About this course

Plant phenotyping is the study and measurement of physical and functional characteristics (phenotype) of plants, which is determined by both genetics and the environment. It involves quantifying traits like growth rate, leaf and seed morphology, and physiological processes such as photosynthesis and water use. This field is crucial for improving crop yields, understanding plant responses to stress, and developing more resilient and productive varieties of crop plants. Modern high-throughput plant phenotyping uses digital technologies (sensors, cameras, robotics and data analytics) that objectively measure and analyse a wide variety of phenotypic markers quickly, objectively and non-destructively. This can be done across spatial, temporal and biological scales — from controlled environments to field settings, from cellular processes to whole ecosystems, and from short-term experimental cycles to long-term observations.

The course will cover the following topics:

  • Sensor Technology: Introduction to RGB, thermal, multispectral, hyperspectral, and LiDAR imaging.
  • Data Science & Bioinformatics: how to handle "big data," including image processing, machine learning/AI, and statistical modelling.
  • Field phenotyping using drones (UAVs), robots and sensors
  • Controlled environment phenotyping using multispectral 3D laser scanning (TraitFinder), handheld sensors and photosynthesis instruments
  • Seed morphological traits and germination phenotyping (Closed Flat FluorCam, Boxeed2.1, Qsorter Explorer)

Learning outcome

Knowledge

After completing the course students will be able to understand the principles and methods used to perform high-throughput plant phenotyping.

Skills

After the course the students will be able to design high-throughput plant phenotyping experiments, utilizing the equipment and pipelines for image data analyses available at partner institutions of the Norwegian Plant Phenotyping Infrastructure (PheNo) (https://pheno.no/)

General competence

Understand the possibilities of using different imaging techniques in plant research and in practical applications. The students will learn the basic principles of plant phenotyping and biological imaging.

  • Learning activities

    The course will last for 3 weeks.

    Week 1 and 2 (online): lectures and seminars, planning of experiments, introduction to data analysis.

    Week 3 (in- person): 2 days at NMBU, 2 days at UiO and 1 day for student presentations

  • Teaching support

    Canvas

  • Syllabus

    Will be informed about at course start

  • Prerequisites

    Plant molecular biology or plant biotechnology course, at least equivalent to the NMBU 200 level, or an MSc degree in a relevant field.

  • Assessment method

    Approved presentation and report (passed/failed).

    Portfolio Grading: Passed / Not Passed

  • About use of AI

    Laboratory report: K2 - it is allowed to use AI for writing assistance, including proofreading, but not to generate the content of the report. If AI is used, the report must include a brief statement on how AI was used and which AI program or platform was used. The student is responsible for the entire final report, both structure and content.

    Descriptions of AI-category codes.

  • Mandatory activity

    Mandatory work requirements:

    1. Attendance at all lectures and seminars

    2. Presence and active participation during the on-site training in week 2, including presentation.

    3. Writing the report

  • Teaching hours

    Lectures, demonstrations, practical training, and seminars: 60 h

    Reading course materials, self-study, writing report: 65 h

  • Admission requirements

    The course is intended for PhD students with basic knowledge in plant breeding, biology and environmental sciences or other relevant fields. PhD students with plant phenotyping related research in their PhD project have priority. MSc students can be admitted if space is available.

    This course is organized as part of the The Norwegian Plant Phenotyping Infrastructure (PheNo) in collaboration with the Norwegian Graduate School Photosyntech. Resources are covered by PheNo and NordPheno. Please see the web pages of PheNo (https://pheno.no/) and Photosyntech (https://photosyntech.no/courses-and-activities/ ) for more information about the course.