Coffee, Tea, Roasting & Dry Goods Processing worked example

Moisture Loss at 13% target moisture-loss percentage: a worked example in coffee, tea, roasting & dry goods processing

This scenario runs the moisture loss calculation on the strong side: 13% target moisture-loss percentage, with every other input held at its documented default. checking moisture reduction and its effect on yield or shelf-life targets

The inputs for this scenario

  • Moisture weight removed in roast/dry: 12 lb (unchanged)
  • Starting wet or green product weight: 100 lb (unchanged)
  • Target moisture-loss percentage: 13 % (raised for this scenario; the documented default is 11)

Working through the calculation

  • Applying the documented formula (Moisture Loss = moisture weight removed ÷ starting wet or green product weight × 100) to the inputs above produces each figure below.
  • At this operating point the engine returns 12 % for moisture loss, the number this scenario is built around.
  • At this operating point the engine returns 1 points for moisture loss gap to target.
  • At this operating point the engine returns 12 count for moisture weight removed.
  • At this operating point the engine returns 100 count for starting wet or green product weight.

How this compares with the baseline

  • Against the tool's baseline example, where target moisture-loss percentage sits at 11% and the headline result is 12 %, this scenario lands almost exactly on the baseline at 12 %.
  • Use it after roasting or drying when you have a verified before-and-after weight, or when dialing in a dryer to a moisture-content spec. Treat this as a target state: the delta against the baseline quantifies what the improvement is worth before you commit to chasing it.

Results at a glance

  • moisture loss: 12 % (headline result)
  • moisture loss gap to target: 1 points
  • moisture weight removed: 12 count
  • starting wet or green product weight: 100 count

Run it with your numbers

  • Every input above is editable in the live Moisture Loss calculator, which recalculates instantly and can be shared with the inputs intact.

Last reviewed 2026-05-12.