Algorithm 1.

ABC rejection sampling for parameter inference.

(1)Given $N_{\hspace{0.17em}p}$ plant structures and $N_t(i)$ longitudinal observations for plant $i$, characterize the summary statistics $d_{ij}=\{B,\hspace{0.17em}L,\hspace{0.17em}\hat{l}\}$ from every plant $i$ and observation $j$ in the dataset. (2)Draw a trial set of parameters ${\theta }^{\ast }$ from the prior distribution $\pi (\theta )$. (3)Simulate $N_{\hspace{0.17em}p}$ instances of root growth, recording the state of structure $i$ at each of the $N_t(i)$ time points corresponding to an experimental observation. (4)Compute $\rho$ using equation (2.2) above, to give the separation between each recorded structure and its simulated counterpart. (5)If $\rho <ϵ$, where $ϵ$ is a given tolerance, accept ${\theta }^{\ast }$ as a sample from the posterior. (6)If a termination condition is not met, return to 2.