High-Throughput Plant Phenotyping Techniques in Controlled Environments

Advancements in plant phenotyping techniques have become critical to solving the complex relationships between genotypes and their corresponding phenotypes. Controlled environments provide researchers with an opportunity to manipulate various growth conditions, thus enabling a deeper understanding of plant responses. This chapter reviews the recent developments in high-throughput plant phenotyping techniques tailored for controlled environments. An inclusive discussion of the spectrum of imaging methods is presented, elucidating the capacity of these methods for efficient and accurate data acquisition and encompassing traits related to growth, morphology, physiology, and stress responses. Furthermore, the integration of automation, robotics, and data analytics-based deep learning (DL) has propelled the field forward, enabling the conducting of large-scale, reproducible experiments. Challenges such as data management, standardization, and the extraction of meaningful biological insights are addressed. By highlighting the advantages and limitations of these techniques, a comprehensive overview is provided for researchers aiming to employ high-throughput phenotyping in controlled environments. As plant phenotyping continues to significantly contribute to crop improvement, climate adaptation, and fundamental plant biology, the consolidation of innovative technologies with controlled environment experimentation is opening new avenues for accelerating scientific discoveries and enhancing agricultural sustainability.