Walter Mupangwa1*
Udhav Maharaj2,3
Jim Taylor2,3
Chris Dickens1
Dennis Choruma4,5Trevor Pike2
Tinashe L. Dirwai4,5Silvia Nyawira6
Matthias Samuel Geck7Isabella Braithwaite2- 1International Water Management Institute, Colombo, Sri Lanka
- 2GroundThruth, Pietermaritzburg, South Africa
- 3University of KwaZulu-Natal, Pietermaritzburg, South Africa
- 4International Water Management Institute, Harare, Zimbabwe
- 5Centre for Transformative Agriculture and Food Systems (CTAFS), University of KwaZulu-Natal, Pietermaritzburg, South Africa
- 6Alliance Biodiversity-International Center for Tropical Agriculture (CIAT), Nairobi, Kenya
- 7Center for International Forestry Research (CIFOR)-ICRAF, World Agroforestry Centre, Nairobi, Kenya
Introduction: Agroecology offers a promising approach to strengthen, and revolutionise, smallholder food and agricultural systems. Unfortunately, the assessment of agroecology impact at different scales and contexts is hindered by a lack of data and a lack of awareness of the potential of agroecology. Citizen science approaches are, however, demonstrating a knowledge revolution where learning is vested in the hands and tools of the farmers. The self-correcting mechanisms, that citizen science offers, enable the farmers to learn about and change their practices through the evidence they discover. In this way, the ability to change comes from within farmers’ experience and practices rather than farmers receiving information and knowledge from the outside. The purpose of this research work was to develop an accessible citizen science-based Agroecology Self-Assessment (ASA) tool framework.
Methods: This proposed ASA framework is purely conceptual, at this stage, and encompasses both physical and digital tools that can be used to assess agroecological practices and has the potential to address gaps related to agroecology performance assessments, data generation and knowledge-sharing. Furthermore, the proposed tool could lead to the development of a citizen science community of practice to empower smallholder farmers to collaborate and share both new and indigenous knowledge practices. Through fieldwork, the feasibility of using a mobile application to both collect data on various agroecological indicators, such as soil health, biodiversity, and water management, as well as socioeconomic factors related to agroecology was investigated.
Results and discussion: The findings from the fieldwork showed that there is interest by smallholder farmers and agricultural extension officers in the use of citizen-science tools to complement and enhance agroecological practices. The conceptual design and framework for the ASA tool was developed using the information from a desktop-based literature review and findings from discussions with smallholder farmers, researchers and agricultural extension officers. It is envisaged that the ASA tool, once in operation, will provide smallholder farmers with personalised feedback based on household and field assessments, foster knowledge sharing and self-correcting mechanisms. Such applied practices enable, and strengthen, evidence-based decision-making. The study concludes that the ASA tool is undoubtably needed and should include relevant practical assessment tools.
1 Introduction
Agroecology is a holistic approach to agriculture that integrates ecological principles with the social and economic facets of agriculture (HLPE, 2019; Wezel et al., 2020). Agroecology has evolved over many years in different parts of the world (Isaac et al., 2018; Wezel et al., 2020; Toledo and Argueta, 2024). The core tenets of agroecology encompass the promotion of socially equitable and resilient food systems, as well as the optimisation and strengthening of resource use for agricultural purposes (Leaky, 2014). The 13 principles of agroecology provide a framework for transitioning towards sustainable, fair, and equitable agricultural practices (Wezel et al., 2020). However, to operationalise the agroecological principles, a combination of scientific methodologies and participatory approaches are required. This will involve a multidisciplinary approach, drawing upon experience in ecology, sociology, economics, agriculture, engineering, soil science, and agronomy, among others (Leaky et al., 2021).
The Holistic Localised Performance Assessment (HOLPA) tool has been designed to evaluate how a farm performs according to the environmental, social, economic, and political dimensions of agroecology (Jones et al., 2024). To ensure its adaptability and relevance, HOLPA includes both globally applicable and locally specific metrices for evidence-based decision making. However, tools such as HOLPA, Tool for Agroecology Performance Evaluation (TAPE) (FAO, 2019) and Agroecology Criteria Tool (ACT) (Biovision and IPES-Food, 2020) have been designed as research tools and are not feasible for smallholder farmers to easily and frequently assess their own performance in implementing the 13 principles of agroecology.
In recognition of this limitation of HOLPA and other existing tools, this study proposes that agroecology can be advanced by harnessing the collective knowledge and power of smallholder farmers and rural communities and by engaging directly with those closest to the land. This can be achieved by incorporating citizen science into a mobile application that can be used for assessing the implementation of agroecological principles at individual smallholder farms. Citizen science can significantly enhance data collection and knowledge sharing among smallholder farmers (Graham and Taylor, 2018), helping bridge the gap between research and practice for more context-specific and effective agricultural solutions (Vohland et al., 2021). For example, by carefully designing an inclusive and accessible citizen science tool that aligns with the 13 agroecology principles, it will be possible to collect valuable insights into smallholder farmers’ practices, challenges, and aspirations. The data could then inform policy decisions, guide sustainable interventions, and build a robust evidence base for promoting agroecological transitions. Simple and robust citizen science tools, data collection software, remote sensing, and Geographic Information Systems (GIS), often in conjunction with mobile applications, offer opportunities to monitor soil health, pests and diseases, biodiversity, and resource efficiency (Vohland et al., 2021). Coupling these tools with participatory research within a citizen science framework will enable the collection of valuable data for informing decision-making and evaluating the impact of agroecological practices. Therefore, the development of a framework for a citizen science tool based on the 13-agroecology principles is proposed in this study. The proposed tool should have capabilities for smallholder farmers to assess the performance of agroecological approaches that they practice based on easy-to-answer questions and provide an agroecology score based on that assessment. By empowering smallholder farmers to frequently assess their agroecological practices, the Agroecology Self-Assessment (ASA) tool will contribute to building more resilient and sustainable food systems.
While tools such as HOLPA, TAPE, and ACT offer robust performance assessment frameworks, the Agroecology Self-Assessment (ASA) tool distinguishes itself by directly enabling farmer-led, real-time, low-tech self-assessments aligned with the 13 agroecology principles. This bottom-up, citizen science-based approach addresses limitations in scalability, agency, and feedback delivery inherent in other tools. This study aimed at (i) assessing the feasibility of developing an AE self-assessment tool through farmer and stakeholder engagement; and (ii) developing a conceptual framework for a citizen science tool to enable smallholder farmers to assess their agroecological performance to enable more efficient and sustainable transition to agroecology.
2 Background and literature review
The food system approach is at the core of agroecology transition, hence the 13 principles of agroecology (Table 1) ought to be applied to the different parts of the food system (Geels, 2002; Wezel et al., 2020; Ceddia et al., 2024). Agroecology transition requires measuring and documenting change, and the use of different approaches, including citizen science, to bring the change at different scales (Geels and Schot, 2007). Furthermore, during transition, changes are triggered (Wezel et al., 2020) and these may include social changes at household, community or national levels (Geels, 2002). Digital tools and applications can play an important role in facilitating changes in different parts of the food system during the transition process (Burns et al., 2022; Petraki et al., 2025). This section summarizes some of the important aspects in agroecology transition for sustainable food systems.
Table 1. The ten principles of agroecology and the different scales of implementation.
2.1 The need to assess and evaluate agroecology
Agrifood systems are complex and interconnected and they influence various aspects of human lives and planetary health (Jalonen et al., 2022). To understand and improve these systems, it is, therefore, crucial to measure and assess their performance. However, the diversity of agrifood systems and the multitude of assessment objectives make it challenging to develop a single, universally applicable agroecological assessment framework (Lamanna et al., 2024). According to Geck et al. (2023), traditional agroecological performance metrics often focus on productivity and profitability, neglecting other crucial aspects such as environmental and social impacts.
To address challenges related to measuring the performance of food systems, Lamanna et al. (2024) proposed a meta-framework to guide the development of holistic agrifood system assessments. This meta-framework outlines a step-by-step process for designing assessments that are tailored to specific needs and objectives and provides principles to assist in selecting appropriate metrics and methodologies, ensuring that the assessments are comprehensive, relevant, and actionable. Lamanna et al. (2024) state that by following this framework, researchers, policymakers, and practitioners can develop effective assessments that contribute to the sustainability and resilience of agrifood systems.
Geck et al. (2023) emphasised the importance of developing agroecology assessment approaches that are both globally comparable and locally relevant. The Holistic Localised Performance Assessment (HOLPA) tool is a comprehensive framework for assessing the multidimensional performance of agroecological systems at the household, field, farm, and landscape levels (Jones et al., 2024). The aim of HOLPA assessments is to capture a wide range of indicators, including economic, environmental, and social factors, and the HOLPA tool has been designed to be flexible and adaptable to different contexts, allowing for local customisation while maintaining global comparability. By incorporating a localisation process, HOLPA ensures that assessments are relevant to local needs and priorities. This approach enables a more nuanced understanding of agroecological practices and their impact on sustainable development (Jones et al., 2024).
2.2 Community-led research through citizen science
Citizen science has been applied in natural resources management and governance, social sciences, humanity studies, agriculture research and development, biodiversity assessments, and human-wild conflict studies (Vohland et al., 2021). Citizen science has been particularly valuable in studying global climate change, crop phenology, landscape ecology, and species distribution. Not only does citizen science contribute to scientific knowledge but it also fosters public engagement with science and environmental stewardship (Dickinson et al., 2012). For example, the One Million Voices (OMV) project is a citizen science initiative launched by the Transformative Partnership Platform on Agroecology (TPP). The OMV project aims to empower smallholder farmers, farm workers, and consumers to participate in agroecological transitions (van Dien and Fuchs, 2023). The OMV initiative identified key barriers and solutions to promote agroecology and is focused on the development of user-centred tools and platforms to facilitate data collection, knowledge and experience sharing, community engagement, and communication within and between communities.
Agroecology, as a holistic approach to agriculture, is gaining recognition as a promising solution to many challenges farmers face. A range of frameworks and tools to engage with and measure the performance of agroecology across various scales, from field to landscape level is of much value (Geck et al., 2023). van Dien and Fuchs (2023) performed a global review of existing citizen science projects that support agroecology and agroecological transitions, categorised into agricultural production, agroecosystems, markets, consumption, and diets. van Dien and Fuchs (2023) found that (a) many studies emphasise natural farming, (b) few projects focus on social justice or circular economy aspects, (c) some studies address multiple areas, but none holistically cover all three categories, and (d) there is a notable gap in published citizen science studies related to food systems and agroecology in the Global South, as well as in projects focusing on off-farm agroecological practices. There is, therefore, a need for a citizen-science based self-assessment tool that can be used to assess all levels of agroecology with a focus on the 13 principles. Citizen science offers an inclusive, low-cost, and scalable pathway to overcome barriers of expert-dependence, digital exclusion, and top-down monitoring in data-scarce agroecological systems of the Global South.
In agriculture, citizen science mobile Apps have been developed for pest and disease management (Christakakis et al., 2024), and Apps such as TeaBagIndex and SOILmentor for soil health management (Bodner and Weinrich, 2022). In hydrology, CrowdWater is a mobile citizen science App used for collecting water data by communities (Blanco-Ramirez et al., 2025). The data is used for hydrological modelling which informs decision making on water resources management. In biodiversity research, applications such as BirdNET and Merlin Bird ID are used globally for studying birds, helping researchers and communities in the management of different species (Nokelainen et al., 2024). The mobile App uses picture and audio systems to help the user to identify different bird species. In climate science, citizen science tools offer opportunities for communities to engage in weather condition assessments, and this informs their climate change adaptation strategies. The CitizenSensing App is used to generate climate information at local level, which helps in tailored targeting of climate change adaptation strategies under different agroecological conditions (Neset et al., 2021).
2.3 Overcoming the challenges associated with social change
Citizen science is a social innovation that can drive the socio-economic aspects of the 13 principles of agroecology (Fiore et al., 2024). Citizen science methodologies and Apps open opportunities for inclusivity as different social groups, including women and youths, can participate in rural development programs. Active participation by different social groups transforms lives of local citizens in households and the community. However, the development and design of the citizen science tools must consider a range of social dynamics. For much of recent history, causal approaches to attitude change and behaviour modification have been attempted. The assumption here, or conventional wisdom, is that such linear change processes do work. Large-scale awareness raising has, even when the awareness raising has been effective in changing attitudes, seldom lead to any tangible or enduring behavioural outcomes. Despite major effort and enormous cost such approaches are simply not working as intended (Taylor, 2010).
Conventional wisdom approaches, which often emphasise attitude change with the assumption that behavioural practices will follow have therefore not proved tenable (Beck, 1992, 1995, 1997; Kemmis and Mutton, 2012). Fien (2003) emphasises that ‘among the most successful [environmental education] programmes are those that avoid the belief that awareness leads to understanding, understanding leads to concern, and concern motivates the development of skills and action’. Causal, linear, top-down or centre-to-periphery approaches that assume behaviour change, following awareness raising, often facilitate a power-gradient from those who feel they know to those who they feel ought to know. This rational logic continues to assume that once informed, the others, often described as a target group, will change accordingly. As reported above, this rational change process fails to meet expectations and, at times, may even alienate the very people it is seeking to change (Taylor, 2010).
Often considered overly top-down, causal approaches are often replaced or complemented by participatory processes. At times the participation, by communities and other stakeholders, has proved more effective but these may run the risk of participation, for participation’s sake. Therefore, participatory approaches may be a step in the right direction, yet they still fail to enable the forms of social change that are required if meaningful transitioning towards more sustainable practices are to become possible.
Although the participatory processes have been valuable, more enabling responses such as citizen science and co-engaged action learning are proving more tenable alternatives (Taylor et al., 2022). A key focus of these approaches is “giving away the tools of science” or placing the tools of science in the hands of those who are part of the agricultural management processes. By engaging in finding out, participants are much more likely to implement the practices, than simply being subject to awareness raising, no matter how effective the awareness raising might be.
For challenges as complex as agroecology, the importance of context and the involvement and co-management of those participating is crucial. Many of these issues and problems require the integration of knowledge from the natural and social sciences, as well as economics, and there is rarely a single “silver bullet” solution. As Bhaskar et al. (2010) state, “exemplifying the triangular relationship of critical realism, interdisciplinarity and complex (open-systemic) phenomena” is needed for the investigation of such challenging problems as assessing agroecology at the farm, field and landscape levels.
Citizen science and co-engaged action learning (Pocock et al., 2014) are, however, showing the way to more inclusive, enabling and effective social change processes. This work deepens the understanding of agroecology issues in a practical and applied manner and enables actions for more sustainable practices (Graham and Taylor, 2018). With these approaches, the democratisation of science engages people who often become proud and eager participants in building understanding and working for more sustainable practices rather than being the passive recipients of knowledge from others. It is envisaged that the proposed ASA tool will provide a platform for inclusivity and transformation as diverse social groups actively participate in evaluating the performance of agroecology under different contexts.
2.4 The use of digital tools in agriculture
Digital tools play an important role in agricultural research and extension (Steinke et al., 2022). These tools link up farmers with researcher, extension agents and other stakeholders, and the tools are suitable for use in remote rural farming communities in the Global South. For example, tools such as FarmerChat supported by Digital Green (https://www.digitalgreen.org), help smallholder farmers get expert advice and implement locally adapted climate smart agricultural practices. This can be pivotal for driving the transition to agroecology under the different contexts in the Global South. Furthermore, digital tools facilitate data collection and sharing from heterogenous smallholder farmers, which helps in designing and targeting context specific solutions in agrifood systems.
Agroecological transitions are increasingly recognised as a crucial strategy to address global challenges such climate change and food insecurity. Digital tools can play a significant role in scaling up these transitions by providing technical support, platforms for performance assessments, and knowledge sharing (Burns et al., 2022). Digital tools could provide the means for a quick and efficient assessment of agroecology and provide a platform for collaboration and the co-creation of knowledge. Although the digitisation of food systems offers opportunities for sustainability and resilience, it also poses risks of marginalisation of smallholder farmers, particularly in low- and middle-income countries. The top-down and corporate-driven nature of many digital tools can undermine the principles of agroecology, which prioritise farmer autonomy and local knowledge (Shelton et al., 2022). To address these challenges, it is crucial to develop digital tools that are inclusive, accessible, and relevant to the needs of smallholder farmers.
Challenges such as digital literacy and access to technology hinder the adoption of digital tools by smallholder farmers, especially in low- and middle-income countries. To overcome these challenges, it is essential to involve farmers in the co-creation of digital tools and practices. The Socially Inclusive Digital Tools (ATDT) project of the CGIAR aims to empower farmers to co-create, adapt, and innovate climate-informed agroecological practices using digital resources and citizen science. By addressing the digital divide and promoting farmer-led innovation, the ATDT project seeks to accelerate the adoption of agroecology and contribute to more sustainable and resilient food systems (Burns et al., 2022).
Dittmer et al. (2022) stated that to address challenges such as limited digital literacy, affordability and lack of infrastructure, it is crucial to design and implement digital tools that are inclusive and accessible to diverse groups of smallholders. According to Dittmer et al. (2022), inclusive digital tools should include:
● Two-way communication: Tools that enable farmers to interact with experts and other farmers.
● Multiple channels of communication: Offering various communication channels (e.g., SMS, voice calls, apps) to cater to different preferences and literacy levels.
● Co-creation of practices: Involving farmers in the development of tools and practices.
● Highlight successes: Highlighting successful practices through visual examples.
● Data privacy and security: Protecting farmer data and ensuring ownership.
● User-friendly interfaces: Designing tools that are easy to use and understand.
● Local language support: Providing content in local languages.
● Offline functionality: Enabling access to tools and information without internet connectivity.
Subsequently, Dittmer et al. (2024) provided six principles for designing and implementing socially inclusive digital tools for smallholder farmers. These principles aim to empower farmers, ensure equitable access to technology, and promote the co-creation of farming practices. Furthermore, by prioritising farmer agency, data privacy, and ethical use of technology, these principles can help mitigate the risks associated with digitalisation and maximise the benefits for diverse and underrepresented groups of farmers (Dittmer et al., 2024). Therefore, by incorporating features and principles recommended by Dittmer et al. (2022) and Dittmer et al. (2024) and adhering to the PDD (2024) principles and social inclusion, digital tools can empower smallholder farmers, reduce inequalities, and contribute to sustainable agricultural development.
3 Materials and methods
3.1 Location of field work sites
The study was carried out in individually owned smallholder farms in rural Kenya and Zimbabwe (Appendix 1). In Kenya (Figure 1), the agroecological living landscapes are in Kiambu and Makueni counties (Nyawira et al., 2025). Both counties are dominated by mixed crop-livestock farming systems, carried out by smallholder farmers who farm on small pieces of land. The Murehwa District is located in the northeastern part of Zimbabwe (Figure 2), near the capital Harare. The area experiences high rainfall variability and occasional dry spells (Falconnier et al., 2024). In Murehwa, the main value chains are horticultural crops (tomatoes and onions), poultry (indigenous), livestock (cattle and goats), maize, groundnuts, and sweet potatoes.
Figure 1. Map of Kenya showing Makueni and Kiambu counties. Source: Nyawira et al. (2025).
Figure 2. Map of Zimbabwe showing Murehwa district. Source: Falconnier et al. (2024).
3.2 Materials
In this section, a number of tools, resources, support materials and methodologies are described. These are outlined as potential support tools for farmers practicing agroecology and assessing the performance of different aspects related to agroecology.
3.2.1 Clarity tube
Soil texture has implications for several agroecological functions, including water infiltration and retention, drainage, aeration, and the capacity of the soil to hold nutrients. For example, sandy soils are characterised by rapid drainage but limited water and nutrient holding capacity, while clay-rich soils retain water and nutrients effectively but can suffer from poor aeration. Therefore, understanding soil texture is crucial for interpreting other soil health indicators and for making informed decisions about soil management practices in an agroecological context.
Soil texture can be easily assessed by citizens using a clarity tube (Graham and Taylor, 2018). This simple method involves mixing a soil sample with water in a clear container/tube, shaking it thoroughly, and allowing the mixture to settle for an undisturbed period (Appendix 2). Over the undisturbed period, the soil particles will separate into distinct layers based on their size and weight: the largest particles, sand, will settle at the bottom, followed by silt, and the finest particles, clay, will form the top layer. If there is organic matter in the soil, it would float to the top of the tube or form a layer above the clay particles. The relative thickness of these layers provides a visual representation of the proportions of sand, silt, clay and organic matter in the soil, which in turn can be used to infer the soil’s textural classification. This is a useful method to quickly compare the soil texture in different fields or plots.
3.2.2 Soil moisture tests - knife and farmer’s test
To facilitate the assessment of soil health and inform critical farming decisions within the context of developing the ASA tool conceptual framework, simple, accessible methods for determining soil moisture levels were considered and utilised during the fieldwork. These included manual or “farmers’ tests” that require minimal equipment and leverage tactile evaluation. One such technique, demonstrated during fieldwork, involved the use of a clean pocket-knife inserted into the soil. The amount of soil residue on the blade upon removal of the knife from the soil was used as an indicator for the soil moisture level (Appendix 3), which has the potential to inform irrigation scheduling. Another simple method employed by farmers to estimate planting time is the soil ball test, which involves assessing soil texture and tilth by rolling the soil into a ball shape to determine moisture content, overall soil health, and determine if practices such as mulching were effective. These practical assessments, alongside other simple soil moisture tests, were demonstrated as potential citizen science tools to gauge their feasibility and farmers’ interest in using such indicators for decision-making on their farms.
3.2.3 MiniSASS
During the fieldwork phase and conceptual development of the ASA framework, the Stream Assessment Scoring System (miniSASS) was identified and utilised as a relevant citizen science training and demonstration tool (Appendix 4). MiniSASS is a biomonitoring approach popular in southern Africa (Graham and Taylor, 2018), notable for its low implementation cost and accessibility, enabling use by farmers with minimal formal training as well as scientists. The results from a miniSASS test are based on the presence of macro-invertebrate families in water bodies. The assessment provides a simple method to assess stream and river health. Modified miniSASS kits were selected and adapted for the fieldwork to complement discussions and demonstrate the use of citizen science tools for assessing water quality. Demonstrations conducted with postgraduate students in Kenya during the fieldwork highlighted the tool’s intuitive nature and its potential to engage users in data collection related to environmental parameters relevant to agroecology. The miniSASS technique is already supported by a smartphone App, including an AI Beta version, aligning with the proposed digital aspects of the ASA tool for data collection and analysis.
3.3 Methods
3.3.1 Transect walk
During the fieldwork phase of this study, transect walks involving researchers, smallholder farmers and agriculture extension officers were employed as a valuable tool for understanding the complexities of agroecological landscapes and social dynamics. By systematically traversing selected Agroecological Living Landscapes (ALLs) in Kenya and Zimbabwe, the research team was able to gather crucial data on agricultural and agronomic practices as well as ecosystem health. This method was considered vital to determine the feasibility of the proposed ASA tool. The discussion points for the fieldwork, while documented, were raised with five farmers in Murehwa and six farmers in Kenya during these walks in the context of organic conversations, rather than through a formal questionnaire format. The key purpose of the conversations was to ascertain if (a) there was a need for a self-assessment tool, (b) what features should the tool have, and (c) would the farmers be willing and able to use such a tool. The feedback from the conversations with the farmers were documented and used for the subsequent conceptual design of the ASA tool. Hence, the transect walks facilitated a comprehensive characterisation and understanding of the landscape structure and function and fostered trust between the researchers and stakeholders.
3.3.2 Informal stakeholder engagement
A key component of the methodology involved semi-structured conversations and group discussions conducted with relevant stakeholders, including farmers, agricultural extension officers, and other key stakeholders. The underlying framework of these informal stakeholder engagements was to adopt a combined bottom-up and opportunity-focused approach. The stakeholders were not interviewed formally, and informal discussions and transect walks were preferred over formal workshops and questionnaires. This approach was specifically chosen to avoid the likelihood of reducing farmer agency and to minimise the effect of deficit development. These qualitative methods aimed to gather in-depth information on farmers’ perceptions, challenges, and aspirations related to citizen science tools and agroecology. By directly engaging with the stakeholders, the goal was to co-create the framework for a user-centred ASA tool tailored to farmer-specific needs and contexts. The outcomes of the informal interactions were documented and compared to the citizen science principles and digital tool design principles (ECSA, 2015; HLPE, 2019; Jones et al., 2024; PDD, 2024) prior to the development of the conceptual ASA tool.
3.3.3 Conceptual tool development
Based on findings from the literature review related to the need for a self-assessment framework for agroecology (Burns et al., 2022; Geck et al., 2023) and consultations with farmers, researchers, and agricultural extension officers, a conceptual ASA tool was designed. This conceptual design included a mobile tool design, self-assessment questions, and citizen science tools. The conceptual citizen science tools and self-assessment platform were designed with the intent to be user-friendly and accessible to farmers with varying levels of literacy and digital literacy. A suite of physical tools that can be used by citizens for data collection (i.e. physical citizen science tools), such as modified clarity tubes and miniSASS kits, were selected and adapted during fieldwork to complement discussions and demonstrate their use in assessing soil and water quality. This was done to determine whether the farmers had the capacity to use and interest in the use of simple citizen science tools to collect agroecology data. It was recognised that specific tools would need to be designed for agroecology and that a toolbox of both soft and hard tools should be co-created with relevant stakeholders to support agroecological transitions and assessments. Based on the fieldwork that was conducted, the key needs of farmers and the 13 principles of agroecology were used to shortlist potential citizen science tools for agroecology. A key factor when shortlisting the tools was the ability to easily upload data or observations from the tools to a mobile App and to obtain a quantifiable score from the data. The conceptual tool architecture included considerations for a user-friendly interface, offline functionality, data privacy, multilingual support, and potential integration of AI and machine learning. Draft citizen science questions and associated tools linked to the 13 agroecology principles were also used to inform the conceptual design phase of the study.
3.3.4 Conceptualisation of ASA tool framework
The framework for the ASA tool was developed based on the literature review, the 13 agroecology principles, and fieldwork findings. The key principle of the framework was that it should include a conceptual scoring mechanism. This was a key principle, because it was envisaged that the ASA program would serve as a self-assessment tool where farmers assess their farming enterprise against the 13 agroecology principles, with the outcome being a score with detailed recommendations to improve their individual score. An additional consideration was for farmers to be able to view scores of other farmers and interact with them to promote peer-to-peer training and collaboration. The conceptual scoring mechanism to determine an agroecology score was developed based on the assumption that the farmer would upload information to a simple mobile App. The data collected by farmers through self-assessment questions and using citizen science tools would then be used to calculate an agroecology score for the plot or field being assessed. A potential approach for this involves indicator-based scoring, assigning a weight to each agroecology indicator and developing a scoring rubric, then calculating an overall score using a weighted average. Based on this score, the framework includes the option to provide tailored, human-centric feedback via the App, highlighting strengths, weaknesses, and opportunities for improvement, including specific recommendations.
3.3.5 Development of a conceptual scoring mechanism
In this section, further details about the scoring methodology are provided. A weight from 1 to 10 could be assigned to each of the 13 principles and for each principle, a farmer will be assessed and given a score from 1 to 100. These weighted scores can be combined into a single agroecology score using a weighted average approach and considering the importance of each principle. The following approach can be used:
1. Multiply the score by the weight: For each principle, multiply the farmer’s score by the weight assigned to that principle.
2. Sum the weighted scores: Add up all the products calculated in step 1.
3. Calculate the total weight: Add up all the weights assigned to the 13 principles.
4. Divide the sum of weighted scores by the total weight: Divide the sum calculated in step 2 by the total weight calculated in step 3.
This score would indicate the overall agroecological performance of the farmer, considering the importance of each principle. A higher score signifies better adherence to agroecological practices. However, the feedback provided to the farmer, based on the score, should be tailored to the score for each individual principle.
Additional factors that can be considered to finalise the scoring system are normalisation, sensitivity analyses and data quality measures. A sensitivity analysis must be performed to test how sensitive the overall score is to changes in individual weights assigned to each principle. To compare the farmers scores across different regions or time, the scores would need to be normalised (e.g., scaling them to a 0–1 range).
Furthermore, data quality protocols must be developed to ensure the accuracy and reliability of the assessments to obtain meaningful results. Regional differences and specific farm conditions should be considered when interpreting scores. It should also be recognised that agroecological practices are constantly evolving and regular reassessment and updates to the scoring system may be necessary. Farmers must be involved in the assessment process to increase ownership and promote continuous improvement. However, if multiple or different assessors (such as Agrochamps) are involved, robust training would be required to minimise variability in the results.
Based on the score, the tool can provide tailored feedback based on the farmer’s score and specific areas for improvement. For example, if the farmer has a low score in soil health, the tool can provide recommendations on improving soil organic matter, reducing soil erosion, and enhancing soil biodiversity. By combining all these elements, the self-assessment app can provide a comprehensive assessment of agroecological practices, empowering farmers to make informed decisions and improve their livelihoods without reducing their agency.
4 Results and discussion
4.1 Transect walks and stakeholder engagement
Through a combination of informal discussions, transect walks, and participatory workshops, the research team engaged with a diverse range of stakeholders, including smallholder farmers, agricultural extension officers, and researchers. By directly engaging with stakeholders, the research team aimed to co-create a user-centred ASA framework that is tailored to the specific needs and contexts of smallholder farmers in the target regions. Key topics discussed include the current agricultural practices, challenges and opportunities, the adoption of agroecological principles, the role of technology in agriculture, and the specific needs and preferences for a self-assessment tool. The insights gained from the fieldwork were crucial in shaping the user-centred ASA App framework design, ensuring its relevance, usability, and potential for positive impact. Based on the fieldwork, it was evident that the farmers and extensions officers in Zimbabwe and Kenya were interested and saw value in citizen science and tools that could be used to potentially assess and improve their agroecological practices. The smallholder farmers even enquired about where they could purchase the tools (clarity tube, tea bags, knife) that were used during the fieldwork. It was evident that to ensure the relevance and effectiveness of citizen science tools, it is important to involve smallholder farmers and other stakeholders in the co-design, co-create, and co-implementation processes. In the agricultural systems of sub-Saharan Africa, user-friendly citizen science tools for spatial and temporal data collection by smallholder farmers and extension agents are pivotal for the success of many research and development programs (Chambers, 1994; Snyder, 2017). In terms of capacity building, it is important to provide training and technical backstopping to smallholder farmers and extension workers on the use of citizen science tools and data analysis techniques. This will enhance the impact of innovations promoted through research and development programs for sustainable agrifood systems (van de Gevel and van Etten, 2020). It is also important to develop robust quality assurance protocols to ensure the accuracy and reliability of citizen-generated data (Resnik, 2019). Furthermore, effective mechanisms for sharing data and knowledge among smallholder farmers, researchers, policymakers, and practitioners is required. This can be achieved using various innovations such as Apps linked to relevant databases and dashboards. This will be beneficial to facilitate data collection and management, communication and knowledge sharing.
The field visits to smallholder farms in Murehwa district of Zimbabwe revealed a complex interplay of social, economic, and environmental factors influencing farming practices. The smallholder farmers, often working alongside family and community members, demonstrated a range of agroecological techniques, such as agroforestry, crop rotation, and organic farming. ‘‘We’re thrilled to showcase our farmers’ progress in utilizing environmentally friendly agroecological practices, such as manure application, conservation agriculture and locally sourced resources.’’ – a comment from an AGRITEX extension officer of ward 27 in Murehwa district of Zimbabwe. The challenges faced by these farmers, including market access, water scarcity, and soil degradation, underscore the need for innovative solutions and supportive policies. In Kenya, the discussions about the proposed ASA App with stakeholders highlighted several key points. Stakeholders expressed concerns regarding the language to be used, accessibility of the proposed ASA App, the cost and sourcing of citizen science tools, and the most effective method for sharing the proposed ASA tool. A USB drive was suggested as a potential solution to ensure easy accessibility. “With the idea of developing a mobile app and citizen science tools, I see the future of agroecology being bright. With this, the farmers can be able to access knowledge and tools they need to grow in a sustainable way. It can also solve most of the farmers challenges by enabling interaction of agroecology indicators, knowledge sharing, and market access can be guaranteed, I hope it can be user centric and accessible.” – a comment from a CSHEP officer in Kenya.
The stakeholders emphasised the importance of co-creation and knowledge sharing between researchers and farmers. The discussions also underscored the value of indigenous knowledge and the need to decolonise research practices. This was aligned with the App framework developers because by actively listening to smallholder farmers and incorporating their insights, researchers can develop more relevant and effective tools and interventions. Additionally, they highlighted the potential of technology to empower extension workers, government officials, Non-Governmental Organisation representatives, and researchers, to provide more effective support to farmers.
By working collaboratively with smallholder farmers, extension officers, and other stakeholders, it is possible to create a sustainable and prosperous future for ALLs globally. Total buy-in and active participation of smallholder farmers, extension agents and other stakeholders are critical for successful development of sustainable food systems (Triomphe and Bergamini, 2022; Bieszczad et al., 2023; Ongachi and Belinder, 2025). The findings from the fieldwork have been used to refine the preliminary ASA tool framework. The findings from the fieldwork provided a sense of hope for more sustainable living going forward. As people experiment, try out different methods and tools, work together and share (Davies et al., 2023), hope rises. A sense of hope is not to be undervalued and is certainly a powerful motivator for trying out new innovations, tools and landscape practices.
As access to healthy food becomes increasingly challenging, and inflation and unemployment rates rise, it is imperative to strengthen just transitions. These challenges are marked by uncertainty and climate variability and the human impact on the resource base further exacerbates these challenges. To address these issues, an exploratory table of just transitions for agroecology is presented below (Table 2), outlining proposed potential pathways towards a more sustainable future. The transitions will happen at different scales such as farm, landscape or territories (Bellon-Maurel et al. (2022), hence the proposed ASA tool is envisaged as one of those tools that will enable the process to be achievable under smallholder farming context of sub-Saharan Africa. The feedback platform on the proposed tool will empower smallholder farmers through increased knowledge of agroecology, as well as information and experience sharing with their peers. This will in turn open networking opportunities, further deepening their involvement in implementing sustainable farming practices on their farms.
Table 2. The relationship between just agroecological transitions and the proposed ASA tool (Source: Maharaj et al., 2024).
4.2 ASA tool conceptual framework development
An overview and conceptual design of the proposed ASA tool are summarized by Figures 3–6 in this section. Only the conceptual design of the program has been developed and the different components of the ASA tool. The design of the tool considers both data collection, self-assessments, and the portal to promote networked learning. The conceptual designs are provided to show the proposed functionalities of the App. However, further detailed design would be required prior to the in-field implementation of the ASA tool.
Figure 3. Conceptual tool welcome and self-assessment pages. (Source: Maharaj et al., 2024).
Figure 4. Conceptual self-assessment feedback and training portal pages on the tool. (Source: Maharaj et al., 2024).
Figure 5. Conceptual communication portal and general tool information. (Source: Maharaj et al., 2024).
Figure 6. Overview of application of the ASA tool. (Source: Maharaj et al., 2024).
The proposed design for the ASA tool has a simple, user-friendly landing page that should be accessible to farmers of all levels of literacy (Figure 3). The landing page provides an overview of the App’s features, including a self-assessment tool, training resources, and a community portal. The key features of the landing page are the general climatic information based on the user’s location, the user profile where the tool can be personalised and the stories of change. The experiences of smallholder farmers and how their work and livelihood choices are made are quite unique to each farming context. To better understand the social contexts, stories of change can offer a useful way of deepening the dialogue and understanding about what is occurring within the agroecology community (Alliance for Food Sovereignty in Africa (AFSA), 2023). Supporting the stories of change with ‘report and respond’ methodologies, where the smallholder farmer is able to describe and record his or her experiences, in the company of a researcher or community facilitator, can be really useful, not only for documenting experiences, and how things may be changing, but also as a useful research record of how the various agroecology projects are functioning and developing (AFSA, 2023). The second page of the tool (Figure 4) contains the links to training on the protocols used to perform the field survey as well as the form for the fieldwork survey. The fieldwork survey should only appear once the household survey is completed to ensure that the fieldwork survey is tailored to the smallholder farm where the assessment is being done.
The third page of the proposed tool should only appear once the self-assessment is completed and will display an agroecology score with simple visual representation (e.g., a robot scale) to indicate the overall performance, with colours like green for good, yellow for acceptable, and red for poor (Figure 4). Along with the score, tailored feedback should be provided based on the user’s score, highlighting areas of strength and areas where improvement is needed. Interactive feedback makes smallholder farmers eager to participate and build more understanding of the sustainable practices rather than being passive recipients of knowledge from extension agents and researchers. There should also be suggestions for relevant training resources, such as videos, documents, and links to external websites, to help users address identified gaps (based on the agroecology score).
The last two pages of the proposed tool are the communication and tool information pages (Figure 5). The communication portal should serve as a platform for smallholder farmers and relevant stakeholders to connect, communicate, and collaborate. The key features should include important information about the platform’s rules, guidelines, off-line mode and policies along with access to various tools and resources, such as: (i) A tool to help farmers access market information and connect with buyers and sellers; (ii) Online forums where farmers can discuss specific topics and share experiences; (iii) A space for real-time communication and collaboration; (iv) Interactive maps displaying the agroecology scores of registered users, helping to identify areas of strength and weakness; and (v) An AI powered chatbot trained specifically for agroecology for real-time communication.
The tool information page should include information related to the current version of the tool, the date when the tool was released or updated, the developer’s liability and disclaimers, and additional information or notes from the tool developer. Regular updating of the ASA tool will enhance its performance and functions, as well as ensuring security of the data generated by each smallholder farmer. All data collected using the ASA tool will be anonymised, stored securely, and used only with prior informed consent. Confidentiality and data owner consent are pillars of the 10 principles of citizen science (ECSA, 2015). Smallholder farmers will retain ownership of their data and be involved in interpreting and using the findings.
Prior to the field implementation, the ASA tool and information portal should be designed and built while considering the 13 principles of agroecology, the proposed citizen science products and tools, relevant rules and governance (country or region specific) and communities of practice. As shown in Figure 6, it is envisaged that the smallholder farmer would make use of the ASA tool to assess how successful and resilient their farming enterprise is by doing assessments based on the 13 agroecology principles. The survey questions will also include questions that will be answered in conjunction with a set of citizen science tools to easily quantify the performance of the smallholder farm. To ensure that the assessment is done timeously, it is proposed that the household survey to collect general information be done occasionally, and the field survey be done more frequently. The feedback from both surveys will be used to generate an agroecology score for the field or farm being assessed, and this will be used to provide tailored feedback to the smallholder farmer on how to improve their enterprise or specific practices. To further align the self-assessment ASA tool with the 13 agroecology principles and provide a comprehensive assessment of agroecological practices, biodiversity, soil health, water management, and socio-economic indicators and biomonitoring techniques will be incorporated into tool.
The results from the surveys and in-field assessments will be used to derive a single agroecology score. A weighted scoring system can be implemented, and each indicator can be assigned a specific weight based on its importance relative to the agroecological principles. The smallholder farmer’s responses to questions and the results of citizen science tests can be used to calculate a score for each indicator. These individual scores can then be combined to generate an overall agroecology score. Using a weighted scoring system (Wu and Yao, 2020), will ensure smallholder farmers make well informed and objective decisions on improving their management practices on the farm. However, the final scoring system and methodology would need to be refined once the final ASA tool is running.
Biodiversity Indicators:
● Bird diversity: Using bird checklists or provide links to bird audio-visual identification apps.
● Pollinator diversity: Monitor bee, butterfly, and other pollinator species around specific plants such as sunflower trees.
● Habitat diversity: Assessing the presence of different habitats, such as hedgerows, ponds, and forest patches around the farms.
Soil Health Indicators:
● Soil organic matter: Measuring soil organic matter content using simple field tests.
● Soil structure: Assessing soil structure by observing soil profiles and performing simple tests like the modified clarity tube settling test or ball and ribbon tests.
● Soil biodiversity: Using organism that live in the soil as bioindicators. This will have to be verified by determining the sensitivity of these organisms to different conditions. The farmer can then count insects, annelids, molluscs, etc. in the soil to get an indicator of soil health.
Water Management Indicators:
● Water use efficiency: Monitoring water use through techniques like soil moisture tests and simple evapotranspiration estimations.
● Water quality: Testing water samples for macroinvertebrates and turbidity using the miniSASS and clarity tube techniques (Graham and Taylor, 2018).
● Water conservation practices: Assessing the adoption of water-saving practices, such as drip irrigation and rainwater harvesting.
Social and Economic Indicators:
● Farmer well-being: Assessing farmers’ health, income, and social capital through qualitative questions.
● Fair trade and ethical practices: Evaluating compliance with fair trade standards and ethical labour practices.
● Community engagement: Assessing the level of community involvement in decision-making and resource management.
The development of a physical toolbox of citizen-science friendly tools specifically for agroecology will also have to be designed and developed. These tools should be low-cost and easy to build using easily available material similar to the water monitoring citizen science tools developed by Graham and Taylor (2018). Incentives for smallholder farmers to engage in agroecological self-assessment can be multifaceted. Beyond the intrinsic value of improving their farming practices, there are tangible benefits such as increased crop yields, improved product quality, and reduced input costs (AFSA, 2023). Moreover, agroecological practices can enhance soil health, water conservation, and biodiversity, leading to long-term sustainability (Wezel et al., 2020). From a social and intangible perspective, participation in self-assessments and citizen science can foster a sense of community, knowledge sharing, and empowerment. Additionally, certifications and labels associated with agroecological practices can lead to new markets and attract premium prices, and providing economic incentives (AFSA, 2023). Ultimately, agroecological self-assessment empowers smallholder farmers to make informed decisions, build resilience, and contribute to a more sustainable future.
The co-development of an agroecology self-assessment tool, incorporating citizen science tools, easy surveys, robust modelling results, and a learning and collaboration portal, presents a promising avenue for fostering the assessment of agroecological practices. Such a tool could empower communities to evaluate their own agroecological performance, identify areas for improvement, and share knowledge and experiences. However, to ensure its effectiveness, a comprehensive design process is essential. Past initiatives have highlighted the importance of a balanced top-down and bottom-up, community-driven approach to avoid the biases associated with solutions developed with a top-down approach (Taylor et al., 2022; Pattinson et al., 2023; Lamanna et al., 2024). Additionally, expanding the ASA tool’s geographic scope beyond the limited two countries where fieldwork have been conducted in this study would enhance its global impact. The development of user-friendly Apps and tools, along with opportunities for in-field training and support, would further strengthen the program’s utility and accessibility. By addressing these considerations and incorporating a robust design phase, the proposed agroecology self-assessment tool can become a valuable in promoting agroecology worldwide. However, challenges such as data quality, user engagement, and scalability need to be carefully considered to ensure the long-term success of the tool. Furthermore, continuous monitoring, evaluation, and adaptation of the App are essential.
4.3 Conceptual scoring system
It was important for the self-assessment module to be linked to a flexible scoring mechanism, offering both complex and simplified scoring options. This will cater to users of varying technical expertise and allow for tailored assessments based on local conditions and individual needs. The scoring logic should be designed to accurately reflect the user’s adherence to agroecological principles, considering factors such as soil health, biodiversity, and water management. The scoring system was developed based on the following premise:
● The system should automatically calculate an overall agroecology score based on the responses to self-assessment questions and data generated using the citizen science tools.
● Tailored feedback should be provided to the farmer based on the score.
The data collected by the farmers during the field survey, using the ASA tool, should be used to calculate an agroecology score for the plot being assessed. Scoring farmers based on their agroecological practices will provide a quantitative measure of their progress and adherence to sustainable principles. Comparing scores across different farms, will make it possible to identify high-performing plots, individuals and communities. This benchmarking can serve as a powerful motivator, inspiring others to adopt practices in alignment with the agroecology principles. Additionally, analysing the scores can help pinpoint areas where farmers may need additional support or training, allowing for targeted interventions and improved outcomes. Hence, a robust scoring system should be developed to assess farmers’ responses to the agroecology self-assessment questions and data collected using the citizen science tools. A potential approach to develop the scoring system is provided below.
1) Indicator-Based Scoring.
● Assign a weight to each agroecology indicator based on its importance relative to the agroecological principles.
● Develop a scoring rubric for each indicator, ranging from low to high.
● Calculate a score for each indicator based on the farmer’s responses and data.
2) Overall Agroecology Score.
● Calculate a weighted average of the scores for all indicators to determine the overall agroecology score.
● This score can be categorised into different levels (e.g., low, medium, high) to provide a clear assessment of the farm’s agroecological practices.
Once the overall score is calculated, the tool and relevant databases of information can be used to provide tailored, human-centric feedback based on the farmer’s performance relative to each indicator. This feedback should include strengths to ensure that farmer agency is not reduced, weaknesses to highlight areas that need to be improved and opportunities for improvement. The feedback should also highlight specific areas where the farmer is doing well and encourage them to continue these practices. However, the feedback must also help the farmer to identify areas where the farmer can improve and specific recommendations to achieve these improvements should also be provided to the farmer via the app. Lastly, the feedback should be structured to suggest potential opportunities for further improvement, such as adopting new technologies or practices and highlight potential risks, such as climate change or pest and disease outbreaks, and suggest strategies to mitigate these risks. Examples of human-centric feedback are provided below:
● High Soil Health Score: “Congratulations! Your soil health is excellent. Keep up the good work by continuing to use organic compost and cover crops. This will lead to increased yields”
● Low Biodiversity Score: “Your farm could benefit from increased biodiversity. Consider planting native trees and shrubs, creating wildlife habitats or greenbelts, and reducing pesticide use.”
● Moderate Water Management Score: “You’re making good progress in water management, but there is still room for improvement. Consider implementing water-saving technologies, such as drip irrigation, and monitoring water use more closely. This will save water and reduce your input costs”.
The feedback must consider the specific context of the farm, including location, climate, and socio-economic factors and should also incorporate local knowledge and traditional practices into the feedback. Furthermore, the feedback must be tailored to the cultural and linguistic background of the farmer (based on the user profile information). By providing tailored and actionable feedback, the app can empower farmers to make informed decisions and improve their agroecological practices. However, incentives and encouragement must be provided to the farmers to ensure that the app is used regularly to monitor their progress and adjust as needed.
5 Conclusion and recommendations
The development of a citizen science tool for assessing the implementation of agroecology principles was approved by smallholder farmers and agriculture extension agents in ALLs in Kenya and Zimbabwe. The smallholder farmers and extension agents emphasized the importance of developing a user-friendly, accessible and affordable tool that should be usable in remote rural farming communities where internet connectivity is poor. Following this engagement with smallholder farmers and extension agents, a conceptual framework of the Agroecology Self-Assessment (ASA) tool was developed.
This proposed citizen science tool represents a significant step towards the meaningful co-engagement of farmers in the sustainable assessment of agroecology. By leveraging the power of technology and community engagement, the ASA tool can empower farmers to make informed decisions, improve their livelihoods, and contribute to environmental conservation. Future research should explore ways to further refine and improve the design the ASA tool, expand its user base through the development and implementation of the program, and integrate it with other citizen science initiatives to create a comprehensive ecosystem for agroecological assessments. The ASA tool framework can complement the HOLPA, TAPE and other tools by enabling interim self-assessments, feeding into more comprehensive evaluations by the already existing tools. Integration with other citizen science initiatives could also facilitate participatory policy advocacy by aggregating grassroots agroecological data.
The following steps are recommended to facilitate the development and implementation of the ASA tool framework:
a. The design, development/construction, and evaluation of the ASA tool at key locations globally,
b. The locations should represent a range of agricultural and socio-economic conditions,
c. Piloting the citizen tools and ASA tool with a range of smallholder farmers, and
d. Comparative assessment of the ASA tool framework with existing tools or assessment frameworks.
To fully operationalise the ASA tool ecosystem i.e., the technology and user experience, there needs to be intentional top-down efforts to provide enabling environments to support digitisation in smallholder farming systems. Southern African countries like Zimbabwe, Zambia, and South Africa, among others, can leverage on the Universal Service Funds (USFs) to support the expansion of ICT infrastructure and services to remote areas or under-served populations.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.
Ethics statement
This sub-activity was part of the CGIAR Agroecology Initiative for the Kenya and Zimbabwe’s Agroecology Living Landscapes (ALLs) initiated in 2022 in the 2 countries. In Zimbabwe the ethical clearance was obtained through CIMMYT who led the agroecology activities in that country. For Kenya, clearance was secured through Alliance of Biodiversity and CIAT. The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because For this sub-activity conducted in 2024, consent was waivered because it was part of the bigger on-going AE initiative activities. The manuscript presents research on animals that do not require ethical approval for their study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.
Author contributions
WM: Conceptualization, Supervision, Writing – original draft. UM: Software, Methodology, Writing – original draft, Investigation, Conceptualization, Visualization, Formal Analysis, Data curation. JT: Validation, Formal Analysis, Methodology, Writing – original draft, Conceptualization, Visualization, Investigation. CD: Funding acquisition, Writing – review & editing, Project administration, Resources, Methodology, Conceptualization, Investigation, Supervision. DC: Investigation, Validation, Writing – review & editing. TP: Data curation, Conceptualization, Formal Analysis, Writing – original draft, Methodology, Software, Investigation, Visualization. TD: Investigation, Writing – review & editing. SN: Writing – review & editing, Supervision. MSG: Supervision, Writing – review & editing. IB: Investigation, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund.
Acknowledgments
This work was carried out with support from the CGIAR Initiative on Agroecology. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Appendix 1
Map of Africa showing location of Agroecology Living Landscapes used in the study.
Appendix 2
Difference between soils from a ploughed field (left) and a minimum till field with organic compost (right) using a clarity tube. (Source: Maharaj et al., 2024).
Appendix 3
A clean knife was inserted to the soil and then removed. The lack of soil residue on the blade of the knife indicates that the soil moisture levels are low and that the soil may require irrigation. (Source: Maharaj et al., 2024).
Appendix 4
GroundTruth research team performing a miniSASS test with the ICRAF researchers in a stream in Kenya. (Source: Maharaj et al., 2024).
Keywords: agroecology, citizen science, digital tool, self-assessment, smallholder farmer
Citation: Mupangwa W, Maharaj U, Taylor J, Dickens C, Choruma D, Pike T, Dirwai TL, Nyawira S, Geck MS and Braithwaite I (2025) Developing a conceptual framework for a citizen Science-based agroecology self-assessment tool. Front. Agron. 7:1646470. doi: 10.3389/fagro.2025.1646470
Received: 13 June 2025; Accepted: 25 November 2025; Revised: 02 August 2025;
Published: 18 December 2025.
Edited by:
Stéphane Cordeau, UMR Agroécologie, FranceReviewed by:
Konstantina Ntassiou, Western Macedonia University Of Applied Science, GreeceMatthew Davies, University of Cambridge, United Kingdom
Copyright © 2025 Mupangwa, Maharaj, Taylor, Dickens, Choruma, Pike, Dirwai, Nyawira, Geck and Braithwaite. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Walter Mupangwa, bXVwYW5nd2FAeWFob28uY29t; dy5tdXBhbmd3YUBjZ2lhci5vcmc=