Interactive tool for designing and assessing on-farm precision agriculture experiments

Overview

This solution is an interactive software application that helps farmers and agronomists design and assess on-farm experiments compatible with precision agriculture technologies. It addresses a key challenge in agricultural research: determining which experimental designs maximize information gain while minimizing yield losses and interference with farming operations. The tool uses a spatial simulation framework to model crop response patterns and evaluate experimental designs under realistic field conditions, helping users improve their knowledge of their fields and make better-informed agronomic decisions.

Technical specifications

The application consists of three integrated components:

• Spatial simulation engine: A random field-based generator that creates plausible crop response patterns conditioned by the characteristics of the fields under study and information about the input, practice, or crop being tested. This allows users to model the true underlying spatial structure of crop response, which is often unknown and variable across years.
• Experimental designs module: A designer that generates alternative experimental designs based on machinery dimensions and field characteristics, ensuring practical compatibility with farm operations.
• Design comparison and visualizations: Tools that enable quantitative comparisons of design performance for specific scenarios or across a range of scenarios, helping users select the best design for their conditions.

Prior validation studies demonstrated that experimental designs with small experimental units combined with analytical methods accounting for spatial auto-correlation outperform non-spatial methods or experiments with larger plots. This evidence informs the tool's design recommendations.

Technology readiness level

The underlying research has been validated through studies examining the effect of experimental designs and analytical methods on on-farm experiment results under multiple spatial structures of crop response. These studies confirmed that a significant portion of results is affected by the spatial structure of the underlying process generating yield response, and that analytical methods can produce biased conclusions depending on variability and spatial structure. The interactive tool itself is currently in development, with future validation planned to assess new experimental designs suitable for farmers' specific conditions through the integration of the spatial simulation engine, experimental designs module, and design comparison tools.