ArticleFoods (Basel, Switzerland)2022
Quality Evaluation of Fair-Trade Cocoa Beans from Different Origins Using Portable Near-Infrared Spectroscopy (NIRS).
Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multivariate Quantitative Prediction of Soluble Solids Content, Moisture Content, and Fruit Firmness in 'Dinosaur Egg' Apricot Plum via Near-Infrared Spectroscopy with Cross-Parameter Feature Fusion and SHapley Additive exPlanations-Based Optimization.Foods (Basel, Switzerland) · 2025Article
- The Role of Near-Infrared Spectroscopy in Food Quality Assurance: A Review of the Past Two Decades.Foods (Basel, Switzerland) · 2024Review
- Chromatographic and spectroscopic methods for the detection of cocoa butter in cocoa and its derivatives: A review.Heliyon · 2024Review
- Fermentation and its effect on the physicochemical and sensory attributes of cocoa beans in the Colombian Amazon.PloS one · 2024Article
- Special Issue "Advanced Spectroscopy Techniques in Food Analysis: Qualitative and Quantitative Chemometric Approaches".Foods (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
7 authors.
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Abstract
Determining cocoa bean quality is crucial for many players in the international supply chain. However, actual methods rely on a cut test protocol, which is limited by its subjective nature, or on time-consuming, expensive and destructive wet-chemistry laboratory procedures. In this context, the application of near infrared (NIR) spectroscopy, particularly with the recent developments of portable NIR spectrometers, may represent a valuable solution for providing a cocoa beans' quality profile, in a rapid, non-destructive, and reliable way. Monitored parameters in this work were dry matter (DM), ash, shell, fat, protein, total polyphenols, fermentation index (FI), titratable acidity (TA) and pH. Different chemometric analyses were performed on the spectral data and calibration models were developed using modified partial least squares regression. Prediction equations were validated using a fivefold cross-validation and a comparison between the different prediction performances for the portable and benchtop NIR spectrometers was provided. The NIRS benchtop instrument provided better performance of quantification considering the whole than the portable device, showing excellent prediction capability in protein and DM quantification. On the other hand, the NIRS portable device, although showing lower but valuable performance of prediction, can represent an appealing alternative to benchtop instruments for food business operators, being applicable in the field.
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