Discrimination between immature and mature green coffees by attenuated total reflectance and diffuse reflectance Fourier transform infrared spectroscopy

The objective of this work was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) in the characterization and discrimination between immature and mature or ripe coffee beans. Arabica coffee beans were submitted to FTIR analysis by reflectance readings employing attenuated total reflectance (ATR) and diffuse reflectance (DR) accessories. The obtained spectra were similar, but in general higher absorbance values were observed for nondefective beans in comparison to immature ones. Multivariate statistical analysis (principal component analysis, PCA, and agglomerative hierarchical clustering, AHC) was performed in order to verify the possibility of discrimination between immature and mature coffee samples. A clear separation between immature and mature coffees was observed based on AHC and PCA analyses of the normalized spectra obtained by employing both ATR and DR accessories. Linear discriminant analysis was employed for developing classification models, with recognition and prediction abilities of 100%. Such results showed that FTIR analysis presents potential for the development of a simple routine methodology for separation of immature and mature coffee beans. Practical Application: The ultimate goal of this research is to be able to propose improvements in the way immature coffee beans are separated from graded mature beans in coffee facilities (cooperatives and other coffee producer's associations). The results obtained herein point toward FTIR as a potential tool for the aimed improvements.     

Chemical characterisation of non-defective and defective green arabica and robusta coffees by electrospray ionization-mass spectrometry (ESI-MS)

The coffee roasted in Brazil is considered to be of low quality, due to the presence of defective coffee beans that depreciate the beverage quality. These beans, although being separated from the non-defective ones prior to roasting, are still commercialized in the coffee trading market. Thus, it was the aim of this work to verify the feasibility of employing ESI-MS to identify chemical characteristics that will allow the discrimination of Arabica and Robusta species and also of defective and non-defective coffees. Aqueous extracts of green (raw) defective and non-defective coffee beans were analyzed by direct infusion electrospray ionization mass spectrometry (ESI-MS) and this technique provided characteristic fingerprinting mass spectra that not only allowed for discrimination of species but also between defective and non-defective coffee beans. ESI-MS profiles in the positive mode (ESI(+)-MS) provided separation between defective and non-defective coffees within a given species, whereas ESI-MS profiles in the negative mode (ESI(−)-MS) provided separation between Arabica and Robusta coffees.     

Discrimination between defective and non-defective roasted coffees by diffuse reflectance infrared Fourier transform spectroscopy

The objective of this work was to evaluate the feasibility of employing Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) for discrimination between defective and non-defective coffees after roasting and grinding. Defective (black, immature and sour) and non-defective Arabica coffee beans were submitted to light, medium and dark roasts at 220, 235 and 250 °C. Principal Components Analysis of the DRIFTS spectra (normalized or not) and of the first derivatives of the spectra provided separation of the samples into four groups: non-defective, black, dark sour and light sour, with immature beans scattered among the sour samples. Classification models were developed based on Linear Discriminant Analysis and recognition and prediction abilities of these models ranged from 95 to 100%. Such results indicate that DRIFTS presents potential for the development of a fast and reliable analytical methodology for discrimination between defective and non-defective coffee after roasting and grinding.     

A comparative study of chemical attributes and levels of amines in defective green and roasted coffee beans

Differences in chemical attributes (proximate composition, water activity, sucrose, acidity and pH levels) and amine levels between defective and healthy coffee beans were studied. Before roasting, significant differences (p < 0.05) were observed for the ash contents of the coffee samples, with the highest values found for black beans. Moisture content was higher for non-defective beans in comparison to defective beans. Non-defective coffee beans had higher lipids contents than both sour and black beans. There were no significant differences (p > 0.05) for protein levels between defective and non-defective beans. After roasting, protein levels remained constant, there was a small decrease in ash contents and a slight increase in oil contents of black and sour beans. Both black and sour beans had higher acidity levels than immature and non-defective beans. Acidity levels decreased after roasting. Water activity levels also decreased with roasting, with slightly higher levels for defective beans in comparison to non-defective ones. Sucrose levels were much higher in non-defective beans, and the lowest values were in black beans, prior to roasting. After roasting, only traces of sucrose were found. Total amine levels were much lower for black beans, in comparison to the other coffee samples. Putrescine was the prevailing amine in all samples. Histamine was only detected in the defective coffee samples. Small amounts of serotonin, cadaverine and tryptamine were found in some of the samples. After roasting to a light degree, only traces of serotonin were detected and no amines were detected after roasting to medium and dark degrees.     

Evaluation of green coffee beans quality using near infrared spectroscopy: A quantitative approach

Characterisation of coffee quality based on bean quality assessment is associated with the relative amount of defective beans among non-defective beans. It is therefore important to develop a methodology capable of identifying the presence of defective beans that enables a fast assessment of coffee grade and that can become an analytical tool to standardise coffee quality. In this work, a methodology for quality assessment of green coffee based on near infrared spectroscopy (NIRS) is proposed. NIRS is a green chemistry, low cost, fast response technique without the need of sample processing. The applicability of NIRS was evaluated for Arabica and Robusta varieties from different geographical locations. Partial least squares regression was used to relate the NIR spectrum to the mass fraction of defective and non-defective beans. Relative errors around 5% show that NIRS can be a valuable analytical tool to be used by coffee roasters, enabling a simple and quantitative evaluation of green coffee quality in a fast way.     

Simultaneous Detection of Multiple Adulterants in Ground Roasted Coffee by ATR-FTIR Spectroscopy and Data Fusion

This paper proposes a novel screening method for the simultaneous detection of four adulterants (spent coffee grounds, roasted coffee husks, roasted corn, and roasted barley) in ground roasted coffee using partial least squares discriminant analysis (PLS-DA) with mid-infrared spectroscopy. Two different acquisition modes (attenuated total reflectance, ATR, and diffuse reflectance, DR) are compared. Two recent chemometric approaches, hierarchical models (HM) and data fusion (DF), were employed in order to improve model performance. First level models provided discrimination between unadulterated and adulterated coffee samples, whereas second level models were able to identify the presence of each specific adulterant. The use of DF decreased the percentage of misclassified samples for the first level models from 19.6/14.7% (DR) and 7.5/14.5% (ATR) down to 2.5/4.5% considering the training/test sets. The percentage of misclassified samples in the second level models went as low as 0% (DF—spent coffee, training set). The proposed method is simple, fast, reliable for detecting adulteration in coffee samples, and capable of identifying these adulterants, even when in complex mixtures containing other adulterants.     

Discrimination between defective and non-defective Brazilian coffee beans by their volatile profile

The coffee roasted in Brazil is considered to be of low quality, due to the presence of defective coffee beans that depreciate the beverage quality. In view of the fact that coffee flavour is directly related to the volatile compounds produced during roasting, the objective of the present study was to perform a comparative evaluation of the volatile fraction of defective (black, immature, sour) and healthy coffee beans, in order to find possible chemical markers for detection of defective coffee beans in roasted coffee. Volatiles extraction and concentration was performed by solid phase micro-extraction (SPME) of the roasted coffee headspace, using a triple phase (divinylbenzene/carboxen/polydimethylsiloxane) fiber. Analysis of the volatile profiles was performed by GC–MS. The results obtained showed that the proposed methodology was adequate for extraction, concentration and analysis of the coffees volatile profile. Several substances were identified as possible markers for differentiating black, sour and immature beans from healthy coffee beans. Statistical analysis of the data by principal components (PCA) demonstrated that the volatile profile enables the differentiation of healthy and defective coffees. The data were separated into two major groups, one represented by immature and black beans and the other by healthy and sour coffee beans. Such results indicated that black and sour beans can be associated to fermentation of immature and of healthy beans, respectively.     

Strontium and oxygen isotope fingerprinting of green coffee beans and its potential to proof authenticity of coffee

Multicollector inductively coupled plasma mass spectrometry (MC-ICP-MS) and Isotope Ratio Mass Spectrometry (IRMS) were applied to combine strontium and oxygen isotope abundance ratios of green coffees from 20 geographical origins in order to evaluate the suitability of these parameters as indicators of geographical origin, which is an important parameter of coffee quality. Results show that both isotopic systems of green coffee beans show a relation to environmental factors that influence processes occurring during the growth of the coffee bean. The final results allowed discrimination of local provenances investigated in this study by principal component analysis (PCA) and exhibit the potential to proof authenticity of world coffees. A good discrimination was obtained especially for coffee of South America region and coffees originating from islands.     

Approaches to Adulteration Detection in Instant Coffees using Infrared Spectroscopy and Chemometrics

Fourier transform infrared (FTIR) spectroscopy is examined as a rapid alternative to wet chemistry methods for the detection of adulteration of freeze-dried instant coffees. Spectra have been collected of pure coffees, and of samples adulterated with glucose, starch or chicory in the range 20–100 g kg⁻¹. Two different FTIR sampling methods have been employed: diffuse reflectance, and attenuated total reflectance. Three different statistical treatments of the spectra were carried out. Firstly, the spectra were compressed by principal component analysis and a linear discriminant analysis performed. With this approach, a 98% successful classification rate was achieved. Secondly, a simultaneous partial least square regression was carried out for the content of three added carbohydrates (xylose, glucose and fructose) in order to assess the potential of FTIR spectroscopy for determining the carbohydrate profile of instant coffee. Lastly, the discrimination of pure from adulterated coffee was performed using an artificial neural network (ANN). A perfect rate of assignment was obtained. The generalization ability of the ANN was tested on an independent validation data set; again, 100% correct classifications were achieved.     

基于顶空气相色谱-离子迁移谱技术的生咖啡豆快速鉴别方法

采用顶空气相色谱-离子迁移谱（headspace-gas chromatography-ion mobility spectrometry,HS-GC-IMS）技术对云南不同品种生咖啡豆的挥发性有机物（volatile organic compounds,VOCs）进行无损分析。根据保留指数和迁移时间对其挥发性成分进行二维定性,创建生咖啡豆VOCs的差异谱图,并对其VOCs数据进行主成分分析（principal component analysis,PCA）。结果表明,HS-GC-IMS可有效分离生咖啡豆挥发性成分,对样品VOCs的信息采集及分析可在20 min内完成,并鉴定出42 种挥发性物质,主要为醛类、酯类、醇类、酮类、吡嗪类、酸类及含硫化合物。采用PCA分析HS-GC-IMS图谱,可准确区分不同品种生咖啡豆。该方法具有快速、灵敏、无损的特点,为生咖啡豆的品种识别、产地追溯、品质控制等提供了一定参考依据和理论基础。     

The influence of particle size and concentration in transmission and diffuse reflectance spectroscopy of wood

FTIR spectra of the tropical hardwood Guibourtia sp. (Caesalpinia-ceae) have been recorded using the KBr pellet technique and diffuse reflection (DRIFT) in KBr powder. It was demonstrated by variation of the wood concentration in KBr and the particle size of the milled wood that the spectroscopic data of wood- mainly those of the intense carbohydrate band around 1100 cm^?1—are strongly influenced by these parameters. The KBr pellet technique gives reproducible results for concentrations between 0.1 and 0.5% with a particle size below 25 μm. The. DRIFT spectra of wood powders in KBr are very much influenced both by particle size and concentration. Wood spectra are also presented which were obtained by transmission spectroscopy and FTIR microscopy of 25 μm microtome cuts and by reflectance on solid wood surfaces. The influence of heterogeneous dispersion of wood in KBr and the roughness of wood surfaces on reflectance spectroscopy is discussed. A simple baseline correction is recommended to increase interlaboratory comparability of wood spectra.     

Potential use of Fourier transform infrared spectroscopy for differentiation of bovine and porcine gelatins

In order to classify unknown gelatin into their species of origin, a simple and rapid method for the qualitative determination was developed using Fourier transform infrared (FTIR) in combination with attenuated total reflectance (ATR) and discriminant analysis. The spectra were analysed using a chemometric method, principal component analysis (PCA), to classify and characterise gelatin compounds using regions of the FTIR spectra in the range of 3290–3280 cm^?1 and 1660–1200 cm^?1 as calibration models. Results from PCA, which were subsequently represented by the Cooman’s plot showed a clear distinction between gelatin samples of bovine and porcine origins. This qualitative approach, besides providing a rapid determination of the source of gelatin, may also be established based on a second derivative study of the FTIR spectrum to alleviate any doubt of the gelatin source for applications in the food and pharmaceutical industries.     

Volatile compounds as potential defective coffee beans’ markers

Although Brazil is the largest raw coffee producer and exporter in the world, a large amount of its Arabica coffee production is considered inappropriate for exportation. This by-product of coffee industry is called PVA due to the presence of black (P), green (V) and sour (A) defective beans, which are known to contribute considerably for cup quality decrease. Data on the volatile composition of Brazilian defective coffee beans are scarce. In this study, we evaluated the volatile composition of defective coffee beans (two lots) compared to good quality beans from the respective lots. Potential defective beans’ markers were identified. In the raw samples, 2-methylpyrazine and 2-furylmethanol acetate were identified only in black-immature beans and butyrolactone only in sour beans, while benzaldehyde and 2,3,5,6-tetramethylpyrazine showed to be potential markers of defective beans in general. In the roasted PVA beans, pyrazine, 2,3-butanediol meso, 2-methyl-5-(1-propenyl)pyrazine, hexanoic acid, 4-ethyl-guayacol and isopropyl p-cresol sulfide also showed to be potential defective coffee beans’ markers.     

ATR‐FTIR spectroscopy and chemometric analysis applied to discrimination of landrace maize flours produced in southern Brazil

This work aims at discriminating flours of 26 maize landraces from southern Brazil, by using the Attenuated Total Reflection Fourier Transform Infrared (ATR‐FTIR) spectroscopy and chemometrics (principal components analysis – PCA). PCA applied to the FTIR spectra in the 3‐600 (whole spectrum) and 1650–1500 cm^?1 (fingerprint region of proteins) spectral windows clearly discriminated the Amarelão landrace. Quantitative and semi‐qualitative analysis of proteins showed a wide range among the fractions, mainly of prolamine (13.47–28.43 g Kg^?1) and glutelin (5.57–30.98 g Kg^?1) contents. Pixurum 6, Pixurum 5, and MPA1 landraces are of superior nutritional value for their albumin, globulin, and glutelin contents. PCA of the spectral dataset in the fingerprint region to carbohydrates (1200–950 and 1065–950 cm^?1) also including commercial standards of amylose and amylopectin was able in separating the Moroti genotype, which grouped with the amylopectin standard. Thus, ATR‐FTIR and PCA showed to be useful tools for the quick screening and discrimination of maize with distinct chemical composition.     

Discrimination between Arabica and Robusta green coffee using visible micro Raman spectroscopy and chemometric analysis

We have applied visible micro Raman spectroscopy combined with principal component analysis (PCA) as a powerful technique for the fast discrimination between the two coffee species, Arabica and Robusta, based on their chlorogenic acid (CGA) and lipid contents. The Raman spectra reveal different CGA and lipid compositions when comparing Arabica and Robusta green coffee. Analysing the whole Raman spectrum, the PCA yielded a clear separation between Arabica and Robusta with 93% of the total spectral variation. Here, the most significant spectral range lies between 1000 and 1750 cm⁻¹ and is dominated by the Raman bands of CGA. Also, by restricting the PCA analysis to the spectral range from 2700 to 3050 cm⁻¹, which is dominated by lipid bands, a reliable discrimination between the two coffee species could be achieved. In this case, the first two principal components of the PCA accounted for 85% of the explained total spectral variation.     

基于机器视觉的咖啡生豆快速检测与分级研究

目的 为了实现咖啡生豆的快速无损等级评估,建立一种基于机器视觉的咖啡生豆快速检测分级方法。方法 本次研究提取咖啡生豆图像预处理后的形状和颜色共13种特征,首先通过特征分布图分析与主成分分析找到13类缺陷豆的显著特征,并确定其显著特征值范围来判定缺陷豆,然后对正常豆按粒度大小判断其等级,最后在MATLAB App Designer平台上设计了咖啡生豆快速检测与分级界面。结果 研究表明,利用机器视觉技术能很好地识别各个类别咖啡生豆,检测一级咖啡生豆准确率为94.77%、二级为93.2%、三级为95.85%,13类缺陷豆平均准确率为82.25%,咖啡生豆检测平均准确率达到91.52%,检测300g咖啡生豆总用时25.3156s。结论 提高了咖啡生豆分级的智能化水平,分级过程平稳且快速,为今后咖啡生豆在线检测分选提供了技术支持。     

Physicochemical characteristics of green coffee: comparison of graded and defective beans

ABSTRACT:  Defective (triage) coffee beans are beans rejected after separating the graded ones according to the size and color. These coffee beans represent about 15% to 20% of coffee production in India but are not utilized for beverages since these affect the quality of coffee brew. In the present study, physical characteristics such as bean density, brightness, titratable acidity, pH, moisture, and total soluble solids and also chemical composition, namely, caffeine, chlorogenic acids, lipids, sucrose, total polyphenols, and proteins, were evaluated in defective as well as in graded green coffee beans. The physical parameters such as weight, density, and brightness of defective coffee beans were low compared to the graded beans, which is due to the presence of immature, broken, bleached, and black beans. Caffeine content was low in triage beans compared to graded beans. Chlorogenic acids, one of the composition in coffee responsible for antioxidant activity, was found to be intact (marginally high in some cases) in defective coffee beans. Hence, triage coffee beans can be evaluated as a source of antioxidant or radical scavenging conserve for food systems.     

Proximate composition and fatty acids profile of green and roasted defective coffee beans

Defective coffee beans are responsible for the depreciation of the quality of roasted coffee consumed in Brazil. The extraction of the oil of defective beans for applications in the food and pharmaceutical sectors is being considered as an alternative use for those beans. The objective of this work was to determine the composition of the fatty acid fraction of the pressed oil and the proximate composition of crude defective beans in order to provide subsidiary information for proposals of alternative uses for these beans. The amounts of oil extracted from the defective beans were smaller than the amounts extracted from healthy mature beans. The fatty acid composition of oils from defective beans was not significantly different than that from healthy mature coffee beans.     

Discrimination of organic coffee via Fourier transform infrared-photoacoustic spectroscopy

BACKGROUND: Procedures for the evaluation of the origin and quality of ground and roasted coffee are constantly needed for the associated industry due to complexity of the related market. Conventional Fourier transform infrared (FTIR) spectroscopy can be used for detecting changes in functional groups of compounds, such as coffee. However, dispersion, reflection and non‐homogeneity of the sample matrix can cause problems resulting in low spectral quality. On the other hand, sample preparation frequently takes place in a destructive way. To overcome these difficulties, in this work a photoacoustic cell has been adapted as a detector in a FTIR spectrophotometer to perform a study of roasted and ground coffee from three varieties of Coffea arabica grown by organic and conventional methods. RESULTS: Comparison between spectra of coffee recorded by FTIR‐photoacoustic spectrometry (PAS) and by FTIR spectrophotometry showed a better resolution of the former method, which, aided by principal components analysis, allowed the identification of some absorption bands that allow the discrimination between organic and conventional coffee. CONCLUSION: The results obtained provide information about the spectral behavior of coffee powder which can be useful for establishing discrimination criteria. It has been demonstrated that FTIR‐PAS can be a useful experimental tool for the characterization of coffee. Copyright © 2012 Society of Chemical Industry     

Correlation between cup quality and chemical attributes of Brazilian coffee

Brazilian arabica coffee is classified for trading according to the quality of the beverage obtained after roasting and brewing. In the present study, Brazilian green and roasted coffee beans were investigated for possible correlations between cup quality and the levels of sucrose, caffeine, trigonelline and chlorogenic acids, determined by HPLC analysis. Trigonelline and 3,4-dicaffeoylquinic acid levels in green and roasted coffee correlated strongly with high quality. To a lesser extent, caffeine levels were also associated with good quality. On the other hand, the amount of defective beans, the levels of caffeoylquinic acids (predominantly 5-caffeoyilquinic acid), feruloylquinic acids, and their oxidation products were associated with poor cup quality and with the Rio-off-flavor. The fact that similar correlations between cup quality and chemical attributes were observed in green and light roasted samples – the latter used for coffee cup classification – indicates that chemical analysis of green beans may be used as an additional tool for coffee quality evaluation.