The IDEMS Podcast

181 – Tricot Participatory Breeding Trials

In this episode, Lily Clements and David Stern discuss the “Tricot” method for participatory breeding trials. Short for “Triadic Comparisons of Technologies”, Tricot involves farmers testing three crop varieties and ranking them based on qualitative measures. They reflect on a recent workshop aimed at simplifying this complex analysis using custom R packages and the R-Instat software.

180 – Twenty Years of RMS for CRFS: On-Farm Agricultural Trials

Lucie and Roger continue their discussions of research methods for agriculture, this time focusing on on-farm trials. They consider the benefits and challenges of conducting research on farms versus research stations, emphasizing the importance of farmer involvement in the research process. They consider the innovative “Tricot” method, which tests multiple crop varieties with minimal control from researchers to increase real-world applicability.

179 – Challenging the Dead Internet Theory

In this episode, David and Santiago debate the 'Dead Internet' Theory, which claims that AI-generated content will dominate the internet, making it less reliable. David challenges this theory, emphasizing the need for digital literacy, responsible use of AI, and the complex nature of trust in institutions versus individuals. They also discuss the implications of misinformation and the importance of critical thinking in society.

178 – Twenty Years of RMS for CRFS: On-Station Agricultural Trials

In this episode, Lucie interviews Roger about essential aspects of agricultural statistical experiments. They discuss treatment, layout, and measurement, using an irrigation and maize variety case study. Roger emphasizes the importance of clear objectives and balancing statistical rigor with practical agricultural considerations.

177 – Mathematical Modelling vs Statistical Modelling

statistical and mathematical modeling. They explore how each field approaches modeling, and touch on hybrid models that incorporate both statistical and mathematical elements, and the significance of uncertainty in modeling predictions.