FTIR-ATR Analysis of Brewed Coffee:  Effect of Roasting Conditions

Lyman, Donald J.; Benck, Robert; Dell, Stacy; Merle, Scott; Murray-Wijelath, Jacqueline

doi:10.1021/jf0209793

Cited by 129 publications

(125 citation statements)

References 5 publications

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“…The spectrum displays prominent peaks at 2930 and 2875 cm -1 , which are characteristic of C-H stretching modes of aliphatic chains and are typically present in the infrared signature of coffee. 39,43 A broad peak consisting of multiple contributions and with resolved maxima at 1670 and 1606 cm -1 is characteristic of carbonyl stretching modes and C-C stretching contributions from aromatic (chlorogenic) acids and caffeine. [43][44][45] Finally, there are two additional smaller peaks at 1285 and 1090 cm -1 that fall in the region of C-O stretching modes and can be assigned to the presence of chlorogenic acids and saccharides.…”

Section: Characterization Of Metal Surfacesmentioning

confidence: 99%

“…39,43 A broad peak consisting of multiple contributions and with resolved maxima at 1670 and 1606 cm -1 is characteristic of carbonyl stretching modes and C-C stretching contributions from aromatic (chlorogenic) acids and caffeine. [43][44][45] Finally, there are two additional smaller peaks at 1285 and 1090 cm -1 that fall in the region of C-O stretching modes and can be assigned to the presence of chlorogenic acids and saccharides. 44 A comparison of IRRAS data with the ATR-FTIR spectrum of coffee powder used for preparing reducing solutions suggests a good correspondence between compounds present in coffee and those found at the Pd surface, thus indicating that organic residues can bind to palladium surfaces following the washing procedure employed in this work.…”

Section: Characterization Of Metal Surfacesmentioning

confidence: 99%

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Green Synthesis of Metal Nanoparticles via Natural Extracts: The Biogenic Nanoparticle Corona and Its Effects on Reactivity

Metz

Sanders

Pender

et al. 2015

ACS Sustainable Chem. Eng.

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The optical and catalytic properties of metal nanoparticles have attracted significant attention for applications in a wide variety of fields, thus prompting interest in developing sustainable synthetic strategies that leverage the redox properties of natural compounds or extracts. Here, we investigate the surface chemistry of nanoparticles synthesized using coffee as a biogenic reductant. Building on our previously developed synthetic protocols for the preparation of silver and palladium nanoparticle/carbon composite microspheres a combination of thermogravimetric and spectroscopic methods were used to characterize the carbon microsphere and nanoparticle surfaces. Infrared reflectance spectroscopy and single particle surface enhanced Raman spectroscopy were used to characterize Pd and Ag metal surfaces, respectively, following synthesis. Strongly adsorbed organic layers were found to be present at metal nanoparticle surfaces after synthesis. The catalytic activity of Pd nanoparticles in hydrogenation reactions were leveraged to study the availability of surface sites, and coffee-synthesized nanomaterials were compared to commercial Pd-based hydrogenation catalysts. Our results demonstrate that biogenic adsorbates block catalytic surface sites and affect nanoparticle functionality. These findings highlight the need for careful analysis of surface chemistry as it relates to the specific applications of nanomaterials produced using greener or more sustainable methods.

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Section: Characterization Of Metal Surfacesmentioning

confidence: 99%

Section: Characterization Of Metal Surfacesmentioning

confidence: 99%

Green Synthesis of Metal Nanoparticles via Natural Extracts: The Biogenic Nanoparticle Corona and Its Effects on Reactivity

Metz

Sanders

Pender

et al. 2015

ACS Sustainable Chem. Eng.

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“…Aldehydes correspond to 1, 720-1,740 cm -1 , Ketones to 1,705-1,750 cm -1 and carboxylic acids to 1,700-1,725 cm -1 . Ketones have the simplest spectra among the carbonyl compounds, with the C=O stretch and the C-H stretch being the major absorptions (Lyman et al 2003) …”

Section: Identification Of Compounds By Gc-msmentioning

confidence: 99%

Effect of edible coating on the aromatic attributes of roasted coffee beans

et al. 2015

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Coffee is known throughout the world for its distinct aroma and flavour which results from a number of volatile compounds present in it. It is very difficult to arrest the aromatic compounds once the roasting process is complete and it becomes even more challenging to store the beans for a longer time with the retained volatiles as these compounds are easily lost during industrialized processing such as the grinding of roasted coffee beans and storage of ground coffee. Thus, an attempt was made to minimise the loss of volatile from roasted coffee beans by coating with Carboxymethyl cellulose (CMC), Hydroxypropylmethyl cellulose (HPMC) and Whey protein concentrate. Coffee volatiles were analysed by Gas chromatography and 14 major compounds were identified and compared in this study. Results showed an increase in the relative area of major volatile compounds in coated roasted coffee beans when compared with unroasted coffee beans for consecutive two months. Moreover, effect of coating on textural properties and non-volatiles were also analysed. The results have indicated that edible coatings preserve the sensory properties of roasted coffee beans for a longer shelf life and cellulose derivatives, as an edible coating, exhibited the best protecting effect on roasted coffee beans.

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“…Também foi avaliada a região entre 1900 e 800 cm -1 do espectro pois a mesma contem as bandas de absorção devidas à deformação axial simétrica da carbonila (ésteres, aldeídos e cetonas), deformação angular simétrica do metileno, deformações axiais e angulares simétricas do C-O (ésteres e alcoóis). Portanto, essa região contém a informação de fingerprint para discriminação de diferentes amostras de cafés LYMAN et al, 2003;WANG et al, 2009;WANG et al, 2011).…”

Section: Transformação Dos Espectrosunclassified

Optimized Multilayer perceptron for the geographical and genotypic classification of four genotypes of arabica coffee

Link¹,

Lemes²,

Sato³

et al. 2013

REBRAPA

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Resumo: As condições climáticas específicas de cada região de cultivo do café fornecem atributos especiais para a bebida e podem assim aumentar seu valor agregado. No entanto, é essencial provar a origem geográfica e genotípica do cultivar por meio de métodos confiáveis. Vários métodos estatísticos foram desenvolvidos na tentativa de reproduzir a capacidade humana de reconhecimento de padrões. Os perceptrons de múltiplas camadas (MLP) são um tipo de rede neural artificial (RNA) com aprendizagem supervisionada que são muito utilizados para classificação de padrões. Este estudo objetivou o desenvolvimento de uma RNA para a classificação geográfica e genotípica de café arábica. Para esse fim os espectros obtidos no equipamento de espectroscopia no infravermelho com transformada de Fourier (FTIR) foram analisados através do emprego de MLPs otimizados através do simplex sequencial. As redes que utilizaram a faixa de 1900-800 cm -1 do espectro FTIR obtiveram menor erro quadrado médio e maior porcentagem de classificação correta para a segmentação das amostras de café arábica tanto por região de cultivo (100%) quanto por genótipo (77,78%). Os MLPs otimizados foram capazes de classificar geograficamente as amostras de café arábica. Entretanto, para a classificação genotípica o desempenho não foi totalmente satisfatório. Além disso, o MLP desenvolvido para classificação genotípica apresenta um número muito elevado de pesos sinápticos, não proporcionando número suficiente de graus de liberdade para que a rede neural possa aprender de maneira confiável. Portanto, para melhorar o desempenho da classificação genotípica, os autores sugerem a utilização de outro tipo de RNA e informações do infravermelho próximo. Palavras-chave:Café Verde, Espectro Infravermelho, MLP, Redes Neurais Artificiais. Optimized Multilayer perceptron for the geographical and genotypic classification of four genotypes of arabica coffee:The climatic conditions of the coffee crop give special attributes to the beverage and could increase its value. However, it is essential to prove the geographical and genotype origin of the cultivar using reliable methods. Several statistical methods have been developed in an attempt to reproduce the human capability of pattern recognition. The multilayer perceptron (MLP) is an artificial neural network (ANN) with supervised learning that is widely used for pattern classification. This study aimed to develop a MLP to classify the geographic origin and the genotypic of the arabica coffee. For this purpose, spectra obtained in the Fourier transform infrared (FTIR) were analyzed using MLPs optimized by sequential simplex. The networks that used the range 1900-800 cm -1 of the raw spectrum had lower mean squared error (MSE) and a higher percentage of correct classification for geographical (100%) and genotypic (77,74%) segmentation. After the results it was concluded that the optimized multilayer perceptrons were able to classify the samples of arabica coffee geographically. However, for genotypic classification the perform...

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FTIR-ATR Analysis of Brewed Coffee: Effect of Roasting Conditions

Cited by 129 publications

References 5 publications

Green Synthesis of Metal Nanoparticles via Natural Extracts: The Biogenic Nanoparticle Corona and Its Effects on Reactivity

Green Synthesis of Metal Nanoparticles via Natural Extracts: The Biogenic Nanoparticle Corona and Its Effects on Reactivity

Effect of edible coating on the aromatic attributes of roasted coffee beans

Optimized Multilayer perceptron for the geographical and genotypic classification of four genotypes of arabica coffee

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