Analysis in R-instat

Lily Clements, Roger Stern, Rachel Chase

Introduction

R-Instat is an accessible, user-friendly free software specifically designed for statistical analysis in agricultural science. In the context of tricot, R-Instat serves as a practical analytical tool that simplifies and streamlines the complex data workflows typical of tricot trials. This integration enhances data-driven, farmer-led insights in on-farm testing.

Download R-instat here

Get all documentation about R-instat here

Watch a 1000FARMS webinar about R-instat here

Purpose and key features

1. Accessibility: R‑Instat provides a user-friendly graphical interface to R’s powerful analytical capabilities, making statistical analysis approachable for practitioners and educators who may not be familiar with coding.

2. Tricot Suitability: Tricot experiments generate ranking data and farmer‑provided assessments across heterogeneous environments. R‑Instat enables efficient processing of such data, including ranking calculations and visual summaries.

3. Educational Integration: IDEMS International’s eCampus includes workshops, such as “KMD R‑Instat Workshop 2022” and “Tricot Workshop”, that embed R‑Instat training within broader curricula focused on participatory on‑farm trial analysis.

Benefits of using R-Instat in tricot analysis

1. User-Friendly Interface: Eliminates the barrier of coding, enabling agronomists, researchers, and educators to focus on interpretation rather than syntax.

2. Streamlined Workflow: From data cleaning to sub-setting, ranking and visualization, R-Instat centralizes tasks common in tricot analysis.

3. Capacity Building: Facilitates training through structured modules and workshops, democratizing access to participatory data analytics.

4. Scalability: Supports high-volume, decentralized data workflows typical of large-scale tricot deployments.

5. Advanced analysis features: For example R-Instat's climatic menu provides daily data, covering rainfall, temperature, and related data that can be used as environmental covariates in the analysis of trial data.

Step	Activity	Role of R-Instat
Design	Farmers implement tricot trials using a randomized incomplete‑block design (three options per block).	Not directly used here but foundational to downstream analysis.
Data Collection	Farmers collect rankings and trait observations from each plot.
Analysis	Use R-Instat to perform ranking analyses (e.g., worth estimates, Plackett-Luce models), visualize results, and generate summaries.	Empowers stakeholders to interpret varietal performance across environments.
Reporting	Generate accessible reports that integrate farmer feedback and statistical insights.	Supports the creation of visual and textual outputs for broader dissemination.