Aplicaciones de la Espectroscopia de Infrarrojo Cercano (NIR) para predecir el contenido y la actividad de agua del embutido tipo “Fuet“

The agri-food sector is one of the main economic engines in Europe. This sector includes the meat industry such as the production of cured sausages. The meat industry is committed to the development of new products and the establishment of quality and food safety controls to transfer to consumers the benefits and added value of its products. Therefore, it is important to implement innovative integrated production techniques and continuous improvement throughout the entire food chain. Quality controls at all levels of the production process are also important. Near infrared spectroscopy (NIRS) has demonstrated its ability to analyze food without altering its properties or destroying the analyzed piece or part of it. In addition, they are considered clean technologies, since they do not generate waste. The main objective of this work was to determine the potential of near infrared spectroscopy (NIRS) technique to be an adequate tool for predicting water activity (aw) and humidity in a cured meat product such as fuet in different parts: on the surface of the fuet, in the center of the fuet or in the minced fuet. To achieve this objective, the work was developed in different stages. Initially,the NIR spectra of the fuets were taken in different parts in a sausage factory using the SCiO pocket NIR instrument, then the aw and moisture values of the samples were determined and finally, with both kind of information, the prediction models were created and evaluated. The spectral and composition measurements were evaluated in the three variants (surface, center, and minced). And predictive models were then developed to determine moisture and water activity, by using the multivariate regression method PLS. Also, several data preprocessing protocols were applied in the spectra as a try to obtain the best calibration and prediction models with the minimum prediction error. The effect of the packaging film on the results of the prediction models was also studied. Furthermore, the performance of the NIR SCiO spectrophotometer was compared with that of an- house NIR Hamamatsu sensor, based on the values of coefficient of determination and the prediction errors of both devices. The obtained results showed that the NIR SCiO sensor provides a different response depending on the area analyzed (surface, center or minced), which is attributed to the change of matrix, the variation of the composition (salt / humidity, fat) and the structure of the sample, involving a different light scattering. At the same time, differences in precision have been observed due to the chosen spectral pretreatments. The prediction errors of the water and moisture activity obtained in the models of the three variants were considered adequate, where the coefficients of determination of prediction R2p were is above 0.97 for all preprocesses. Also, it has been shown that it is feasible to predict the aw and humidity of the minced samples even with the presence of the packaging film. The cross validation errors of the prediction models developed for the determination of water activity were similar, between 0.0039 with film and 0.0036 without film. But, they were different for the prediction of humidity, between 1.24 % y 1.71 % for the samples with film and without film respectively. Finally, the best prediction models of water and moisture activity in the case of samples with film was obtained with the NIR Scio spectrometer rather than the Hamamatsu spectrometer. The prediction coefficient with Scio was 0.9932 and 0.9925 for water activity and humidity respectively. With Hamamatsu sensor, the prediction coefficients were a slightly lower has decreased for both parameters of (0.9658 and 0.982, respectively).In brief, the results created revelaed that from the NIRS technology have proven its feasibility in accurate estimation of various food quality parameters and could represent an improvement in the control of drying systems of meat industry.El sector agroalimentario es uno de los principales motores económicos de Europa. Este sector incluye la industria cárnica como la producción de embutidos curados. La industria cárnica apuesta por el desarrollo de nuevos productos y el establecimiento de controles de calidad y seguridad alimentaria para transmitir a los consumidores los beneficios y el valor añadido de sus productos. Por ello, es importante la implantación de técnicas innovadoras de producción integrada y la mejora continua a lo largo de toda la cadena alimentaria. También son importantes los controles de calidad en todos los niveles del proceso de producción. La espectroscopia de infrarrojo cercano (NIRS) ha demostrado su capacidad para analizar los alimentos sin alterar sus propiedades ni destruir la pieza analizada o parte de ella. Además, se consideran tecnologías limpias, ya que no generan residuos. El objetivo principal de este trabajo ha sido determinar si la espectroscopia de infrarrojo cercano (NIRS) es una técnica adecuada para la predicción de la aw y la humedad en un producto cárnico curado como el fuet en distintas partes: en la superficie del fuet, en el centro del fuet y en el fuet picado. Para conseguir este objetivo, el trabajo se desarrolló en diferentes etapas. Inicialmente se tomaron los espectros NIR de los fuets en sus distintas partes en una fábrica de embutidos mediante el equipo NIR de bolsillo SCiO, seguidamente se realizaron los análisis de aw y humedad de las muestras y finalmente, con dicha información, se crearon los modelos de predicción. Se evaluó las diferencias espectrales y de composición en las tres areas analizadas (superficie, centro, y picado). Seguidamente se desarrollaron modelos predictivos para la determinación de la humedad y de la actividad de agua, mediante la aplicación del método de regresión multivariante PLS sin preprocesamiento. También, se aplicaron varios preprocesamientos en los espectros para construir los mejores modelos de calibración y predicción con el mínimo error de predicción. También se estudio el efecto del film de envasado en las muestras del fuet picado conservadas en congelación sobre los resultados de los modelos de predicción. Por ultimo, se comparó el espectrofotómetros NIR SCiO y el sensor NIR Hamamatsu, y se determinaron cuáles son los errores de predicción mediante ambos equipos. Los resultados obtenidos muestran que el sensor NIR SCiO proporciona una respuesta diferente según el aréa analizada (superficie, centro o picado), que se atribuye al cambio de matriz, la variación de la composición (NaCl/humedad, grasa) y la estructura de la muestra, comportando una reflexión de la luz distinta. Paralelamente, se han observado diferencias de precisión debido a los pretratamientos espectrales elegidos. Los errores de predicción de la actividad de agua y humedad obtenidos en los modelos de las tres areas se consideran adecuados, asi como el coeficiente de determinación de predicción R2 está por encima de 0.97 para todos los preprocesamientos. También, se ha demostrado que es factible predecir la aw y la humedad de las muestras picadas aunque haya film de envasado. Los errores de cross validación de los modelos de predicción desarrollados para la determinación de la actividad de agua, fueron similares, entre 0.0039 con film y 0.0036 sin film. Y fueron distintos para la prédiccion de la humedad, entre 1.24 % y 1.71 % para las muestras con film y sin film respectivamente. Finalmente, la mejor predicción de la actividad de agua y humedad en el caso de muestras con film se obtuvo con el NIR Scio. El coeficiente de determinación R2 con SCIO es 0.9932 para la actividad de agua y 0,9925 para la humedad. Con Hamamatsu, el coeficiente ha disminuido por los ambos paramétros (0.9658 y 0.982 ). Los resultados creados a partir de la tecnología NIRS han demostrado su viabilidad y podría representar una mejora en el control de los sistemas de secado

Environmental and yield comparison of quick extraction methods for caffeine and chlorogenic acid from spent coffee grounds

This study aims to provide an overview of different extraction methods to obtain chlorogenic acid (CA) and caffeine (Caf) from spent coffee grounds (SCG). This overview shows that the quantity extracted is highly dependent on the type of SCG, so experiments using the same SCG are needed to compare different methods. Three easy and simple extraction methods will be tested at a laboratory scale and environmentally compared. All three experiments were of 1 min duration: first, using supramolecular solvent; second, with water and vortex; and third, with water assisted by ultrasound. Water extraction assisted by ultrasound at room temperature yielded the greatest quantity of chlorogenic acid and caffeine, with 1.15 mg CA/g and 0.972 mg Caf/g, respectively. Extraction using supra-solvent leads to a lower content of CA in the supra-phase since it has more affinity for the water-based inferior phase. An environmental assessment using life cycle assessment has been carried out to compare water and supra extraction methods for the manufacture of two different commercial products: a face cream and an eye contour serum. Results show that the type of solvent and the amount of active substance extracted have a great influence on the environmental results. The results presented here are important for companies willing to obtain these active substances at an industrial scale.The authors wish to acknowledge the financial support from the Spanish Ministry of Science and Innovation to the project KAIROS-BIOCIR (PID2019-104925RB-C32). The first author also appreciates the support (2021FI SDUR 00130) from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund

Environmental and Yield Comparison of Quick Extraction Methods for Caffeine and Chlorogenic Acid from Spent Coffee Grounds

This study aims to provide an overview of different extraction methods to obtain chlorogenic acid (CA) and caffeine (Caf) from spent coffee grounds (SCG). This overview shows that the quantity extracted is highly dependent on the type of SCG, so experiments using the same SCG are needed to compare different methods. Three easy and simple extraction methods will be tested at a laboratory scale and environmentally compared. All three experiments were of 1 min duration: first, using supramolecular solvent; second, with water and vortex; and third, with water assisted by ultrasound. Water extraction assisted by ultrasound at room temperature yielded the greatest quantity of chlorogenic acid and caffeine, with 1.15 mg CA/g and 0.972 mg Caf/g, respectively. Extraction using supra-solvent leads to a lower content of CA in the supra-phase since it has more affinity for the water-based inferior phase. An environmental assessment using life cycle assessment has been carried out to compare water and supra extraction methods for the manufacture of two different commercial products: a face cream and an eye contour serum. Results show that the type of solvent and the amount of active substance extracted have a great influence on the environmental results. The results presented here are important for companies willing to obtain these active substances at an industrial scale