Plant Phenotyping Methods (P2M)

The course will provide a general overview on the application of phenotyping methods and tools, including data analysis techniques in all plant sectors of agricultural interest. In particular, it will cover aspects foreseen by the Plant Science Research Network (PSRN) which has formulated a ten-year strategic plan on the information infrastructure, big data challenges and training necessary to advance plant systems science. These goals empower students to bridge the gap between computational techniques and horticultural practices, fostering innovation in plant science.
In particular, students will have an overview of the approaches to:
Understand the basics of plant phenotyping: Define and describe the fundamental concepts of plant phenotyping and its importance in plant research and breeding.
Identify key plant traits: Recognize and categorize key plant traits relevant to phenotyping, such as growth, development, yield, and stress responses.
Utilize phenotyping tools and technologies: Demonstrate proficiency in using various phenotyping tools and technologies, including imaging systems, sensors, and software for data collection and analysis.
Design phenotyping experiments: Plan and execute phenotyping experiments, including selecting appropriate methods, setting up experimental designs, and collecting data.
Analyze phenotypic data: Analyze and interpret phenotypic data using statistical methods and software and draw meaningful conclusions from the results.
Apply phenotyping techniques in breeding programs: Apply phenotyping techniques to improve plant breeding programs, including selecting superior genotypes and identifying traits associated with desired plant performance.
Understand high-throughput phenotyping: Explore high-throughput phenotyping platforms and their applications in large-scale plant research and breeding.

Through theoretical lectures and practical sessions, students will be able to:
· Gain an understanding of various phenotyping techniques, tools, and technologies used in plant research and breeding programs.
· Set up an experiment and apply complex data analysis techniques in experimentation and research applied to tree species and agricultural species.
· Manage and organize large datasets generated from phenotyping experiments, ensuring data quality and integrity.
· Identify and address challenges encountered during phenotyping experiments and develop innovative solutions to improve phenotyping processes.