NRC Designs—New Tools for Successful Agricultural Experiments

Abstract

In a nested row–column design (NRC), the experimental units in each of n blocks are grouped into n1 rows and n2 columns. Due to its structure, this experimental design allows full control of the experimental material and a relatively simple feedback loop within the “statistical triangle”. By applying such designs in agricultural experiments, we provide an insurance policy against future unexpected problems. Until now, the cost of this policy has been a complex statistical analysis of experimental data. This paper proposes a new “direct” approach to ANOVA based on the latest literature on the subject. The paper provides the theoretical foundations of this approach, indicates the possibility of applying it to factorial and near-factorial experiments, and supplements the theory with a familiar letter-based representation of all-pairwise comparisons, which has so far been lacking in the literature. The methodology is illustrated by the analysis of a field experiment carried out to improve the use of fungicides against late blight in tomato processing. The presented analytical tools are supplemented with code in R.