Seminar: The importance of long-term experiments in agricultural system research

Chloe Maclaren (Rothamsted Research) - The past, present and future of long-term agricultural experiments

View Chloe's talk here, on Youtube

Long-term experiments (LTEs) provide unique insights into the functioning and performance of agricultural systems over long timescales. The lifespan of LTEs often stretches far into the past (the world’s oldest LTE, Broadbalk at Rothamsted Research, began nearly 180 years ago) but the knowledge gained from LTEs is key to our future. Unlike shorter-term experiments, LTEs show which farming practices can truly be sustained over long timescales, and how resilient they are to temporal shocks and stresses such as climate change. This talk will give a tour of research highlights from LTEs to demonstrate their critical contributions to agricultural science, and will explore how we can learn even more from LTEs in future.

Janna Macholdt (Martin-Luther-University Halle-Wittenberg) - Yield variability in cereal production: LTE-analyses based on a system perspective "climate x soil x agronomic management"

The design of climate-resilient cereal cropping systems is important for global food security and stable cereal production over time. However, in the face of climate change and the associated increases in abiotic stresses, maintaining productivity while minimizing temporal yield variability of cereal cropping systems will become increasingly challenging. Consequently, it is essential to evaluate the yield variability of different cereal crops over the past decades under different soil conditions and agronomic management practices. Long-term experiments are a valuable resource for investigating this complex system of climate, soil and agronomic management, as they provide enough time to accurately estimate yield variability and its trend over years. In the presentation, we report our analyses results based on different long-term experiments across Europe (Germany, Denmark, England, Poland). For yield variability estimations of wheat, barley and rye, we analysed the data sets using individually adapted mixed model approaches with REML (restricted maximum likelihood) based and refined Shukla`s stability variance. We implemented statistical models that allowed yield variability to be determined independently of yield level in order to avoid any misinterpreting. In addition, we present findings based on yield risk analyses (Eskridge) and environmental adaptability estimations (Eberhart-Wilkinson regression). We identified diversified crop rotations, especially by introduction legumes and winter catch crops, moderate mineral fertilisation, sufficient liming and additional organic matter input (e.g. manure) as important agronomic management practices for reducing temporal yield variability of cereal crops. The results can help improve the climate resilience in cereal production by optimizing their agronomic management, which are associated with benefitting soil fertility over time.