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Knowing the mechanisms that operate under water stress in commercial crops, particularly those that can affect productivity, such as phenolic or cell wall metabolism, is becoming increasingly important in a scenario of global climate change. However, our understanding of how to analyse statistically the relationships between these commonly used biochemical markers of water stress and growth in crops like pineapple, needs to be improved. In the present work, we have addressed the question of whether polynomial regression analysis can be used to describe the influence of selected plant metabolites (chlorophylls, carotenoids, phenolics and aldehydes) on shoot biomass, in response to a mannitol-induced water stress in temporary immersion bioreactors (TIBs). Polynomial regression analysis has been applied to investigate plant stress responses in many species but is very seldom used in in vitro screening studies. Here, the relationship between biochemical indicators (x; independent variable) and shoot growth (y; dependent variable) has been characterised, with y modelled as an n degree polynomial in x. This statistical approach accommodated for the non-linear (curvilinear) relationships between variables, and the results showed that shoot biomass was negatively, and significantly correlated with soluble phenolics, cell wall-linked phenolics and other aldehydes (characterised by “High” R values).

notulae botanicae horti agrobotanici cluj-napoca

Assessing the effects of in vitro imposed water stress on pineapple growth in relation to biochemical stress indicators using polynomial regression analysis