Practical and Investigative Agricultural Skills
This domain tests the scientific method, sampling, measurement, records and safe practical work. Questions often ask you to design a fair trial, interpret data or identify why a result is unreliable.
Core rules
- State a testable hypothesis, then identify the independent variable (what you change), dependent variable (what you measure) and controlled variables (what you keep constant).
- Include a control treatment, replication and randomisation. One plot per treatment is not a valid experiment.
- Sample representatively: use random or zig-zag sampling, take enough samples, and composite soil from 0-20 cm depth for routine analysis.
- Calibrate instruments and use consistent units. Record raw data before calculating means.
- Present results in tables or graphs with labelled axes and units. Correlation does not prove causation.
- Keep livestock, crop and financial records; they support decisions and traceability.
- Follow safety rules for chemicals, machinery and animals.
Worked example
A trial compares 0, 30 and 60 kg N/ha on maize, with four replicated plots per rate, each 5 m x 4 m = 20 m2, arranged randomly. The independent variable is nitrogen rate; the dependent variable is grain yield; controlled variables include variety, planting date, spacing and water. One plot yields 12 kg grain at 12.5% moisture. Yield = 12 kg/20 m2 = 0.6 kg/m2 = 6 000 kg/ha = 6 t/ha. The reasoning converts plot yield to a hectare basis, then compares treatment means rather than single plots. Borders should be discarded to avoid edge effects.
Traps
- No replication or randomisation, so differences may be chance.
- Confounding two variables, such as fertilizer and watering.
- Measuring border plants or the wrong growth stage.
- Forgetting to convert plot yields to per hectare.
- Recording opinions instead of measured data.