Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Measuring quantitative plant phenotypes, or traits, is essential for understanding plant responses to environmental factors, including biotic and abiotic stresses. However, traditional methods of measuring plants can be time-consuming, inaccurate, and destructive, particularly when assessing traits such as biomass and height on an individual basis. Image-based analysis offers an opportunity to reduce labor, improve accuracy and precision, and enable repeated measurements of the same plant over multiple time points. While high-throughput phenotyping facilities provide a solution, they are often prohibitively expensive and limited in availability worldwide. A method is described for capturing plant images using low-cost single-board computers and digital cameras within a photo studio setup, accompanied by an image analysis pipeline based on the free and open-source package PlantCV. This method offers a fast and accurate protocol for image capture, labeling, and transfer, along with best practices for ensuring high-quality image acquisition. Through image analysis, more than 10 phenotypes were quantified for all images in the experiment simultaneously, including traits such as plant size, height, and color. These methods were used to characterize the response of the Zea mays (maize) inbred variety B73 to heat, drought, and combined heat and drought abiotic stress conditions.