5 resultados para cold season

em CORA - Cork Open Research Archive - University College Cork - Ireland


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The aim of this study was to develop a methodology, based on satellite remote sensing, to estimate the vegetation Start of Season (SOS) across the whole island of Ireland on an annual basis. This growing body of research is known as Land Surface Phenology (LSP) monitoring. The SOS was estimated for each year from a 7-year time series of 10-day composited, 1.2 km reduced resolution MERIS Global Vegetation Index (MGVI) data from 2003 to 2009, using the time series analysis software, TIMESAT. The selection of a 10-day composite period was guided by in-situ observations of leaf unfolding and cloud cover at representative point locations on the island. The MGVI time series was smoothed and the SOS metric extracted at a point corresponding to 20% of the seasonal MGVI amplitude. The SOS metric was extracted on a per pixel basis and gridded for national scale coverage. There were consistent spatial patterns in the SOS grids which were replicated on an annual basis and were qualitatively linked to variation in landcover. Analysis revealed that three statistically separable groups of CORINE Land Cover (CLC) classes could be derived from differences in the SOS, namely agricultural and forest land cover types, peat bogs, and natural and semi-natural vegetation types. These groups demonstrated that managed vegetation, e.g. pastures has a significantly earlier SOS than in unmanaged vegetation e.g. natural grasslands. There was also interannual spatio-temporal variability in the SOS. Such variability was highlighted in a series of anomaly grids showing variation from the 7-year mean SOS. An initial climate analysis indicated that an anomalously cold winter and spring in 2005/2006, linked to a negative North Atlantic Oscillation index value, delayed the 2006 SOS countrywide, while in other years the SOS anomalies showed more complex variation. A correlation study using air temperature as a climate variable revealed the spatial complexity of the air temperature-SOS relationship across the Republic of Ireland as the timing of maximum correlation varied from November to April depending on location. The SOS was found to occur earlier due to warmer winters in the Southeast while it was later with warmer winters in the Northwest. The inverse pattern emerged in the spatial patterns of the spring correlates. This contrasting pattern would appear to be linked to vegetation management as arable cropping is typically practiced in the southeast while there is mixed agriculture and mostly pastures to the west. Therefore, land use as well as air temperature appears to be an important determinant of national scale patterns in the SOS. The TIMESAT tool formed a crucial component of the estimation of SOS across the country in all seven years as it minimised the negative impact of noise and data dropouts in the MGVI time series by applying a smoothing algorithm. The extracted SOS metric was sensitive to temporal and spatial variation in land surface vegetation seasonality while the spatial patterns in the gridded SOS estimates aligned with those in landcover type. The methodology can be extended for a longer time series of FAPAR as MERIS will be replaced by the ESA Sentinel mission in 2013, while the availability of full resolution (300m) MERIS FAPAR and equivalent sensor products holds the possibility of monitoring finer scale seasonality variation. This study has shown the utility of the SOS metric as an indicator of spatiotemporal variability in vegetation phenology, as well as a correlate of other environmental variables such as air temperature. However, the satellite-based method is not seen as a replacement of ground-based observations, but rather as a complementary approach to studying vegetation phenology at the national scale. In future, the method can be extended to extract other metrics of the seasonal cycle in order to gain a more comprehensive view of seasonal vegetation development.

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Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

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In the area of food and pharmacy cold storage, temperature distribution is considered as a key factor. Inappropriate distribution of temperature during the cooling process in cold rooms will cause the deterioration of the quality of products and therefore shorten their life-span. In practice, in order to maintain the distribution of temperature at an appropriate level, large amount of electrical energy has to be consumed to cool down the volume of space, based on the reading of a single temperature sensor placed in every cold room. However, it is not clear and visible that what is the change of energy consumption and temperature distribution over time. It lacks of effective tools to visualise such a phenomenon. In this poster, we initially present a solution which combines a visualisation tool with a Computational Fluid Dynamics (CFD) model together to enable users to explore such phenomenon.

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In this thesis we relate the formal description of various cold atomic systems in the energy eigenbasis, to the observable spatial mode dynamics. Herein the `spatial mode dynamics' refers to the direction of photon emission following the spontaneous emission of an excited fermion in the presence of a same species and spin ideal anisotropic Fermi sea in its internal ground state. Due to the Pauli principle, the presence of the ground state Fermi sea renders the phase space, anisotropic and only partially accessible, thereby a ecting the direction of photon emission following spontaneous emission. The spatial and energetic mode dynamics also refers to the quantum `tunneling' interaction between localised spatial modes, synonymous with double well type potentials. Here we relate the dynamics of the wavefunction in both the energetic and spatial representations. Using this approach we approximate the relationship between the spatial and energetic representations of a wavefunction spanning three spatial and energetic modes. This is extended to a process known as Spatial Adiabatic Passage, which is a technique to transport matter waves between localised spatial modes. This approach allows us to interpret the transport of matter waves as a signature of a geometric phase acquired by the one of the internal energy eigenstates of the system during the cyclical evolution. We further show that this geometric phase may be used to create spatial mode qubit and qutrit states.

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Defects in commercial cheese result in a downgrading of the final cheese and a consequential economic loss to the cheese producer. Developments of defects in cheese are often not fully understood and therefore not controllable by the producer. This research investigated the underlying factors in the development of split and secondary fermentation defect and of pinking defects in commercial Irish cheeses. Split defect in Swiss-type cheese is a common defect associated with eye formation and manifests as slits and cracks visible in the cut cheese loaf (Reinbold, 1972; Daly et al., 2010). No consensus exists as to the definitive causes of the defect and possible factors which may contribute to the defect were reviewed. Models were derived to describe the relationship between moisture, pH, and salt levels and the distance from sample location to the closest external block surface during cheese ripening. Significant gradients within the cheese blocks were observed for all measured parameters in cheeses at 7 day post/after manufacture. No significant pH gradient was found within the blocks on exit from hot-room ripening and at three months post exit from the hot-room. Moisture content reached equilibrium within the blocks between exit from hot-room and 3 months after exit from hot-room while salt and salt-to-moisture levels had not reached equilibrium within the cheese blocks even at three months after exit from hot-room ripening. A characterisation of Swiss-type cheeses produced from a seasonal milk supply was undertaken. Cheeses were sampled on two days per month of the production year, at three different times during the manufacturing day, at internal and external regions of the cheese block and at four ripening time points (7 days post manufacture, post hot-room, 14 days post hot-room and 3 months in a cold room after exit from hot-room). Compositional, biochemical and microbial indices were determined, and the results were analysed as a splitplot with a factorial arrangement of treatments (season, time of day, area) on the main plot and ripening time on the sub-plot. Season (and interactions) had a significant effect on pH and salt-in-moisture levels (SM), mean viable counts of L. helveticus, propionic acid and non-starter lactic acid bacteria, levels of primary and secondary proteolysis and cheese firmness. Levels of proteolysis increased significantly during hot-room ripening but also during cold room storage, signifying continued development of cheese ripening during cold storage (> 8°C). Rheological parameters (e.g. springiness and cohesiveness) were significantly affected by interactions between ripening and location within cheese blocks. Time of day of manufacture significantly affected mean cheese calcium levels at 7 days post manufacture and mean levels of arginine and mean viable counts of NSLAB. Cheeses produced during the middle of the production day had the best grading scores and were more consistent compared to cheeses produced early or late during day of manufacture. Cheeses with low levels of S/M and low values of resilience were associated with poor grades at 7 days post manufacture. Chesses which had high elastic index values and low values of springiness in the external areas after exit from hot-room ripening also obtained good commercial grades. Development of a pink colour defect is an intermittent defect in ripened cheese which may or may not contain an added colourant, e.g., annatto. Factors associated with the defect were reviewed. Attempts at extraction and identification of the pink discolouration were unsuccessful. The pink colour partitioned with the water insoluble protein fraction. No significant difference was observed between ripened control and defect cheese for oxygen levels and redox potential or for the results of elemental analysis. A possible relationship between starter activity and defect development was established in cheeses with added coulourant, as lower levels of residual galactose and lactose were observed in defective cheese compared to control cheese free of the defect. Swiss-type cheese without added colourant had significantly higher levels of arginine and significantly lower lactate levels. Flow cell cytometry indicated that levels of bacterial cell viability and metabolic state differed between control and defect cheeses (without added colourant). Pyrosequencing analysis of cheese samples with and without the defect detected the previously unreported bacteria in cheese, Deinococcus thermus (a potential carotenoid producer). Defective Swiss-type cheeses had elevated levels of Deinococcus thermus compared to control cheeses, however the direct cause of pink was not linked to this bacterium alone. Overall, research was undertaken on underlying factors associated with the development of specific defects in commercial cheese, but also characterised the dynamic changes in key microbial and physicochemical parameters during cheese ripening and storage. This will enable the development of processing technologies to enable seasonal manipulation of manufacture protocols to minimise compositional and biochemical variability and to reduce and inhibit the occurrence of specific quality defects.