Mistake 1: Trusting Every Number Blindly
Lab results can be wrong.
I always compare:
- trends
- plant conditions
- visual observations
One strange result doesn’t always mean the plant is failing.
Mistake 2: Poor Sample Handling
Improper:
- storage
- timing
- preservation
Can ruin tests before analysis even starts.
Mistake 3: Dirty Equipment
Cross-contamination happens easily.
Good cleaning habits matter.
Mistake 4: Rushing Procedures
Skipping steps creates unreliable results.
Slow, consistent lab work is usually more accurate.
Mistake 5: Ignoring Calibration
Meters drift over time.
Regular calibration prevents false readings.
Final Thought
The best operators don’t just run tests.
They understand:
- what the results mean
- whether the data makes sense
- how it connects to plant performance