Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Chemical and physical attributes and calcium, magnesium, potassium, and phosphorus in the soil of murundu fields in Brazil

Fields of murundus (FM) are wetlands that provide numerous ecosystem services. The objectives of this study were to evaluate the chemical [organic carbon (OC), P, K+, Ca2+, Mg2+, Al3+ and H+Al] and physical [texture and bulk density (Bd)] soil attributes and calculate the organic matter (OM) and nutrient stock (P, Ca, Mg, and K) in soils of FM located in the Guapore River basin in Mato Grosso. Thirty-six sampling points were selected, and soil samples were collected from two environments: the murundu and plain area surrounding (PAS). At each sampling point, mini trenches of 0.5 × 0.5 × 0.4 m were opened and disturbed and undisturbed soil samples were collected at depths of 0-0.1, 0.1-0.2, and 0.2-0.4 m. In the Principal Component Analysis the variables H+Al (49%) and OM (4%) were associated with the F1 component and sand content (47%) with the F2 component. The FM had lower pH values and higher concentrations of K+, P, and H+Al than PAS at all depths (p < 0.05). Additionally, FM stocked up to 433, 360, 205, and 11 kg ha-1 of Ca, Mg, K, and P, respectively, for up to a depth of 0.2 m. The murundu stored two times more K and three times more P than that in the PAS. Our results show that the FM has high sand content and Bd greater than 1.5 Mg m-3, high acidity, low OC content, and low nutrient concentrations. Thus, special care must be taken to preserve FM such that human intervention does not trigger environmental imbalances.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Spatial and temporal evolution of family-farming land use in the Tapajós region of the Brazilian Amazon

Pressures on the Brazilian Amazon forest have been accentuated by agricultural activities practiced by families encouraged to settle in this region in the 1970s by the colonization program of the government. The aims of this study were to analyze the temporal and spatial evolution of land cover and land use (LCLU) in the lower Tapajós region, in the state of Pará. We contrast 11 watersheds that are generally representative of the colonization dynamics in the region. For this purpose, Landsat satellite images from three different years, 1986, 2001, and 2009, were analyzed with Geographic Information Systems. Individual images were subject to an unsupervised classification using the Maximum Likelihood Classification algorithm available on GRASS. The classes retained for the representation of LCLU in this study were: (1) slightly altered old-growth forest, (2) succession forest, (3) crop land and pasture, and (4) bare soil. The analysis and observation of general trends in eleven watersheds shows that LCLU is changing very rapidly. The average deforestation of old-growth forest in all the watersheds was estimated at more than 30% for the period of 1986 to 2009. The local-scale analysis of watersheds reveals the complexity of LCLU, notably in relation to large changes in the temporal and spatial evolution of watersheds. Proximity to the sprawling city of Itaituba is related to the highest rate of deforestation in two watersheds. The opening of roads such as the Transamazonian highway is associated to the second highest rate of deforestation in three watersheds.

Natural fibers for soil reinforcement

The reinforcement of soil is defined as an effective and reliable technique to improve strength and stability. For this propose, the use of natural fibers has been commonly. Over the past years, a series of studies have been performed in order to investigate the influence of randomly oriented fibers, especially for compressible clayey soils. However, less attention has been given to the reinforcing of sandy materials, as well as the use of oriented fibers meshes in order to improve mechanical behaviour. The main aim of this study is to identify the influence that different percentages of fibers, as well as the use of meshes of oriented fibers, has on soil mechanical behaviour. For this purpose, unconfined compression tests with local strain measurements were performed on a silty sand reinforced with Sisal fibers and a comparative study between randomly oriented and 0° and 90° fibers is presented.

Deteção remota na avaliação das alterações da cobertura do solo no Parque Nacional da Peneda-Gerês

Dissertação de mestrado integrado em Engenharia Civil

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Sustentabilidad del monocultivo de soja y otras alternativas agrícolas, en relación a los recursos suelo y agua, en la Región Centro-Norte de Córdoba. Sustainability of soybean monoculture and another agricultural alternatives, in relation to soil and water natural resources, in the north-central area of Cordoba (Argentina).

En este proyecto se pretende demostrar que existen alternativas sustentables al monocultivo de soja y económicamente factibles si se consideran los costos ambientales.Se cumplirán los siguientes objetivos específicos:- Caracterizar la sensibilidad de indicadores de calidad del suelo: infiltración, densidad aparente, penetrometría, C orgánico, fracciones de la MO y un índice químico de disponibilidad de N. - Medir escurrimiento y erosión en dos microcuencas con manejos contrastantes donde existe instrumental instalado y registros desde hace mas de 10 años.- Establecer rangos para las situaciones encontradas en los suelos representativos de la región.- Integrar los parámetros considerados en un sistema de diagnóstico de calidad/salud del suelo, para las condiciones de la región. - Aplicar el sistema de Calidad/salud del suelo para situaciones con monocultivo de soja y otras alternativas.- Calibrar y aplicar el modelo de simulación de la materia orgánica AMG, al monocultivo de soja y otras alternativas, a distintas escalas temporales y espaciales.- Estimar los costos ambientales de monocultivo a partir de los datos obtenidos.- Extrapolar los resultados del monocultivo y las otras alternativas a los suelos característicos, para estimar la sustentabilidad de los suelos en el centro-norte de la provincia de Córdoba.Se trabajará en dos áreas piloto en campos de productores, con y sin erosión hídrica. Se evaluarán parámetros indicadores del estado de los suelos, se los integrará en un sistema, se evaluarán los suelos con situaciones de monocultivo de soja y manejos contrastantes y se los correlacionará con su historial de intervención antrópica. Se brindará una herramienta apta para el ordenamiento territorial.

Manejo ganadero y restauración de ambientes montanos en relación a la biodiversidad, el suelo y la producción de agua. Livestock management and ecological restoration of mountain environments in relation to biodiversity, soil and water production.

Las áreas montanas brindan numerosos bienes y servicios a la humanidad cómo la provisión de agua. Asimismo, albergan una biota muy diversa y existe en ellas una actividad económica de considerable importancia centrada en la ganadería. En algunos casos las actividades asociadas a la ganadería pueden modificar los ecosistemas montanos y los bienes y servicios que brindan de forma drástica. Esto se debe a los cambios en la vegetación, y la pérdida y compactación de los suelos, que tiene repercusiones en la cantidad de agua captada, evapotranspirada y almacenada. También tiene repercusiones sobre la biodiversidad, tanto positivas como negativas. Aquí nos propusimos investigar cómo los cambios en la cobertura vegetal producidos por cuatro siglos de uso ganadero en el piso superior de las Sierras de Córdoba (Centro Argentino) han afectado a atributos del ecosistema como la diversidad vegetal, la integridad de los suelos y la capacidad de proveer agua a la población humana. A su vez, nos propusimos estudiar en detalle cómo las distintas opciones actuales de manejo pueden afectar a la cobertura vegetal y por ende a los atributos del ecosistema. De este modo, esperamos: (1) poder desarrollar un modelo espacialmente explícito que permita predecir la evolución del ecosistema ante distintos escenarios de manejo. (2) Más a largo plazo determinar los costos y los beneficios de los distintos manejos, en términos de la conservación de la biodiversidad, los suelos y la provisión de agua. El área de estudio cuenta un Sistema de Información Geográfica muy completo que incluye numerosas capas de información (vegetación, topografía, casas y caminos y otras). Además, existe en el área un Parque Nacional, con potreros bajo distintos manejos ganaderos (exclusión, cargas ganaderas moderadas continuas y estacionales), y una zona con herbivoría nativa de guanacos, que fueron reintroducidos recientemente en el Parque. Fuera del Parque, hay establecimientos con ganadería tradicional, con cargas ganaderas altas; así como un área donde se ha realizado una restauración modelo mediante reforestación y revegetación de zonas erosionadas. Estos escenarios representan una oportunidad muy especial para realizar estudios comparativos de la evolución de la fisonomía, composición florística, diversidad vegetal, integridad del suelo (erosión, tasa de infiltración, contenido de agua a lo largo del año) y el caudal de los arroyos en la estación seca. En este proyecto proponemos seguir con mediciones de la evolución de la vegetación bajo los distintos escenarios y seguir averiguando métodos de restauración de la vegetación. Además, proponemos empezar a realizar mediciones relacionadas al valor de los distintos tipos de cobertura vegetal, resultado de cuatro siglos de historia de disturbio, sobre la diversidad y los recursos hídricos. Por otro lado, realizaremos mediciones ecofisiológicas en las especies dominantes, para comprender sus efectos sobre el ciclo del agua.