Cacao

1. Brief Description

Cacao (Theobroma cacao L.) is the raw material of chocolate and one of the most valuable tropical commodities, grown across the equatorial belt; West Africa (Côte d’Ivoire, Ghana, Nigeria, Cameroon) accounts for roughly 70% of world production. Its commercial value depends on composition and post-harvest processing: fat content (cocoa butter), the flavour precursors developed during fermentation and drying, and low levels of defects, shell and foreign matter.

Quality is traditionally assessed with the cut test (visual colour of the cotyledons), sensory panels and laboratory methods: Soxhlet extraction for fat, HPLC for theobromine and caffeine, and spectrophotometric determination of the fermentation index (FI). These methods are accurate but slow, destructive and dependent on laboratory infrastructure that is rarely available where cocoa is produced.^1,3

2. The Problem

Traditional cocoa quality control faces several vulnerabilities across the supply chain:

• Subjective cut test: fermentation degree is judged visually on cut beans (slaty, violet or brown); results vary between operators, cannot be scaled to every lot, and say nothing about composition.^1,4
• Slow, destructive lab chemistry: fat, theobromine, caffeine and polyphenols require grinding, solvents and trained staff; the answers arrive long after the price and the process decision.^1,3
• Moisture and safety: beans must be dried to roughly 7-8% moisture; outside that range the risk of mould and ochratoxin A rises, yet moisture meters give only a partial picture of quality.²
• Adulteration and mislabelling: cocoa shell in powder, undeclared cocoa butter equivalents in chocolate, and origin or variety substitution all exploit the price gap between premium and commodity cocoa.^3,8
• Fermentation is the main driver of flavour and price: farmers and cooperatives rarely get fast, objective feedback while fermentation is still running, so they cannot adjust turning, duration or drying in time.^2,4
• Cost and access: reference analyses are expensive and centralised, making them impractical for routine screening at origin, at reception or on the production line.^5,6

3. How NIR Can Contribute at Each Step

The value chain runs from the farm to the finished chocolate. NIR can be applied at several key stages, replacing slow lab chemistry and visual grading with fast, non-destructive, objective measurements, provided the models are properly calibrated and validated.^1,5

Parameters that can be measured by NIR in Cacao

In a non-destructive, fast and objective way, NIR can quantify several of the traits that traditionally depended on lab chemistry, visual cut tests or sensory evaluation:

The chain, step by step

• 1. Cultivation. Smallholders and estates grow different varieties and hybrids; genetics and environment set the quality potential of the crop.
• 2. Harvest. Ripe pods are cut; ripeness at picking directly affects fermentation and the final flavour.
• 3. Pod opening and extraction. Beans with their pulp are removed from the pods and prepared for fermentation.
• 4. Fermentation. Beans ferment for about 5-7 days in boxes or heaps with periodic turning; the pulp breaks down and flavour precursors form. NIR can monitor fermentation index, pH and ammonia nitrogen while the process runs.²
• 5. Drying. Beans are sun-dried or mechanically dried to roughly 7-8% moisture; NIR controls the drying endpoint and the safety margin against mould.^2,4
• 6. Bagging and storage. Dried beans are bagged and stored; moisture stability and mould risk can be screened quickly at intake.
• 7. Grading and export. The cut test, defect counts and lot classification set the price; NIR offers an objective alternative at this step.^3,4
• 8. Import and storage. Importers receive and store the green beans; reception checks (moisture, fat, authenticity) can be made in minutes.
• 9. Roasting. The time-temperature profile develops aroma; NIR controls roast degree and batch-to-batch consistency.^5,6
• 10. Processing. Beans are ground into cocoa liquor, pressed into butter and cake, milled into powder, and manufactured into chocolate; NIR supports composition and adulteration QC.⁸
• 11. Retail and consumption. The consumer trusts origin, cocoa percentage and “pure” claims that were never independently verified along the chain.

4. Who Can Benefit from This Technology

• Farmers and cooperatives: benefit at the post-harvest and pre-sale grading step, with objective feedback on fermentation and drying before negotiating price, without depending on manual cut tests.⁴
• Fermentation centres / post-harvest operators: benefit at the fermentation monitoring step, tracking fermentation degree while the process runs and standardising it across batches.²
• Exporters: benefit at the lot classification and export step, quickly checking moisture and quality specifications before shipment.³
• Importers and traders: benefit at the goods receiving and storage step, verifying in minutes that shipments match declared moisture, fat and origin before redistribution.^3,4
• Chocolate manufacturers: benefit at the raw material and process QC step, controlling roasting and detecting cocoa shell, foreign fats and mislabelling.⁸
• Certifiers and auditors: benefit at the periodic audit step, gaining an objective, repeatable tool to validate origin, organic and fair-trade claims.⁴

5. References

1. Caporaso N, Whitworth MB, Fowler MS, Fisk ID. Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans. Food Chem. 2018;258:343-351. Available from: Food Chem 2018
2. Hue C, Gunata Z, et al. Near infrared spectroscopy as a new tool to determine cocoa fermentation levels through ammonia nitrogen quantification. Food Chem. 2014;148:240-245.
3. Álvarez C, et al. The use of near infrared spectroscopy to determine the fat, caffeine, theobromine and (−)-epicatechin contents in unfermented and sun-dried beans of Criollo cocoa. J Near Infrared Spectrosc. 2012;20:307-315.
4. Forte M, Currò S, Van de Walle D, et al. Quality evaluation of fair-trade cocoa beans from different origins using portable near-infrared spectroscopy (NIRS). Foods. 2023;12:4. Available from: Foods 2023
5. Teye E, Anyidoho E, Agbemafle R, Sam-Amoah LK, Elliott C. Cocoa bean and cocoa bean products quality evaluation by NIR spectroscopy and chemometrics: a review. Infrared Phys Technol. 2020;104:103127.
6. Sunoj S, Igathinathane C, Visvanathan R. Nondestructive determination of cocoa bean quality using FT-NIR spectroscopy. Comput Electron Agric. 2016;124:234-242.
7. Teye E, Huang X, Dai H, Chen Q. Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification. Spectrochim Acta A Mol Biomol Spectrosc. 2013;114:183-189.
8. Teye E, Huang X, Lei W, Dai H. Feasibility study on the use of Fourier transform near-infrared spectroscopy together with chemometrics to discriminate and quantify adulteration in cocoa beans. Food Res Int. 2014;55:288-293.