Farmer-centric On-farm Experimentation Enhanced by Digital Agronomy

Experimentation is a key process by which farmers all over the world have generated situated knowledge to continuously adapt their practices and evolve their farming systems. During the last century, small-plot experiments led by scientists have gained such prominence that other types of farming experimentation have been overlooked or discarded. In recent years, renewed interest in on-farm experimentation as a pragmatic process to connect different types of knowledge is opening promising pathways, notably through recent progress in digital agronomy that creates new opportunities for scientists and farmers to learn together, including in the context of climate change adaptation and the development of climate-smart practices that reduce greenhouse gas emissions, enhance resource use efficiency, and build cropping system resilience. This renewed momentum calls for critical reflection and synthesis from the scientific communities working across the diverse contexts of farmer-centric on-farm experimentation.

No consensus exists on standard practices to best enable farmer-centric on-farm experimentation, and the scientific literature on the subject remains limited, which itself perpetuates scepticism among scientists unfamiliar with farmer-led research and slows broader engagement. Yet these collaborations open multiple research directions, from problem framing to methods, and communities worldwide are exploring how to enable, implement and scale them across diverse contexts, including climate change adaptation and sustainable agroecosystem management. Research gaps persist across three interconnected disciplines: in agronomy, around consistent interpretation of results from diverse farming contexts; in data science, around analytical methods that bring greater certainty to unreplicated and farmer-designed trials; and in social science, around collaboration models and process organisation that make farmer-researcher partnerships more efficient and equitable. Recent advances offer promising entry points across all three: open digital platforms are lowering barriers to data sharing; new statistical approaches are improving trial interpretation; and refined frameworks are helping scientists trained in controlled experiments engage productively in farmer-led research. This Research Topic seeks contributions that build the evidence base, consolidate emerging knowledge and help establish shared foundations for farmer-centric on-farm experimentation at the interface of agronomy, data science, social science and climate-smart practice.

In this Research Topic, we welcome studies on the following subtopics, but not limited to:
• Conceptualisation and contribution of farmer-centric on-farm experimentation to agri-cultural transitions, including climate change adaptation and mitigation
• Critical accounts of case studies from inception to finalisation, addressing climate variability, extreme weather or resource use efficiency
• On-farm research network results and niche experiments including Living Labs, with attention to climate-smart practices and agroecosystem resilience
• Contextualisation methodology, including climatic and environmental drivers of agronomic performance
• Unreplicated farm trials interpretation and statistical analysis adapted to farmers' experimental designs, including approaches accounting for climate variability
• Surveys on farmers' experimental practices and actors' mental models toward farmer-centric innovation under climate change
• Collaboration models and value propositions for farmers, agronomists, industry, scientists and government, with relevance to SDGs 2, 13 and 15
• Political economy of on-farm experimentation funding, governance and climate policy linkages

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: On-farm experimentation, digital agronomy, farmer-centric, on-farm research, data science, co-learning

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.