Data analysis in plant physiology: are we missing the reality?

Abstract

In plant physiology, data analysis is based on the comparison of mean values. In this perspective, variability around the mean value has no significance per se , but only for estimating statistical significance of the difference between two mean values. Another approach to variability is proposed here, derived from the difference between redundant and deterministic patterns of regulation in their capacity to buffer noise. From this point of view, analysis of variability enables the investigation of the level of redundancy of a regulation pattern, and even allows us to study its modifications. As an example, this method is used to investigate the effect of brassinosteroids (BSs) during vegetative growth in Sorghum bicolor . It is shown that, at physiological concentrations, BSs modulate the network of regulation without affecting the mean value. Thus, it is concluded that the physiological effect of BSs cannot be revealed by comparison of mean values. This example illustrates how a part of the reality (in this case, the most relevant one) is hidden by the classical methods of comparison between mean values. The proposed tools of analysis open new perspectives in understanding plant development and the nonlinear processes involved in its regulation. They also ask for a redefinition of fundamental concepts in physiology, such as growth regulator, optimality, stress and adaptation.

Identification of Differentially Expressed Genes in Brassinosteroid-Treated Brassica napus Seedlings

“…In addition, the rate of transport varies with different plant species. Yet another possibility is that BRs act mainly during critical periods in development when the target cells or organs are sensitive to this class of growth regulators (Amzallag 2001). Except for a few genes, the mechanism of induction for most BR-regulated genes has not been described (Vert and others 2005).…”

Functional groups of forest succession as dissipative structures: an applied study

“…Data were submitted to variance analysis procedures (ANOVA) and the mean values compared by Tukey's test (p < 0.01). Coefficients of variation (CV) were calculated for physiological parameters as an additional data-variation measure (Dutilleul & Potvin, 1995), indicating changes in system redundancy level (Amzallag, 2001).…”

“…Changes in gas exchange network connectance were evaluated according to Amzallag (2001). The coefficients of correlation (r) between gs x A, gs x E, gs x Ci, A x E, and A x Ci were considered as a measure of the strength of the relationship between two variables.…”

“…The coefficients of correlation (r) between gs x A, gs x E, gs x Ci, A x E, and A x Ci were considered as a measure of the strength of the relationship between two variables. As suggested by Amzallag (2001) The network global connectance (Cg) was calculated as the mean of the total connectance of paired parameters (Amzallag, 2001). The Cg value represents the level of global coordination of gas exchanges.…”

Mutation Patterns Due to Converging Mitochondrial Replication and Transcription Increase Lifespan, and Cause Growth Rate-Longevity Tradeoffs

“…The use of maximal lifespan for animals in captivity is a reasonable proxy for longevity, as well as maximal lifespan in the wild, as was shown at least in geckos (Werner et al, 1993). Before using correlation coefficients as variables in analyses, they were z transformed in order to linearize their scales (Amzallag, 2001) considering sample sizes (Seligmann et al, 2007). Analyses were done for various groups for which the relevant genomic and life history data were available for a sufficient number of species.…”