Bridging the gap between models and users: A lightweight mobile interface for optimized farming decisions in interactive modeling sessions

Highlights

• Whole-farm modeling is hampered by the gap between models and users regarding accessibility, credibility and relevance

• We test if Interactive whole-farm optimization models can be effective for knowledge-bridging in a participatory context

• We use a lightweight model-user interface implemented with an open-source adaptable software solution

• Our study shows that interactive modeling tools are well-accepted by smallholder farmers and extension service officers

• Interactive modeling sessions can elicit tacit farmer knowledge and provide valuable insights for participatory research

Abstract

CONTEXT

Whole-farm mathematical programming (MP) models help to understand the complex implications of farm planning decisions taking the full agricultural system into account. Applying optimization models in direct interaction with farmers goes beyond leading to improved recommendations for mixed crop-livestock farm systems. The tacit farmer knowledge revealed in such interaction sessions can also provide valuable input for descriptive and predictive models of farmer behavior in scientific analyses of agricultural policy or technology adoption. To date, a conceptual and technical knowledge divide has prevented the widespread use of MP in interactive modeling with farmers in the field.

OBJECTIVE

This article revisits the rationale for interactive MP modeling and explores whether it can be upheld in practice. We evaluate whether a lightweight graphical interface that can be quickly adapted to practical applications of whole-farm planning can help bridge the gap between models and users.

METHODS

We present a user interface for whole-farm MP models implemented in the open-source statistical programming language R. We apply the tool in a participatory research process in Paraguay, analyzing the opportunities and barriers to adoption of new agroforestry options for smallholder farmers. Using in-depth interviews and participant feedback, we evaluate the tool's accessibility, credibility and relevance as well as its contribution to bridging knowledge gaps in the overall research process.

RESULTS AND CONCLUSIONS

In our explorative case study, interactive MP modeling provided essential insights into the local farming system and was highly accepted by smallholder farmers and extension workers. We observed a high interest in structured farm analysis, planning and education for smallholder agriculture. The lightweight user interface contributed to efficient and successful interaction between models and users.

SIGNIFICANCE

Interactive modeling helps to improve the application of whole-farm MP modeling in agricultural systems analysis. Case study examples and a quickly customizable interface can lower the barriers for using interactive MP modeling with farmers and other stakeholders. With the recent wave of digitalization in agriculture, the insights obtained here are also relevant for the development of digital farm management tools for systematic whole-farm planning.