About this course

The subject includes lectures on soil analysis theory and how soil analyses are used as a tool for fertilization and liming planning, as well as for assessing pollution potential. In the laboratory, the following soil analyses are conducted: soil pre-treatment, bulk density determination, dry matter and loss-on-ignition determination, pH analysis, and analysis of easily soluble (plant-available) potassium, magnesium, calcium, phosphorus, and nitrogen. Exercises using DGT will also be conducted to determine the kinetics of phosphorus in soil from field trials with different phosphorus treatments

Learning outcome

Learning outcome:

Knowledge

Evaluate the best strategies for soil sampling and the best methods to be used for a given situation.

Evaluate uncertainties and quality of soil analysis results.

Evaluate soil analysis results as a tool for plant availability and as environmental potential.

Skills

Pre-treat and analyze soil samples for plant-available nutrients and assess the environmental consequences of reactive trace metals and phosphorus

General competense

Argue for the importance of soil analysis for best management fertilization and environmental quality.

  • Learning activities

    The course is given as 50% lectures and 50% laboratory work by guidance of teacher and engineers.

  • Teaching support

    The course teacher is available for questions and discussion in regular office hours as well as on email.

  • Syllabus

    Will be announced at Canvas.

  • Prerequisites

    JORD230 or similar

  • Assessment method

    Combined assessment:

    • Semester thesis (laboratory reports in groups) reports counts 40%.
    • Oral examination counts 60%.

    Both parts needs to be passed to pass the course.

    Grading scale: Passed / Not passed.



    Portfolio Karakterregel: Letter grades

  • About use of AI

    Oral exam: K1 - No use of AI

    Semester thesis: K3 - Full use of AI.

    The use of AI is permitted, but it must comply with the Guidelines for Use of Artificial Intelligens (AI) at NMBU.

    Mandatory activity: K3 - Full use of AI.

    The use of AI is permitted, but it must comply with the Guidelines for Use of Artificial Intelligens (AI) at NMBU.

    Descriptions of AI-category codes.

  • Examiner scheme

    The teacher evaluates laboratory reports (group reports). External senor and the teacher evaluate oral examination.

  • Mandatory activity

    Laboratory reports for all exercises have to be approved before the exam. Laboratory reports are group reports.

  • Notes

    Students who want to take the course must apply for admission in Studentweb no later than January 20th. After that, the places in the course will be distributed.

  • Teaching hours

    26 h of lectures and 26 h of laboratory work. Lectures and laboratory work are concentrated to 4 h per day and week.

  • Preferential right

    B-MILJØ, M-MILJØ, B-PV, M-PV

  • Reduction of credits

    5 credits overlap with JORD213.

  • Admission requirements

    Special requirements in Science