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An efficient class of tree network balanced designs for agroforestry experimentation.

Authors :
Birteeb, Peter T.
Varghese, Cini
Jaggi, Seema
Varghese, Eldho
Harun, Mohd
Source :
Communications in Statistics: Simulation & Computation. 2022, Vol. 51 Issue 12, p7169-7179. 11p.
Publication Year :
2022

Abstract

The use of an appropriate design is a very important aspect of agroforestry experimentation. Since different species of trees may interact spatially, plots in agroforestry could be connected through network of trees which would create non-directional adjacency effects on a plot. Hence, there is a need to take the "direct effect of trees" and "tree network effects" on the crop into account when designing an agroforestry experiment. Tree network effect refers to the influence a tree exerts on the surrounding plots as a result of adjacency of the plots. In this paper, a class of network designs incorporating effects of trees from adjacent plots has been obtained. The characterization properties of the designs have also been studied. The designs are found to be variance balanced for the estimation of direct as well as network effects of trees. They are also highly efficient designs, and hence, are recommended for agroforestry experimentation with multiple tree species and a single crop. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03610918
Volume :
51
Issue :
12
Database :
Academic Search Index
Journal :
Communications in Statistics: Simulation & Computation
Publication Type :
Academic Journal
Accession number :
160564763
Full Text :
https://doi.org/10.1080/03610918.2020.1825739