Plants are crucial to our lives because they provide us with building materials, oxygen, and food. A season s crop yield can be significantly affected by local environmental factors. In particular, improving fundamental understanding of plant root interactions with their local soil environment, or rhizosphere, will help improve crop yield. Studying such interactions is challenging because roots are underground, making it difficult to observe interactions and to manipulate the local soil environment. The goal of this study was to develop an automated mini-channel platform to investigate how plant roots respond to changes in their environment using corn as a model plant. Considering the size of corn seedling roots, mini-channel devices were fabricated in soft lithography using master molds produced with a 3D printer and polydimethylsiloxane (PDMS). Our use of a 3D printer instead of photolithography allowed for a broader range of PDMS mold designs, such as including embedded rubber gaskets built into the mold. Then, corn seedlings were grown inside the transparent mini-channel devices, and they were found to consume an observable amount of nitrate over time. Image processing was employed to measure the contour length of the roots for quantitative characterization of root growth. Then, an automated platform was developed to measure the growth rate of the corn seedling roots and the consumed nitrate over time. The automated platform maintained the level of growth medium in the channel device, and was equipped with a digital camera to image the root growing in the channel, electrochemical sensors to measure changes in nitrate concentration in the channel, and sensors to measure temperature and humidity. Therefore, the platform could automatically measure root growth while simultaneously measuring root environment. The platform s adaptable design, simple fabrication, and low cost make it simple to replicate and use to study different plants and environmental stimuli.