Within this study we applied closed-loop optimization using simulated experiments and assessed the effect of different surrogate models and data representations. In terms of sampling strategy, we conducted both exploitative search (the condition with the highest predicted yield is chosen for experimental evaluation) and Bayesian optimization (BO) based on expected improvement (EI) acquisition function (the condition with the highest expected improvement for yield was chosen for evaluation -incorporating the uncertainty of the prediction). For more detailed information on EI, BO and sampling strategies, refer to the SI and published literature.