In the past, plant phenotyping was primarily done by scoring traits by the naked eye. As this approach is time consuming, has a low resolution and is prone to human bias, plant phenotyping has evolved towards a new scientific discipline called phenomics which refers to the characterization of plant phenotypes via the acquisition and analysis of high-dimensional phenotypic data. Dimensionality points to diversity of phenotypic traits measured at different spatial- and temporal resolutions. Phenomics is especially interesting when investigating plant biostimulants as their impact on plant physiology and -morphology is often small and/or transient. Here, we’ll discuss some biostimulant case studies which highlight the need for phenomics,. PathoViewer is a plant phenotyping system, intended for high-resolution multispectral imaging in a highly controllable environment. The system is composed of 6Mp - 16 bit camera mounted on a Cartesian coordinate robot, and can be used to monitor the effect of a novel agrochemical on a large numbers of seedlings and small plants in their natural or in an extreme environment. Due to the highly automated sensor-to-plant principle, the spread of a disease or the effect of an agrochemical or stressor can be traced throughout the plant in time. Using a combination of RGB, Chlorophyll fluorescence, anthocyanin, NIR and GFP/RFP imaging, PathoViewer can visualize the impact of agrochemicals and (a)biotic stress in multiple ways. Moreover, researchers with expertise on image processing within the LAMP research can be consulted to compute scientifically relevant measures from these images, thus reaching beyond the mere visualization of phenomena.