Examples
Examples
Try the starting example
- Trees represented
- 100
- Fruit counts on sampled trees
- 80,100,120
- Masses of sampled fruit (g)
- 150,200,250
- Expected loss (%)
- 10
- Lower scenario loss (%)
- 5
- Upper scenario loss (%)
- 20
- Sample-mean projected gross fruit mass (kg)
- 2000
- Expected saleable mass (kg)
- 1800
- Scenario minimum saleable mass (kg)
- 1600
- Scenario maximum saleable mass (kg)
- 1900
- Mean sampled fruit count per tree
- 100
Try another scenario
- Trees represented
- 10
- Fruit counts on sampled trees
- 50,50
- Masses of sampled fruit (g)
- 100,100
- Expected loss (%)
- 0
- Lower scenario loss (%)
- 0
- Upper scenario loss (%)
- 10
- Sample-mean projected gross fruit mass (kg)
- 50
- Expected saleable mass (kg)
- 50
- Scenario minimum saleable mass (kg)
- 45
- Scenario maximum saleable mass (kg)
- 50
- Mean sampled fruit count per tree
- 50
Calculation method
Calculation method
Sample-mean projected gross fruit mass (kg)
Tree count × mean sampled fruit count × mean sampled fruit mass / 1000.
Expected saleable mass (kg)
Gross projection × (1 − expected loss/100).
Scenario minimum saleable mass (kg)
Gross projection × (1 − upper scenario loss/100).
Scenario maximum saleable mass (kg)
Gross projection × (1 − lower scenario loss/100).
Mean sampled fruit count per tree
Arithmetic mean of entered fruit counts.
Symbols and units
- a
- Trees represented
- b
- Fruit counts on sampled trees
- c
- Masses of sampled fruit (g)
- d
- Expected loss (%)
- e
- Lower scenario loss (%)
- f
- Upper scenario loss (%)
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- A sample-based arithmetic projection using representative tree counts and fruit masses. Scenario bounds are your selected loss assumptions, not statistical confidence intervals or a harvest guarantee.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.
Further reading
OpenStax: arithmetic and geometry ↗
Background reading; this does not imply endorsement or independent review of SumFizz.