Coffee - Green Bean Moisture
Green coffee bean moisture content is the single most important pre-roast quality checkpoint. Beans above 12.5% moisture are prone to mould, off-flavours, and post-harvest deterioration during transit - a major cause of lot rejection at destination ports. Beans below 10% become brittle, fracture unevenly during roasting, and produce inconsistent flavour profiles. Current measurement relies on capacitance-based moisture meters that are poorly calibrated for green coffee. NIR offers a path to a commodity-agnostic measurement approach.
Findings
What We've Established
Literature Precedent
Published NIR studies on green coffee bean moisture show strong calibration performance (R² > 0.95) using the same spectral regions effective for tea - confirming that the core measurement physics transfers. No commercial NIR system has been specifically validated for the Sri Lankan or East African export corridors, representing an addressable market gap.
Market Qualification
A structured questionnaire was distributed to specialty roasters and green coffee exporters in the target market. Early responses indicate strong interest in a rapid, reference-standard MC measurement tool, particularly for pre-shipment lot inspection.
Methodology
Technical Approach
Proposed approach mirrors the green tea MC methodology: build a PLS-R calibration model against ISO 6673 oven-drying reference values across a representative range of bean varieties and origins. Requires 200–400 calibration samples covering the 8–14% moisture range. Sample collection is the current bottleneck.
Status
Where We Stand
Questionnaire distributed to the target partner list. Awaiting confirmed interest and first commitments to supply calibration samples. No dataset collection has commenced.
Roadmap
Next Steps
Consolidate questionnaire responses and identify two to three anchor calibration partners
Design sample collection protocol covering major origin varieties (Ethiopia, Colombia, Sri Lanka)
Begin spectral acquisition once minimum sample commitment is confirmed
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Interested in This Research?
If you have relevant data, domain expertise, or a measurement problem in this area, we're open to research collaboration and data-sharing agreements.