Quality evaluation of cheddar cheese containing Gamma-Oryzanol

Health benefits from consuming rice bran oil (RBO) have been extensively studied in humans. RBO has been shown to decrease cholesterol absorption by inhibiting the oxidation of the LDL-cholesterol. Gamma-Oryzanol is one of the RBO components that possess antioxidative properties; it is a polyphenolic compound resembling tocopherol (vitamin E), which is another component of RBO. There are evidences that oryzanol has potential applications for enhancing shelf-life of foods containing fats processed at a high temperature, decreasing the total cholesterol, LDL-cholesterol and triglyceride levels in plasma lipids, and healing ulcers. In order to take advantage of the health benefits of oryzanol, food products fortified with oryzanol should be developed and characterized. Cheddar cheese containing Gamma-Oryzanol was developed, and the effects of oryzanol on cheese quality during ripening process were studied. Cheese was stored for 5 months and drawn every month for quality evaluation of color, texture, microbial growth, aroma development, bacterial identification by polymerase chain reaction, oryzanol retention, moisture content and free fatty acid profile. The consumer acceptance was evaluated after 5 months of maturation. The results indicated that by adding Gamma-Oryzanol to cheddar cheese changes occurred in the quality, but, they were not significant when stored for up to 4 months, and the Gamma-Oryzanol was well retained. Consumers were able to differentiate the cheddar cheese containing Gamma-Oryzanol from the control containing no Gamma-Oryzanol. Overall appearance, texture, taste and hardness were the most discriminatory sensory attributes. There was a significant positive increase 0.13 to 0.30 times higher in the purchase intent of cheddar cheese containing Gamma-Oryzanol after consumers had been informed about the health benefits of oryzanol. Overall liking was the attribute critical to purchase intent and the most important attribute that changed the acceptability of the cheese. Consumers preferred the cheese with Gamma-Oryzanol less than the control but were willing to buy it and compromise the overall liking of cheese merely to get the health benefits of the product. Further studies need to be done to determine the direct effects of cheddar cheese containing Gamma-Oryzanol in human health, and to optimize the homogenization and fortification of Gamma-Oryzanol when incorporated in cheese products

Other Buds in Membrane Computing

It is well-known the huge Mario’s contribution to the development of Membrane Computing. Many researchers may relate his name to the theory of complexity classes in P systems, the research of frontiers of the tractability or the application of Membrane Computing to model real-life situations as the Quorum Sensing System in Vibrio fischeri or the Bearded Vulture ecosystem. Beyond these research areas, in the last years Mario has presented many new research lines which can be considered as buds in the robust Membrane Computing tree. Many of them were the origin of new research branches, but some others are still waiting to be developed. This paper revisits some of these buds

Doppler wind LIDAR systems data processing and applications : an overview towards developing the new generation of wind remote-sensing sensors for off-shore wind farms

This Ph.D. thesis addresses remote sensing of the atmosphere by means of lidar and S-band clear-air weather radar, and related data signal processing. Active remote sensing by means of these instruments offers unprecedented capabilities of spatial and temporal resolutions for vertical atmospheric profiling and the retrieval of key optical and physical atmospheric products in an increasing environmental regulatory framework. The first goal is this Ph.D. concerns the estimation of error bounds in the inversion of the profile of the atmospheric backscatter coefficient from elastic lidar signals (i.e., without wavelength shift in reception when interacting with atmospheric scatterers) by means of the two-component inversion algorithm (the so-called Klett-Fernald-Sasano’s algorithm). This objective departs from previous works at the Remote Sensing Lab. (RSLab) of the Universitat Politècnica de Catalunya (UPC) and derives first-order error-propagated bounds (approximate) and total-increment bounds (exact). As distinctive feature in the state of the art, the error bounds merge into a single body both systematic (i.e., user-calibration inputs) and random error sources (finite signal-to-noise ratio, SNR) yielding an explicit mathematical form. The second goal, central to this Ph.D., tackles retrieval of the Atmospheric Boundary Layer Height (ABLH) from elastic lidar and S-band Frequency-Modulated Continuous-Wave (FMCW) radar observations by using adaptive techniques based on the Extended Kalman Filter (EKF). The filter is based on morphological modelling of the Mixing-Layer-to-Free-Troposphere transition and continuous estimation of the noise covariance information. In the lidar-EKF realization the proposed technique is shown to outperform classic ABLH estimators such as those based on derivative techniques, thresholded decision, or the variance centroid method. The EKF formulation is applied to both ceilometer and UPC lidar records in high- and low-SNR scenes. The lidar-EKF approach is re-formulated and successfully extended to S-band radar scenes (Bragg’s scattering) in presence of interferent noise sources (Rayleigh scattering from e.g., insects and birds). In this context, the FMCW feature enables the range-resolved capability. EKF-lidar and EKF-radar ABLH estimates are cross-examined from field campaign results. Finally, the third goal deals with exploitation of the existing UPC lidar station: In a first introductory part, a modified algorithm for enhancing the dynamic range of elastic lidar channels by “gluing” analog and photon-counting data records is formulated. In a second part, two case examples (including application of the gluing algorithm) are presented to illustrate the capabilities of the UPC lidar in networked atmospheric observation of two recent volcano eruption events as part of the EARLINET (European Aerosol Research Lidar Network). The latter is part of GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network)-GEOSS (Global Earth Observation System of Systems) framework.La tesis doctoral aborda la teledetecció atmosfèrica amb tècniques lidar i radar (banda S) i llur tractament del senyal. La teledetecció activa amb aquests instruments ofereix resolucions espacials i temporals sense precedents en la perfilometria vertical de l’atmosfera i recuperació de productes de dades òptics i físics atmosfèrics en un marc de creixent regulació mediambiental. El primer objectiu d’aquesta tesi concerneix l’estimació de cotes d’error en la inversió del perfil del coeficient de retrodispersió atmosfèrica a partir de senyals lidar de tipus elàstic (és a dir, sense desplaçament de la longitud d’ona en recepció al interactuar amb els dispersors atmosfèrics) mitjançant l’algorisme d’inversió de dues components de Klett-Fernald-Sasano. Aquest objectiu parteix de treballs previs en el Remote Sensing Lab. (RSLab) de la Universitat Politècnica de Catalunya (UPC) i permet obtenir cotes de primer ordre (aproximades) basades en propagació d’errors i cotes (exactes) basades en el increment total de l’error. Característica diferencial en front l’estat de l’art és l’assimilació d’errors sistemàtics (per exemple, entrades de cal·libració d’usuari) i aleatoris (relació senyal-soroll, SNR, finita) en forma matemàtica explícita. El segon objectiu, central de la tesis, aborda l’estimació de l’altura de la capa límit atmosfèrica (ABLH) a partir de senyal lidar elàstics i d’observacions radar en banda S (ona continua amb modulació en freqüència, FMCW) utilitzant tècniques adaptatives basades en filtrat estès de Kalman (EKF). El filtre es basa en modelat morfològic de la transició atmosfèrica entre la capa de mescla i la troposfera lliure i en l’estimació continua de la informació de covariança del soroll. En el prototipus lidar-EKF la tècnica proposada millora clarament les tècniques clàssiques d’estimació de la ABLH como són les basades en mètodes derivatius, decisió de llindar, o el mètode de la variança-centroide. La formulació EKF s’aplica tant a mesures procedents de ceilòmetres lidar como de la pròpia estació lidar UPC en escenes d’alta i baixa SNR. Addicionalment, l’enfoc lidar-EKF es reformula i s’estén amb èxit a escenes radar en banda S (dispersió Bragg) en presència de fonts de soroll interferent (dispersió Rayleigh de, per exemple, insectes i ocells). En aquest context, la característica FMCW permet la capacitat de resolució en distància. L’estimació de la ABLH amb els prototipus lidar-EKF i radar-EKF s’interrompés en campanyes de mesura. Finalment, el tercer objectiu atén a l’explotació de l’estació lidar UPC existent: En una primera part introductòria, es formula un algorisme modificat de “gluing” per a la millora del marge dinàmic de canals lidar elàstics mitjançant combinació (o "enganxat") de senyals lidar adquirits analògicament i amb foto-comptatge. En una segona part, es presenten dos exemples (incloent l’aplicació de l’algorisme de “gluing”) que il·lustren les capacitats del lidar de la UPC en l’observació atmosfèrica de dos recents erupcions volcàniques des de la xarxa d’observació EARLINET (European Aerosol Research Lidar Network). Aquesta última és part de GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network)-GEOSS (Global Earth Observation System of Systems).Postprint (published version