Evaluación espectroscópica de un nuevo producto a base de pulpa de café

imagen hiperespectral en el rango VIS?NIR (400?1000 nm) para la evaluación de la pulpa de café deshidratada. La espectroscopia NIR ha mostrado su potencial para la segregación de muestras de pulpa con diferentes contenidos en humedad. Tanto la espectroscopia VIS como la imagen hiperespectral han mostrado su viabilidad para identificar el producto como de pulpa roja o amarilla o a una mezcla de ambas, a pesar de que en el producto deshidratado dejan de percibirse los tonos rojos o amarillos. Las herramientas quimiométricas aplicadas desvelan que las regiones del espectro entre 400 y 500 nm, banda de absorción de carotenos, y entre 500 y 535 nm, región de absorción relacionada con las antocioaninas, son las más significativas en los modelos de clasificación, lo que indica que la espectroscopia visible es capaz de percibir cualitativamente las posibles diferencias en los patrones de pigmentos presentes en la pulpa deshidratada de las variedades rojas y de las variedades amarillas

Estudio de técnicas para la supervisión de calidad y clasificación de granos de café tostado: análisis de nuevas tecnologías

El tostado es el paso más importante en el procesamiento del café, responsable de los cambios químicos, físicos, estructurales y organolépticos en el grano. Durante este proceso los granos verdes y secos son sometidos a un tratamiento caracterizado por varias temperaturas aplicadas en fases sucesivas a lo largo del tiempo consignado, que determinará las características finales del producto. El color es el parámetro más empleado para establecer el nivel de tostado del café, aspecto relevante en el momento de evaluar la calidad del producto final. Para la medición del color en el café existe instrumentación específica, colorímetros comerciales desarrollados exclusivamente para esta aplicación. El presente trabajo presenta y compara la instrumentación comercialmente disponible para asistencia en el control de calidad de la industria tostadora de café, y propone otros equipos cuya aplicación podría potencialmente aumentar el nivel de control sobre la operación de tostado aportando información adicional y complementaria a la de la colorimetría, como espectrofotómetros o técnicas de análisis de imagen

Advanced characterization of a coffee fermenting tank by multi-distributed wireless sensors: spatial interpolation and phase diagrams.

In coffee processing the fermentation stage is considered one of the critical operations by its impact on the final quality of the product. However, the level of control of the fermentation process on each farm is often not adequate; the use of sensorics for controlling coffee fermentation is not common. The objective of this work is to characterize the fermentation temperature in a fermentation tank by applying spatial interpolation and a new methodology of data analysis based on phase space diagrams of temperature data, collected by means of multi-distributed, low cost and autonomous wireless sensors. A real coffee fermentation was supervised in the Cauca region (Colombia) with a network of 24 semi-passive TurboTag RFID temperature loggers with vacuum plastic cover, submerged directly in the fermenting mass. Temporal evolution and spatial distribution of temperature is described in terms of the phase diagram areas which characterizes the cyclic behaviour of temperature and highlights the significant heterogeneity of thermal conditions at different locations in the tank where the average temperature of the fermentation was 21.2 °C, although there were temperature ranges of 4.6°C, and average spatial standard deviation of ±1.21ºC. In the upper part of the tank we found high heterogeneity of temperatures, the higher temperatures and therefore the higher fermentation rates. While at the bottom, it has been computed an area in the phase diagram practically half of the area occupied by the sensors of the upper tank, therefore this location showed higher temperature homogeneit

Prospective of Innovative Technologies for Quality Supervision and Classification of Roasted Coffee Beans

Color sorting is the major procedure employed for establish roast degree of coffee beans. However, color-based procedures have been proven to be ineffective, since coffee beans roasted to different degrees can present the same average readings in light reflectance measurements with significant quality variations. Besides to color, other major changes in beans are volume (swell), mass, form, bean pop and density. Eight samples of arabica coffee from Colombia and Guatemala have been roasted under slightly different conditions of time and temperature in order to obtain the same color classification. Sample analysis of data from nuclear magnetic resonance relaxometry show differences between samples in T1 and T2 parameters at cellular and subcellular level, and image analysis carried out on X-ray μCT leading to microestruture images corroborate differences in porosity and fissures presence among them, proving the potentiality of these technological solutions for sensing the microstructure of coffee to provide tools to enhance the roasting process

Advanced Characterisation of a Coffee Fermenting Tank by Multi-distributed Wireless Sensors: Spatial Interpolation and Phase Space Graphs

The fermentation stage is considered to be one of the critical steps in coffee processing due to its impact on the final quality of the product. The objective of this work is to characterise the temperature gradients in a fermentation tank by multi-distributed, low-cost and autonomous wireless sensors (23 semi-passive TurboTag® radio-frequency identifier (RFID) temperature loggers). Spatial interpolation in polar coordinates and an innovative methodology based on phase space diagrams are used. A real coffee fermentation process was supervised in the Cauca region (Colombia) with sensors submerged directly in the fermenting mass, leading to a 4.6 °C temperature range within the fermentation process. Spatial interpolation shows a maximum instant radial temperature gradient of 0.1 °C/cm from the centre to the perimeter of the tank and a vertical temperature gradient of 0.25 °C/cm for sensors with equal polar coordinates. The combination of spatial interpolation and phase space graphs consistently enables the identification of five local behaviours during fermentation (hot and cold spots)

Methods for interpolating missing data in aerobiological databases

Missing data is a common problem in scientific research. The availability of extensive environmental time series is usually laborious and difficult, and sometimes unexpected failures are not detected until samples are processed. Consequently, environmental databases frequently have some gaps with missing data in it. Applying an interpolation method before starting the data analysis can be a good solution in order to complete this missing information. Nevertheless, there are several different approaches whose accuracy should be considered and compared. In this study, data from 6 aerobiological sampling stations were used as an example of environmental data series to assess the accuracy of different interpolation methods. For that, observed daily pollen/spore concentration data series were randomly removed, interpolated by using different methods and then, compared with the observed data to measure the errors produced. Different periods, gap sizes, interpolation methods and bioaerosols were considered in order to check their influence in the interpolation accuracy. The moving mean interpolation method obtained the highest success rate as average. By using this method, a success rate of the 70% was obtained when the risk classes used in the alert systems of the pollen information platforms were taken into account. In general, errors were mostly greater when there were high oscillations in the concentrations of biotic particles during consecutive days. That is the reason why the pre-peak and peak periods showed the highest interpolation errors. The errors were also higher when gaps longer than 5 days were considered. So, for completing long periods of missing data, it would be advisable to test other methodological approaches. A new Variation Index based on the behaviour of the pollen/spore season (measurement of the variability of the concentrations every 2 consecutive days) was elaborated, which allows to estimate the potential error before the interpolation is applied

Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields

We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities. Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper. We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data

Building an Automatic Pollen Monitoring Network (ePIN): Selection of Optimal Sites by Clustering Pollen Stations

Airborne pollen is a recognized biological indicator and its monitoring has multiple uses such as providing a tool for allergy diagnosis and prevention. There is a knowledge gap related to the distribution of pollen traps needed to achieve representative biomonitoring in a region. The aim of this manuscript is to suggest a method for setting up a pollen network (monitoring method, monitoring conditions, number and location of samplers etc.). As a case study, we describe the distribution of pollen across Bavaria and the design of the Bavarian pollen monitoring network (ePIN), the first operational automatic pollen network worldwide. We established and ran a dense pollen monitoring network of 27 manual Hirst-type pollen traps across Bavaria, Germany, during 2015. Hierarchical cluster analysis of the data was then performed to select the locations for the sites of the final pollen monitoring network. According to our method, Bavaria can be clustered into three large pollen regions with eight zones. Within each zone, pollen diversity and distribution among different locations does not vary significantly. Based on the pollen zones, we opted to place one automatic monitoring station per zone resulting in the ePIN network, serving 13 million inhabitants. The described method defines stations representative for a homogeneous aeropalynologically region, which reduces redundancy within the network and subsequent costs (in the study case from 27 to 8 locations). Following this method, resources in pollen monitoring networks can be optimized and allergic citizens can then be informed in a timely and effective way, even in larger geographical areas

Biosphere futures: a database of social-ecological scenarios

Environmental Biolog

Uncovering Ecosystem Service Bundles through Social Preferences

Ecosystem service assessments have increasingly been used to support environmental management policies, mainly based on biophysical and economic indicators. However, few studies have coped with the social-cultural dimension of ecosystem services, despite being considered a research priority. We examined how ecosystem service bundles and trade-offs emerge from diverging social preferences toward ecosystem services delivered by various types of ecosystems in Spain. We conducted 3,379 direct face-to-face questionnaires in eight different case study sites from 2007 to 2011. Overall, 90.5% of the sampled population recognized the ecosystem’s capacity to deliver services. Formal studies, environmental behavior, and gender variables influenced the probability of people recognizing the ecosystem’s capacity to provide services. The ecosystem services most frequently perceived by people were regulating services; of those, air purification held the greatest importance. However, statistical analysis showed that socio-cultural factors and the conservation management strategy of ecosystems (i.e., National Park, Natural Park, or a non-protected area) have an effect on social preferences toward ecosystem services. Ecosystem service trade-offs and bundles were identified by analyzing social preferences through multivariate analysis (redundancy analysis and hierarchical cluster analysis). We found a clear trade-off among provisioning services (and recreational hunting) versus regulating services and almost all cultural services. We identified three ecosystem service bundles associated with the conservation management strategy and the rural-urban gradient. We conclude that socio-cultural preferences toward ecosystem services can serve as a tool to identify relevant services for people, the factors underlying these social preferences, and emerging ecosystem service bundles and trade-offs