Introduction to Bayesian Thinking

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Abstract

Stress caused by environmental factors evokes dynamic changes in plant phenotypes. In this study, we deciphered simultaneously the reaction of plant growth and chlorophyll fluorescence related parameters using a novel approach which combines existing imaging technologies (GROWSCREEN FLUORO). Three different abiotic stress situations were investigated demonstrating the benefit of this approach to distinguish between effects related to (1) growth, (2) chlorophyll-fluorescence, or (3) both of these aspects of the phenotype. In a drought stress experiment with more than 500 plants, poly(ADP-ribose) polymerase (PARP) deficient lines of Arabidopsis thaliana (L.) Heynh showed increased relative growth rates (RGR) compared with C24 wild-type plants. In chilling stress, growth of PARP and C24 lines decreased rapidly, followed by a decrease in Fv/Fm. Here, PARP-plants showed a more pronounced decrease of Fv/Fm than C24, which can be interpreted as a more efficient strategy for survival in mild chilling stress. Finally, the reaction of Nicotiana tabacum L. to altered spectral composition of the intercepted light was monitored as an example of a moderate stress situation that affects chlorophyll-fluorescence related, but not growth-related parameters. The examples investigated in this study show the capacity for improved plant phenotyping based on an automated and simultaneous evaluation of growth and photosynthesis at high throughput.

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Introduction to Bayesian Thinking. (2007). In Bayesian Computation with R (pp. 19–37). Springer New York. https://doi.org/10.1007/978-0-387-71385-4_2

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