Abstract
Experiments in greenhouses usually have to be conducted with very limited resources. This makes it particularly important to control the between plot variation by appropriate use of blocking. Many greenhouse experiments are naturally laid out in a pattern that makes a class of designs known as semi-Latin squares useful. Their properties have been studied recently by a number of authors and this work is reviewed. Often, the experimental treatments will have a factorial structure. An example of a 23 structure is used to show how factorial treatments can be assigned to treatment labels to ensure that the appropriate information is obtained from the experiment.
Keywords
Glasshouse experiments; Semi-Latin square design; Tomatoes; Trojan square design
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Ferris, Steve and Gilmour, Steven G.
(1998).
"BLOCKING FACTORIAL DESIGNS IN GREENHOUSE EXPERIMENTS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1283
BLOCKING FACTORIAL DESIGNS IN GREENHOUSE EXPERIMENTS
Experiments in greenhouses usually have to be conducted with very limited resources. This makes it particularly important to control the between plot variation by appropriate use of blocking. Many greenhouse experiments are naturally laid out in a pattern that makes a class of designs known as semi-Latin squares useful. Their properties have been studied recently by a number of authors and this work is reviewed. Often, the experimental treatments will have a factorial structure. An example of a 23 structure is used to show how factorial treatments can be assigned to treatment labels to ensure that the appropriate information is obtained from the experiment.
