Analysing treatment means in plant tissue culture research

Abstract

Many researchers set up an experiment, make measurements, do an analysis of variance, calculate the mean response for each treatment, and then try to decide if the" treatment means are significantly different and why. Much too frequently, Duncan's multiple range test is used to test differences among means. It is only one of a number of techniques that can be used to examine treatment means. Some researchers are unaware of the different techniques and that the interpretation of the results of an experiment is strongly influenced by the technique used i.e. using two different techniques might produce two different interpretations of the results. Selection of the appropriate technique to use for a particular experiment depends upon the nature of the treatments and the objectives of the research. This paper discusses four techniques (ranking treatment means, multiple comparison procedures, fitting response models, and using contrasts to make planned comparisons) that can be used to examine treatment means and presents examples of the use of each one for plant tissue culture research.

Effects of donor plant temperature, photoperiod, and age on anther culture response of Capsicum annuum L.

“…Effects due to interactions with block were included in the experimental error. Polynomial regression was used to study main effects of growth temperature and donor plant age (Mize & Young, 1988). Backtransformed least square means and their standard deviations are presented in figures.…”

Shoot organogenesis and plant regeneration in Pityopsis ruthii

“…The data was analyzed as a randomized complete block design in SAS version 9.2 using PROC MIXED with the RANK option because transformation failed to improve normality. Additionally, it has been noted that plant tissue culture experiments with the objective of determining which treatment has the highest or lowest mean or identifying a certain number of treatments with the highest or lowest means, the only analysis that needs to be done is to rank the means from highest to lowest and identify the appropriate treatments (Mize and Chun 1988).…”

Statistical considerations for in vitro research: I — Birth of an idea to collecting data

“…Although actual numbers will not be available, identify the sources of variation and estimate their degrees of freedom (df). Also, identify planned contrasts, mean separation tests, or other data analysis procedures at this time (Compton, 1994;Mize and Chun, 1988;Mize et al, 1999). Draw tables and graphs to compare the expected results to the objectives.…”