Determination of the geographical origin of green coffee beans using NIR spectroscopy and multivariate data analysis

In this work, near infrared (NIR) spectroscopy and multivariate data analysis were investigated as a fast and non disruptive method to classify green coffee beans on continents and countries bases. FT-NIR spectra of 191 coffee samples, origin from 2 continents and 9 countries, were acquired by two different laboratories. Laboratory-independent Partial Least Square-Discriminant Analysis and interval PIS-DA models were developed by following a hierarchical approach, i.e. considering at first the continent and then the country of origin as discrimination rule. The best continent-based classification model was able to identify correctly more than 98% in prediction, whereas 100% of them were correctly predicted by the best country-based classification model. The inter-laboratory reliability of the proposed method was confirmed by McNemar test, since no significant differences (P > 0.05) were found. Furthermore, a validation was performed predicting the spectral test set of a laboratory using the model developed by the other one

Classification of coffee beans by GC-C-IRMS, GC-MS, and 1H-NMR

In a previous work using 1H-NMR we reported encouraging steps towards the construction of a robust expert system for the discrimination of coffees from Colombia versus nearby countries (Brazil and Peru), to assist the recent protected geographical indication granted to Colombian coffee in 2007.This system relies on fingerprints acquired on a 400MHz magnet and is thus well suited for small scale random screening of samples obtained at resellers or coffee shops. However, this approach cannot easily be implemented at harbour's installations, due to the elevated operational costs of cryogenic magnets. This limitation implies shipping the samples to the NMR laboratory, making the overall approach slower and thereby more expensive and less attractive for large scale screening at harbours. In this work, we report on our attempt to obtain comparable classification results using alternative techniques that have been reported promising as an alternative toNMR: GC-MS andGC-C-IRMS.Although statistically significant information could be obtained by all threemethods, the results showthat the quality of the classifiers dependsmainly on the number of variables included in the analysis; hence NMR provides an advantage since more molecules are detected to obtain a model with better predictions

Trends in application of NIR and hyperspectral imaging for food authentication

Food fraud can cause damage to consumer health and affect their confidence, destroy brands and generate large economic losses in the industry. Food authenticity allows to identify if food composition, geographical origin, genetic variety and farming system corresponds to what has been declared on the label. Although there are currently standardized methods to identify certain adulterants, the complexity of the food, the complexity of the supply chain and the appearance of new adulterants require the continuous development of analytical techniques to detect food fraud. NIR and Hyperspectral imaging (HSI) in tandem with chemometrics are non-destructive, non-invasive and accurate techniques for food authentication. This review focuses on NIR and HIS approaches to food authentication, including adulteration by substitution, geographical origin and farming system. In this context, the advances in NIR and HSI approaches reported since 2014 are discussed regarding their potential use in food authentication. Both techniques have shown to have efficiency, precision and selectivity to detect adulterants and identify geographic origin, genetic variety and farming system. Portability and remote access are shown as the next step for the industrialization of NIR and HSI devices

Authentication of the origin, variety and roasting degree of coffee samples by non-targeted HPLC-UV fingerprinting and chemometrics. Application to the detection and quantitation of adulterated coffee samples

In this work, non-targeted approaches relying on HPLC-UV chromatographic fingerprints were evaluated to address coffee characterization, classification, and authentication by chemometrics. In general, HPLC-UV fingerprints were good chemical descriptors for the classification of coffee samples by PLS-DA according to their country of origin, even for nearby countries such as Vietnam and Cambodia. Good classification was also observed according to the coffee variety (Arabica vs. Robusta) and the coffee roasting degree. Sample classification rates higher than 89.3% and 91.7% were obtained in all the evaluated cases for the PLS-DA calibrations and predictions, respectively. Besides, the coffee adulteration studies carried out by PLSR, and based on coffees adulterated with other production regions or variety, demonstrated the good capability of the proposed methodology for the detection and quantitation of the adulterant levels down to 15%. Calibration, cross-validation and prediction errors below 2.9, 6.5, and 8.9%, respectively, were obtained for most of the evaluated cases

Klasifikasi Kopi Bubuk Spesialti Kalosi dan Toraja Menggunakan UV-Visible Spectroscopy dan Metode PLS-DA

 Specialty coffee is sold in a very expensive price. Specialty coffee is usually consumed as a single origin (without mixed with other coffee). For this reason, the detection of impurities (authentication) in specialty coffee is a very important process to be performed. In this study, UV-visible spectroscopy combined with PLS-DA method were used to discriminate between two specialty coffees from South Sulawesi (Kalosi and Toraja). A number of 100 ground roasted coffee samples were used for Kalosi and Toraja, respectively (1 gram each sample). A standard aqueous extraction procedure of the coffee samples using distilled water was performed and the spectral data of aqueous samples of Kalosi and Toraja coffee were acquired in transmittance mode using a UV-Visible spectrometer (Genesys™ 10S UV-Vis, Thermo Scientific, USA). The result showed that using PLS-DA method, all prediction samples were correctly classified into their corresponding classes with 100% rate for sensitivity, specificity, and accuracy, respectively

Seleção de variáveis em dados de espectroscopia no infravermelho para controle de qualidade

Nos últimos anos, a espectroscopia no infravermelho (IR) ganhou grande aceitação em diversas áreas de pesquisa por ser uma técnica rápida, simples e não destrutiva que permite a quantificação de diversos componentes químicos em amostras. Apesar de a IR resultar em valores de absorbância que auxiliam na caracterização da amostra, tal técnica acaba por gerar bancos de dados compostos por centenas, ou até milhares, de variáveis altamente correlacionadas e ruidosas, comprometendo o resultado de diversas técnicas de análise multivariada. Dentro deste cenário, esta Tese apresenta novas metodologias para seleção de variáveis, também chamada de seleção de comprimentos de onda quando aplicados em dados de IR, com o intuito de auxiliar o reconhecimento de padrões para o controle de qualidade em diversas áreas. Tais metodologias são apresentadas em três artigos onde as proposições visam à solução de problemas específicos: no primeiro artigo, amostras de erva mate são categorizadas de acordo com seu país de origem através de uma nova metodologia para seleção de variáveis Para tanto, um problema de Programação Quadrática, combinado com a Informação Mútua entre as variáveis, é utilizado para reduzir a redundância entre as variáveis retidas e maximizar sua relação com o local de origem da amostra; por sua vez, o segundo artigo adequa as proposições do primeiro artigo para um problema de predição, onde o objetivo é determinar a concentração de cocaína e adulterantes em amostras de cocaína laboratoriais e apreendidas; por fim, o terceiro artigo utiliza a estatística do teste de Kolmogorov-Smirnov para duas amostras em uma abordagem de seleção de intervalos de comprimentos de onda com o intuito de identificar falsificações em medicamentos para disfunção erétil. A aplicação dos métodos em bancos de dados com distintas características e a validação dos resultados corrobora a adequabilidade das proposições desta tese.Over the last few years infrared (IR) spectroscopy gained wide acceptance in many research fields as a quick, simple and non-destructive technique allowing the quantification of many chemical compounds. Although IR provide many absorbance values that helps the sample characterization, this technique also generate databases comprised by hundreds, or even thousands, of highly noisy and correlated wavenumbers, jeopardizing the results of many multivariate analysis techniques. Under such scenario, this thesis presents new variables selection methodologies (also called wavenumber selection when applied in IR data) aimed to recognize patterns for quality control in many areas. Such methodologies are presented in three papers where the propositions are tailored for the solution of specific problems: on the first paper, yerba mate samples are categorized according to their country of origin through a novel variable selection methodology. Thereunto a quadratic programming problem, combined with the Mutual Information among variables, is utilized to reduce the redundancy among variables and increase their relationship with the samples’ place of origin; the second paper adequate the first paper propositions for a prediction method which aims to determine cocaine and adulterants concentration in laboratorial and seized cocaine samples; lastly, the third paper uses the two-samples Kolmogorov-Smirnov statistic in an wavenumber interval selection method aimed for the identification of counterfeit erectile dysfunction medicines. The application of the methods in databases with distinct characteristics and the results validation corroborates the suitability of this thesis propositions

Spectroscopic techniques applied to the real time monitoring and control of the production processes of the pharmaceutical and food industry

L'abstract è presente nell'allegato / the abstract is in the attachmen