Designing of experiments and analysis of data in plant genetic resource management.

Abstract

In genetic resources environment, which is a field in the forefront of biological research, an essential activity is to test or evaluate the new germplasm/provenances/superior selections (new treatments, henceforth called test treatments) with the existing provenances or released varieties (checks, henceforth called control treatments). A problem in these evaluation studies is that the quantity of the genetic material collected from the exploration trips is very limited or cannot be made available since a part of this is to be deposited in genebank. The available quantity of seed is often not sufficient for replicated trials. Moreover, the number of new germplasm or provenances to be tested is very high (usually about 1000-2000 and sometimes upto 3000 accessions). A problem of interest is to design such experiments for making comparisons among the test treatments, among the control treatments and test treatments vs control treatments. The basic interest in these trials is to identify the promising germplasms. The promising germplasms identified are then subjected to more rigorous experimentation by allowing replications (generally two to three) of the test treatments (the promising germplasms or entries) along with the controls. In order to test the adaptability of these germplasms or entries in different environmental conditions, the trials are generally conducted over different environments (locations or years) to identify the promising lines. The purpose of the present note is to make an attempt to highlight some considerations in designing of experiments and analysis of experimental data. No claim is made about it being exhaustive.