# Caffeine Content

> Rapid caffeine screening for black tea blends - lite model delivered, enabling blend certification and label compliance workflows.

- Canonical URL: https://spectrify.ai/research-pipeline/caffeine-content

- Sector: Sector 01 · Food & Agriculture
- Status: Lite Model Ready
- Tags: NIR, Tea, Caffeine, Compliance, PLS-R

Caffeine is one of the most regulated parameters in tea for export labelling, particularly for health-oriented and decaffeinated product lines. A rapid, non-destructive screening tool enables blenders to verify caffeine concentration at intake without waiting for HPLC laboratory results. We have delivered a lite model capable of stratifying samples into compliance bands, with a full quantitative model in the development queue.

## What We've Established

### Caffeine Absorption Features in NIR

Caffeine's imidazole and carbonyl functional groups produce distinguishable NIR absorption features, particularly in the combination band region (4,000–5,000 cm⁻¹). These features are partially overlapping with other nitrogenous compounds in tea but are resolvable with multivariate deconvolution.

### Lite Model Performance

The lite model was trained to classify samples into low, medium, and high caffeine bands corresponding to standard grade ranges for Sri Lankan black tea. Classification accuracy on the validation set was sufficient for blend-level screening and label compliance workflows, though not for precise quantification.

## Technical Approach

The lite model was trained using a reduced calibration dataset relative to the full quantitative models - sufficient for band classification but not continuous prediction. Reference values were obtained by UV spectrophotometry at 274 nm, a widely used rapid reference method for caffeine in tea. The full model will require HPLC reference values and a larger, more diverse calibration set.

## Where We Stand

The lite model is delivered and available for client use for blend screening purposes. The full quantitative model has been scoped but is pending dataset expansion. Priority is lower than the TF/TR fractionation models given existing client needs.

## Next Steps

- Expand calibration dataset with HPLC-referenced values for full quantitative model
- Assess feasibility of simultaneous caffeine and theanine prediction from a single scan
- Evaluate application to decaffeinated tea authentication

## Related Projects

- [Moisture Content - Green Tea](https://spectrify.ai/research-pipeline/moisture-content-green-tea) (Model Ready): Real-time MC measurement for green tea. Model trained on TRI-standard data and independently validated in December 2025.
- [Total Polyphenols (TPP)](https://spectrify.ai/research-pipeline/total-polyphenols-tpp) (Model Ready): Total polyphenol profiling for black tea - the leading proxy for antioxidant quality and a primary auction pricing signal.
- [Sugar in Tea](https://spectrify.ai/research-pipeline/sugar-in-tea) (Model Ready): Total sugar quantification across black tea grades - a key differentiator for premium blend specification and export documentation.

[Research Pipeline](https://spectrify.ai/research-pipeline)