Discrimination between arabica and robusta green coffee varieties according to their chemical composition

doi:10.1016/S0039-9140(97)00409-8

Talanta

Volume 46, Issue 6, August 1998, Pages 1259-1264

https://doi.org/10.1016/S0039-9140(97)00409-8 Get rights and content

Abstract

Arabica and robusta green coffee varieties have been differentiated by using pattern recognition procedures. Chlorogenic acid, caffeine, trigonelline, aqueous extract, amino acids and polyphenols have been analysed in 41 samples of green coffee and used as chemical descriptors. Principal component and cluster analysis in addition with the K-nearest neighbours method have been applied.

Introduction

The two most important varieties of commercial coffee are Coffea arabica and Coffea canephora, usually known as arabica and robusta, respectively. Commercial coffee beverage is made from arabica or robusta beans or blends of them, the arabica being considered of better quality [1]and is therefore more expensive. Accordingly, it is interesting to have methods for differentiating between those two coffee varieties. Chemometric procedures applied to the data of chemical composition of the samples provide an interesting approach to the food quality control [2]. Within this realm several works on the discrimination of coffee varieties based on differences of their chemical composition have been published. Some of them use as descriptors sterols 3, 4, diterpenic alcohols [4], volatile components [5]and metals [6].

In the present paper the content of chlorogenic acid, caffeine, trigonelline, amino acids, polyphenols and aqueous extract have been determined in 41 samples of green coffee. By using these chemical data, principal component analysis (PCA), cluster analysis (CA) and the K-nearest neighbours (KNN) method have been applied to discriminate between arabica and robusta varieties.

Section snippets

Reagents and solutions

Tannic acid (Fluka), Folin–Ciocalteu reagent (Fluka), glycine (Merck), ninhydrine (Sigma), 2-metoxiethanol (methylcellosolve) (Fluka), caffeine (Merck), chlorogenic acid (Fluka), trigonelline (Sigma) and concentrated hydrochloric acid (Merck) were of analytical grade. Methanol (Romil) of HPLC quality was also used. Milli-Q water (Millipore) was used throughout.

Glycine (0.3 g l⁻¹), tannic acid (0.1 g l⁻¹) and ninhydrine (10 g l⁻¹) in methylcellosolve with 0.03% of ascorbic acid were used. HPLC

Results and discussion

Before the PR analysis, the selected variables were tested for normality. In all cases, they did not follow the normal distribution according to the χ² criterion and the Kolmogorov test [19]. Therefore, this address us to call on non-parametric PR procedures as the best choice.

A preliminary study based on PCA and CA has been applied for a better understanding of the discriminating efficacy of the selected descriptors and, while, visualising samples trends.

Conclusion

After applying PR methods, with the exception of three outliers, green coffee varieties (arabica and robusta) can be easily differentiated according to their contents in caffeine and total free amino acids.

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Discrimination between arabica and robusta green coffee varieties according to their chemical composition

Abstract

Introduction

Section snippets

Reagents and solutions

Results and discussion

Conclusion

Food Chemistry

J. Pharm. Sci.

Chromatographia

J. High Resolut. Chromatogr.

Biosci. Biotechnol. Biochem.

Mikrochim. Acta