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Three centuries on the science of coffee authenticity control
Thiago Ferreira1, Leticia Galluzzi1, Tomas de Paulis2
1Núcleo de Pesquisa em Café Prof. Luiz Carlos Trugo (NUPECAFÉ), Laboratório de Química e Bioatividade de Alimentos, Instituto de Nutrição, Universidade Federal do Rio de Janeiro, Brazil.
This review traces the evolution of coffee authenticity testing over three centuries, highlighting advancements from early chemical methods to modern DNA analysis. DNA-based methods show promise for detecting coffee adulteration, despite challenges with roast intensity.
Area of Science:
- Food Science
- Analytical Chemistry
- Forensic Science
Background:
- Coffee adulteration has occurred since its popularization in the 18th century.
- Methods for detecting food fraud have evolved with technology and increasing demands.
- Authenticity control focuses on distinguishing coffee from other foods or its by-products.
Purpose of the Study:
- To review the historical evolution of scientific methods for coffee authenticity control.
- To analyze the development of techniques used to detect coffee adulteration over three centuries.
- To identify challenges and future prospects in ensuring coffee genuineness.
Main Methods:
- Review of historical and modern analytical techniques including microscopy, chromatography, spectroscopy, and DNA-based methods.
- Analysis of statistical tools associated with analytical methods.
- Examination of common adulterants like chicory, corn, barley, and coffee by-products.
Main Results:
- Early methods relied on chemical and physical analyses.
- 20th and 21st-century methods incorporate advanced techniques like DNA analysis.
- Challenges include matrix effects (roast degree, particle size) and lack of validated reference samples.
- DNA methods offer high specificity and low detection limits but are affected by roast intensity.
Conclusions:
- DNA-based methods are promising for coffee authenticity but require further validation and optimization for roasted samples.
- Microscopy is widely used but not always sufficiently efficient.
- Robust validation and testing on commercial samples are needed for most methods.
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