Longitudinal analysis of a long-term conservation agriculture experiment in Malawi and lessons for future experimental design

TLDR: In this article, a longitudinal analysis of 10 years of data from the Chitedze Agriculture Research Station in Malawi was performed to understand the joint effects of variations between the seasons and particular contrasts among treatments on yield of maize.

Abstract: Resilient cropping systems are required to achieve food security in the presence of climate change, and so several long-term conservation agriculture (CA) trials have been established in southern Africa – one of them at the Chitedze Agriculture Research Station in Malawi in 2007. The present study focused on a longitudinal analysis of 10 years of data from the trial to better understand the joint effects of variations between the seasons and particular contrasts among treatments on yield of maize. Of further interest was the variability of treatment responses in time and space and the implications for design of future trials with adequate statistical power. The analysis shows treatment differences of the mean effect which vary according to cropping season. There was a strong treatment effect between rotational treatments and other treatments and a weak effect between intercropping and monocropping. There was no evidence for an overall advantage of systems where residues are retained (in combination with direct seeding or planting basins) over conventional management with respect to maize yield. A season effect was evident although the strong benefit of rotation in El Nino season was also reduced, highlighting the strong interaction between treatment and climatic conditions. The power analysis shows that treatment effects of practically significant magnitude may be unlikely to be detected with just four replicates, as at Chitedze, under either a simple randomised control trial or a factorial experiment. Given logistical and financial constraints, it is important to design trials with fewer treatments but more replicates to gain enough statistical power and to pay attention to the selection of treatments to given an informative outcome.