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Gravity is a powerful element in shaping plant development, with gravitropism, the oriented growth response of plant organs to the direction of gravity, leading to each plant’s characteristic form both above and below ground. Despite being conceptually simple to follow, monitoring a plant’s directional growth responses can become complex as variation arises from both internal developmental cues as well as effects of the environment. In this protocol, we discuss approaches to gravitropism assays, focusing on automated analyses of root responses. For Arabidopsis, we recommend a simple 90􏰁 rotation using seedlings that are 5–8 days old. If images are taken at regular intervals and the environmental metadata is recorded during both seedling development and gravitropic assay, these data can be used to reveal quantitative kinetic patterns at distinct stages of the assay. The use of software that analyzes root system parameters and stores this data in the RSML format opens up the possibility for a host of root parameters to be extracted to characterize growth of the primary root and a range of lateral root phenotypes. 

We use Bayesian methods to explore fitting the von Bertalanffy length model to tag-recapture data. We consider two popular parameterizations of the von Bertalanffy model. The first models the data relative to age at first capture; the second models in terms of length at first capture. Using data from a rainbow trout Oncorhynchus mykiss study we explore the relationship between the assumptions and resulting inference using posterior predictive checking, cross validation and a simulation study. We find that untestable hierarchical assumptions placed on the nuisance parameters in each model can influence the resulting inference about parameters of interest. Researchers should carefully consider these assumptions when modeling growth from tag-recapture data.