the filter-based search, include advanced search features such as Boolean operators, proximity searches, and wildcard searches to enhance search capabilities.
• Seamless Integration: Ensure that users can easily switch between the filter-based search and the chatbot search within the same interface. For example, the chatbot could suggest filters to apply based on the user's queries, and vice versa.
• Contextual Assistance: Implement contextual assistance within the chatbot to help users understand how to use filters effectively. The chatbot could provide tips and examples of how to refine searches using filters.
• Personalization: Allow users to save their search preferences and frequently used filters. The chatbot could learn from user interactions and offer personalized suggestions based on past queries and behaviors.
• Feedback Mechanism: Include a feedback mechanism for users to rate the effectiveness of search results and provide suggestions for improvement. This feedback can be used to continuously refine both the filter-based and chatbot search functionalities.
• Comprehensive Help Section: Provide a comprehensive help section that explains how to use both search methods, with tutorials, FAQs, and example queries. This can help users become more proficient in using the knowledge base.

By offering both classic filter-based search and chatbot search, and continuously improving these features based on user feedback and technological advancements, the ATIO KB can provide a versatile and user-friendly search experience that caters to a wide range of user needs and preferences.

7. We use Artificial Intelligence (AI) to enrich and automatically categorize the records: you will see an AI stamp at the end of descriptions that have been generated by AI: how good is the text generated? Is AI enriching the records in a meaningful way?

The AI-generated text in the ATIO KB has the potential to significantly enrich the records and provide meaningful insights to users. However, it is crucial to ensure that the AI-generated content is accurate, relevant, and of high quality. A robust human review process, continuous improvement of AI algorithms, and user feedback mechanisms are essential to achieving this goal. By leveraging AI effectively, the ATIO KB can become a comprehensive, dynamic, and user-friendly resource for agrifood systems innovations.

Benefits of using AI in ATIO KB:

• Efficiency: AI can significantly enhance the efficiency of data processing and content generation. By automating the categorization and initial description of records, AI can handle large volumes of data quickly, ensuring that the ATIO KB remains up-to-date and comprehensive.
• Comprehensiveness: AI can help identify patterns and connections within the data that might be overlooked by human curators. This can lead to more comprehensive and holistic records that capture the full spectrum of information relevant to each innovation.
• Scalability: The use of AI allows the ATIO KB to scale its operations effectively. As more data sources are integrated and more innovations are documented, AI can manage the increased workload without compromising on quality.
• Continuous Improvement: AI systems can learn and improve over time based on user interactions and feedback. This means that the quality of AI-generated content can continuously improve, becoming more accurate and insightful as the system evolves.
• Contextual Information: AI can enrich records with contextual information that enhances their usefulness. This includes linking related innovations, providing background information on the socio-economic context, and highlighting key adoption criteria.
• User-Centric Insights: AI can tailor the content to the needs of different user groups. For example, policy makers might need information on regulatory impacts, while farmers might be more interested in practical implementation tips. AI can generate content that addresses these diverse needs.
• Interactive Features: AI can support interactive features such as chatbots and dynamic filtering, making it easier for users to find relevant information and insights. This enhances the overall user experience and makes the knowledge base more accessible.

The quality of AI-generated text should be assessed based on:

• Accuracy and Relevance: The AI-generated text should be accurate, relevant, and context- specific. The information provided must align with the actual data and insights from the sources it draws upon. The AI should be capable of understanding the nuances of agrifood systems and the specific needs of the ATIO KB users.
• Clarity and Readability: The text generated by AI should be clear, concise, and easily understandable. It should avoid technical jargon unless necessary and should be written in a way that is accessible to a broad audience, including policy makers, researchers, and farmers.
• Depth and Insight: The AI-generated content should provide meaningful insights and not just surface-level information. It should capture the complexity and multifaceted nature of innovations, including technical specifications, use cases, and socio-economic impacts.
• Consistency: The AI should generate text that is consistent in style and tone with the rest of the content in the ATIO KB. This ensures a cohesive user experience and maintains the credibility of the knowledge base.
• Evaluation Process: To evaluate the quality of AI-generated text, it is essential to have a human review process in place. Experts in agrifood systems should review the AI-generated content to ensure its accuracy, relevance, and quality. Feedback from these reviews can be used to improve the AI algorithms.

Dear Sir

Dear sir thank you very much, giving me opportunity to submit the formats of FAO's Agri-Food System, Science, Technologies and Innovation outlooks (ATIO) knowledge base suggestion with including consultation. I'm not subject of agricultural expert but long time experience of working agricultural field, I have many working references, So i'm trying to make best suggestion. Thank you very much.

With best regards,

Dhanbahadur Magar

The program specially focus to rural farmers women, Not only Nepal entire of Asia, Africa, Europe, America, Latin America, Gulf Countries and land locked country, Plain to Mountainous Himalayas, Sea based countries, basically where are playing the dimension role by women in the world, in the agricultural sectors, priorities to innovative program for women first, second and third phase programs. Environment and women Friendly technologies. We can seems and feels women led program have been effective. Very less program has unsuccess along with they are distinguished double role not agriculture safe landing their families, value aid their labor costs, who are engaging about 14-17 an hours in 24 hours. 

Key point of crossing the challenges : Asian country have a most challenges to implement the program, There are major hinderance Patriarchal, and Caste discrimination system of size if can't minimize it will be remain long lasting time, ownerless using the theirs property, Asian women's have under controlling by Socially and culturally theirs decision cannot applied. Discrimination is still live, hindering them by caste systems, high and low castes is major problems. In this conditions Food supply system being a challenges. Specially Nepal, India, Bangladesh, Maldivs Bhutan remaining its baring the one society to other society, Using the food technologies, foodline sectors they also need to make empowerment policy. Women they not only earn income, but also keep their families welly. Need aware FAO guidelines farmers rights, like the UNDROP. Facility to in local market to marketization, guided to local government policy, priority to subsidies, grants and loan for engage agriculture sectors. Specially: invest to rural women by the government to the small holder farmers. 

If we want to mitigate the some key point should toward ahead, 1 is practical education (ATIO-KB) for women, women only can transfer to their family, they can play to implement as a communicator role in the society, can transfer women to women, children to children. It will be a knowledge base.

Please highlight organic farming as a separate topic in your catalog. At all stages of the plant life cycle (by species, such as cereals, legumes, oilseeds, forage, vegetables, fruits, wild plants, medicinal herbs, and others), starting with crop rotation, cover crops, and tillage methods, then from the moment of seed search and preparation, then the first shoots until harvest It is necessary to offer innovations tool to protect crop from pests, diseases, adverse weather conditions, plant nutrition, and biofertilizer. 

1.Given the description of the ATIO KB, how do you think it can help you and users like you? 

a) One would like to see information amongst farmers themselves, an example is the FAO’s Farmer Field School is a case that can be used wherein farmers use another farmers field as a learning platform to gain practical knowledge.  

b) To consolidate global knowledge on agricultural technologies, innovations, and best practices, supporting informed decision-making and the adoption of sustainable solutions across agrifood systems.

c) To foster collaboration, drive innovation, and promote the scaling of effective agrifood technologies and policies that address food security, sustainability, and resilience challenges.

d) Ensuring resources and tools are available and user-friendly for all stakeholders.

e) Accessibility: Ensuring resources and tools are available and user-friendly for all stakeholders.

f) Sustainability: Promoting practices that align with long-term environmental, economic, and social goals.

g) Effective Communication: Using language and formats that resonate with diverse of communities.

h) Local Relevance: Tailoring solutions to address the unique socio-economic dynamics and cultural specificities of various regions.

I) The goal would to create a globally accessible knowledge base of agri-food technologies and innovations. This resource will emphasize Asian's diverse ecosystems, traditional practices, and innovation potential, ensuring grassroots and indigenous knowledge contributions.

2.What do you make of concepts like policy innovation and social innovation? 

Prepare to game changer planning and an effectively drive crowdsourcing for grassroots innovations by creating an engaging platform where participants solve real-world challenges through interactive missions, earning points, rewards, and recognition for their contributions. Localized accessibility, team-based collaboration, and mentorship opportunities enhance inclusivity and innovation. Features like leaderboards, storytelling, and community voting foster continuous engagement and validation.

For Policymakers: Policymakers could leverage the KB to identify and compare technologies based on readiness, contextual appropriateness, scalability, and impact. For example, a policymaker may search for sustainable irrigation systems suitable for low-income regions. The KB could provide details on adoption rates, readiness levels, environmental impacts, and cost-effectiveness.

For Extension Agents: Extension agents could use the KB to identify grassroots innovations tailored to small-scale farmers’ needs. For instance, they might search for low-cost, farmer-led solutions for pest control, complete with implementation guides and field-tested results.

For Agripreneurs and Investors: Entrepreneurs and investors could use the KB to discover scalable innovations in food processing technologies, complete with data on market readiness and adoption trends.

For Researchers: Researchers could analyze correlations between inclusivity or co-design of solutions and their adoption levels, using KB-provided metadata on user demographics, participatory development processes, and implementation success stories.

Policy Innovation: A case study some specific program where policies incentivized smallholder adoption of solar-powered irrigation systems. The KB could provide policy details, adoption metrics, and lessons learned.

Social Innovation: Including policy and social innovations will enhance the KB’s relevance. Examples include: Such content should be presented in case-study format with key takeaways, implementation guidance, and links to further resources. These examples could serve as templates for replication or adaptation in other regions. Documentation of farmer cooperatives creating shared water harvesting systems. The KB could include the social structure, funding mechanisms, and resulting productivity improvements.

Infrastructure Limitations: Inadequate transportation, storage, and communication infrastructure hinders the efficient flow of goods and information.

Fragmented Value Chains: The dominance of small-scale producers who often lack access to markets and finance creates fragmented value chains.

3. How important is it to feature grassroots innovations? 

It is critical as these are the most challenged to communities in terms of resources. Under the Innovations section need to add: Use of paperless technologies for farmers [especially subsistence farmers/producers] to apply for support in their respective areas-this reduces their travel costs to areas and sites where such support is dispatched from.  

Consultation prior the development of innovations and awareness including illustration of benefits for such innovations. 

4. How do you think branded commercial products should be featured on the ATIO KB? 

Commercial products need to branded, should be featured as they are provided by the owners of such brands as this will promote data sharing and exchange amongst users. Consultation with owners is necessary to ensure protection of people’s information.  

Use of easy to buy mechanize for smallholder and subsistence producers’ alternative sources of energy and climate smart technologies that are basic and user friendly.

5.  Here are two of the main taxonomies used in the prototype: types of innovations and use cases.  Considering that there is no agreed standard for these categorizations, and that we are aligning them to those used in similar projects, are these “good enough” to start? 

The exclusion of some excellent lessons from some of the countries that failed to share their cases due to lack of access to this platform.  The need to link up with specific government departments, Agricultural knowledge center, learning and research institutions as well as feedback sessions. 

The proposed taxonomies for innovation types and use cases are sufficient to start but should be modular and subject to iterative refinement. Specific recommendations: Involve stakeholders in reviewing and updating taxonomies regularly.

Ensure taxonomies cover non-technical dimensions such as gender, inclusivity, and environmental sustainability.

6.  We are developing a chatbot-like search capability. Do you prefer the classic filter-based search or the chatbot search? 

Establish a control desk or enhance the existing to filter information whilst allowing new ideas to come through Search Capability.

Chatbot Search: Useful for handling complex queries, “Find grassroots innovations in Asian countries addressing post-harvest loss of crops.”

Filter-Based Search: Ideal for refining broader searches, with filters such as region, innovation stage, and use case.

Lesson learn : While launching the Agricultural base Project why failed ? make the concrete plans.

7.  We use Artificial Intelligence (AI) to enrich and automatically categorize the records: you will see an AI stamp at the end of descriptions that have been generated by AI: how good is the text generated? 

AI-is a useful tool though more research is needed to enhance is use by all not the selected few. 

AI-generated descriptions add value but should be transparently marked and editable. 

Clearly label AI-enriched records with an “AI stamp.”

Enable users to suggest edits, ensuring accuracy and contextual relevance.

Regularly audit AI-generated content to maintain quality.

AI-should be prior to innovation in natural base agricultural systems, better production, better nutrient, better environment and better life as strategy of framework for sustainable Agri-Food Systems for world to make good healthy world. 

AI-prior to Indigenous knowledge base Technologies, Seedlink, Culinary, producing, processing and branding for Agri-Food Systems.

JIRCAS Comments for ATIO KB e-consultation

We extend our sincere appreciation to the FAO team for their outstanding initiative and eagerly support the launch of ATIO KB to enable policymakers, investors, innovation users, and scientists with more appropriate solutions to identify and promote scalable technologies in light of comprehensive contextual information. 

We strongly believe that sharing the experience of the Japan International Research Center for Agricultural Sciences (JIRCAS) in the Green Asia project can be beneficial when designing ATIO KB.   

This project aims to accelerate the application of scalable agricultural technologies with special attention to the context specificity of the Asia-Monsoon region characterized by key features, esp. a hot and humid climate, rice paddy farming, and small-scale farmers, that form an environment conducive to highly intensive food production systems (https://www.jircas.go.jp/en/publication/gars-e/1). These distinguishing features should be considered when identifying and devising effective science, technology and innovation interventions to contribute to environmental sustainability without sacrificing productivity during climate emergencies and environmental crises. As a mechanism to achieve the aim of the project, the project conducts the collection, analysis, management, and dissemination of research results and outputs useful and applicable to the region, including those from Japan. The results of this project could serve as a reference for various stakeholders, including government officials, researchers, extension officers, producers, and the private sector. Given the collective significance of the Asia-Monsoon region, the success of the regional food systems transformation should have enormous global impacts to demonstrate the potential of synergies for climate change mitigation and sustainable agricultural production.

More specifically, the following experience of Green Asia project should contribute to designing ATIO KB:

• We have worked with research/academic partners to compile the technology catalogue (https://www.jircas.go.jp/en/greenasia/techcatalog) which has been introduced in the following websites.

• The UN Food Systems Coordination hub website at:

  https://www.unfoodsystemshub.org/latest-updates/news/en

• The ASEAN Secretariat website at:

  https://asean.org/asean-deliberates-regional-initiatives-on-sustainable-agriculture/

• Digital Villages Initiative in Asia and the Pacific at:

  https://www.fao.org/digital-villages-initiative/asia-pacific/resources/publications/en 

• In developing the catalogue, we have come up with classification of technologies, which help search and identify technologies of interest, by contribution areas (biomass utilization, chemical fertilizer reduction, pesticide reduction, disaster mitigation, GHG reduction, etc.), industries (agriculture, livestock, forestry, fishery and processing), commodity (agricultural machinery, agricultural residues, rice, oil palm, sugarcane, timber, etc.), institutions, and countries.
• In the last 3 years, we have chosen three technologies for pilot studies (AWD/BNI/Rice Blast Disease). Aside from compiling the reports elaborating the technologies, in conducting experiments with counterparts, we have been compiling data on contextual information to identify enabling vs. constraining factors to determine the feasibility of technologies in specific locations which can be used to fine-scale tailoring to guide scaling and dissemination. For some technologies, we have been collecting information on socio-economic constraints (costs and benefits of adoption by smallholders) while we have learned that understanding institutional conditions for scaling up (ex. national variety registration systems) is critical to guide dissemination strategies.  
• For other technologies in the technical catalog, we have been collaborating with regional partners to evaluate their feasibility and exchange information on their needs and adaptability through expert interviews and workshops.
• We receive advice and comments on the operation of the Green Asia project from the Scientific Advisory Board comprising globally distinguished scientists and leaders of regional agricultural institutions. 

JIRCAS also has compiled a kind of technology catalogue useful for those engaged in sustainable agricultural technologies in African smallholder contexts, with a dedicated HP (https://www.jircas.go.jp/en/africa-research)

We believe we can make some practical contributions to help design ATIO KB with our own experience. We are available for the expert consultation that is scheduled in February.

Information links

• JIRCAS HP: https://www.jircas.go.jp/en
• Green Asia Project HP: https://www.jircas.go.jp/en/greenasia
• Green Asia Background Report: https://www.jircas.go.jp/en/publication/gars-e/1
• Green Asia Technology Catalogue: https://www.jircas.go.jp/en/greenasia/techcatalog
• Green Asia Report Series: https://www.jircas.go.jp/en/greenasia/report
• Information Page on Agricultural Research in Africa: https://www.jircas.go.jp/en/africa-research

Warn regards, Miyuki Iiyama, on behalf of JIRCAS team

This is such a great inititative. However, the taxonomy/categorization has issues. One major issue is how it deals with established and emerging technologies for sustainable food production such as alternative proteins, including: approaches to plant-based meat production, cultured meat, precision fermentation, and biomass protein production (single cell proteins, like Quorn or Solein). Right now it has two items:

• production of alternative protein sources (e.g. insect farming, meat substitutes)
• cellular agriculture to develop lab-grown meat

This is great initiative.

The key challenge to delivering development interventions, particularly to rural communities of developing countries, is the fact that the population lives in a scattered geography, where the infrastructure, particularly the road network and other communication facility is poor, making service delivery very costly. Indeed, much of the cost of education is in bringing sufficient numbers of people together with an educator at set times and places.

Now that the group lending methodology (started by Grameen Bank of Bangladesh, early 1980s, and adopted widely in many developing countries), as well as the Self-Help Group movements have managed to bring large number of local population together, who meet regularly (monthly and weekly). But women’s improved access to credit will have to be accompanied by a number of additional measures, such as non-formal education, skill up-grading, new agricultural technology and social and political consciousness-raising to challenge the patriarchal social structure. 

Such regular community meetings provide convenient, cost effective platform to introducing such technology (often termed ‘’Credit with Education’’) to many people at the same time. In addition, participants not only learn on innovations from ‘’formal’’ sources (e.g agricultural extension) but also from fellow colleagues who already adopted such innovations. Indeed, the prospect of getting a loan can draw many people to a programme that offers them additional services.

But, if programmes aim at ensuring that rural women in patriarchal system use such technology, they also need to make sure that such women not only earn income, but also they ‘’control’’ such  income. Indeed, while accessing micro-credit have been highly advocated for advancing innovative agricultural technologies, so little attention has been paid to the issues of women’s ability to control income. Women’s ability to control income, e.g through facilitating tailored saving services is an important source of promoting women’s empowerment and bargaining power (see attached paper).

Regards

CONTRIBUTE TO SHAPING THE DESIGN OF THE AGRIFOOD SYSTEM TECHNOLOGIES & INNOVATIONS OUTLOOK (ATIO) KNOWLEDGE BASE (KB)

DISCUSSING A PROTOTYPE AND A DRAFT CONCEPT NOTE OF ATIO KNOWLEDGE BASE

Questions and proposed responses: Department of Agriculture, Land Reform and Rural Development (DALRRD) Chief Directorate: Food Security 

1. Given the description of the ATIO KB, how do you think it can help you and users like you? As a Policy developer and support provider to farmers/producers the ATIO KB will assist in providing realistic and appropriate technologies to the users, key is that the ATIO should be considerate of the farmer’s circumstance which will then enhance their adoption. Grassroots communities require hand holding and once an innovation is adopted success benefits these users, in particular at their local spheres.

   Describe one or more specific use cases that you wish the KB would address, - one would like to see information amongst farmers themselves, an example is the FAO’s Farmer Field School is a case that can be used wherein farmers use another farmers field as a learning platform to gain practical knowledge.    

2.           What do you make of concepts like policy innovation and social innovation? Policy innovation is a process wherein policy makers such as government craft policies that create conducive environments for farmers and policy users to thrive. Social innovation on the other hand is like a public call to support community growth and development without expecting profit. 

Can you think of examples? Examples include the supply of water harvesting equipment to communities which then enables the communities to harvest rainwater to augment water availability for their various needs. 

Is it useful for you to be able to find such content? Yes. 

In which form do you expect to find them? User friendly, pamphlets, graphics. How would you use them? Collaborate with Provincial Extension Officers to disseminate the information to users. 

3.           How important is it to feature grassroots innovations? It is critical as these are the most challenged communities in terms of resources.

Looking at some records of grassroots innovations in the prototype, what would you like to see in the descriptions that you don’t see? Under the Innovations section need to add: Use of paperless technologies for farmers [especially subsistence farmers/producers] to apply for support in their respective areas – this reduces their travel costs to areas and sites where such support is dispatched from.  

Which dimension should we capture? Support to subsistence producers as these are disadvantaged. 

What is most useful for grassroots use/application of innovations? Consultation prior the development of innovations and awareness including illustration of benefits for such innovations. 

4.           How do you think branded commercial products should be featured on the ATIO KB? Branded commercial products should be featured as they are provided by the owners of such brands as this will promote data sharing and exchange amongst users. Consultation with owners is necessary to ensure protection of people’s information.  

Data sources of technology-related information often feature individual models of technologies (for instance, different models of solar-powered irrigation pumps). Should the ATIO KB feature models? Yes as these will promote knowledge sharing. 

What is the “innovation” unit you expect to find? Use of easy to buy mechanisation for smallholder and subsistence producers’ alternative sources of energy and climate smart technologies that are basic and user friendly.

5.           Here are two of the main taxonomies used in the prototype: types of innovations and use cases.  Considering that there is no agreed standard for these categorizations, and that we are aligning them to those used in similar projects, are these “good enough” to start? As a start, yes. 

Which major problems do you see? The exclusion of some excellent lessons from some of the countries that failed to share their cases due to lack of access to this platform. 

Please suggest changes or volunteer to help us improve them in the next months. The need to link up with specific government departments, institutions of learning and research institutions as well as feedback sessions. Other taxonomies are here.

6.           We are developing a chatbot-like search capability. Do you prefer the classic filter-based search or the chatbot search? The filter -based search to avoid spams is ideal but should be easily accessible. Or the possibility of choosing either? 

Tell us how we can improve the search experience. Establish a control desk or enhance the existing to filter information whilst allowing new ideas to come through. 

7.           We use Artificial Intelligence (AI) to enrich and automatically categorize the records: you will see an AI stamp at the end of descriptions that have been generated by AI: how good is the text generated? Is AI enriching the records in a meaningful way? Response: AI is a useful tool though more research is needed to enhance is use by all not the selected few. 

END