794 resultados para Optical sensors


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The unique surface-sensitive properties make quantum dots (QDs) great potential in the development of sensors for various analytes. However, quantum dots are not only sensitive to a certain analyte, but also to the surrounding conditions. The controlled response to analyte may be the first step in the designing of functional quantum dots sensors. In this study, taking the quenching effect of benzoquinone (BQ) on CdTe QDs as model, several critical parameters of buffer solution conditions with potential effect on the sensors were investigated. The pH value and the concentration of sodium citrate in the buffer solution critically influenced the quenching effects of BQ.

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Two kinds of polymeric pH indicators PPF (phenolphthalein-formaldehyde product) and CPF (o-cresolphthalein-formaldehyde product) immobilized cross-linked poly(vinyl alcohol) membranes (PPF-PVA and CPF-PVA) for optical intermittent determination of high basicity ([OH-] = 1-8 M) based on a kinetic process were developed. In our previous work, we had demonstrated that PPF-PVA and CPF-PVA could perform the determination of high pH values from pH 10.0 to 14.0. Here the discoloring kinetic behaviors of PPF-PVA and CPF-PVA were compared with those of free phenolphthalein, o-cresolphthalein and thymolphthalein. Experimental results and theoretical analysis indicated that the response behaviors of the optodes' membranes in concentrated NaOH solutions were diffusion-independent and still complied with the pseudo-first-order kinetics. In addition, two data analysis methods for determination were presented. One was directly based on the reduced absorbance: the other was based on the discoloring kinetic constant. It was found that the latter could perform a rapid (60 s) and reliable (relative standard deviation: 2.6%) determination for high basicity.

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The evolution of the optical sensor for CO2 over the past two decades is outlined and illustrated through examples of luminescent-based sensors. The basic principles and design of the early 'wet covered' type sensor, in which a pH sensitive dye in an aqueous buffer is covered by a gas permeable, ion impermeable, membrane, are outlined. The gradual move from the 'wet covered' types of CO2 optical sensor to 'solid-water droplet' type sensors and then onto 'solid' sensors is charted. The basic design and principles of operation of the modern 'solid' optical sensor for P-CO2 is covered in some detail. Other sensing strategies outside the simple use of pH-sensitive dyes are also considered, most notably those based on luminescence lifetime measurements.

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The features of two popular models used to describe the observed response characteristics of typical oxygen optical sensors based on luminescence quenching are examined critically. The models are the 'two-site' and 'Gaussian distribution in natural lifetime, tau(o),' models. These models are used to characterise the response features of typical optical oxygen sensors; features which include: downward curving Stern-Volmer plots and increasingly non-first order luminescence decay kinetics with increasing partial pressures of oxygen, pO(2). Neither model appears able to unite these latter features, let alone the observed disparate array of response features exhibited by the myriad optical oxygen sensors reported in the literature, and still maintain any level of physical plausibility. A model based on a Gaussian distribution in quenching rate constant, k(q), is developed and, although flawed by a limited breadth in distribution, rho, does produce Stern-Volmer plots which would cover the range in curvature seen with real optical oxygen sensors. A new 'log-Gaussian distribution in tau(o) or k(q)' model is introduced which has the advantage over a Gaussian distribution model of placing no limitation on the value of rho. Work on a 'log-Gaussian distribution in tau(o)' model reveals that the Stern-Volmer quenching plots would show little degree in curvature, even at large rho values and the luminescence decays would become increasingly first order with increasing pO(2). In fact, with real optical oxygen sensors, the opposite is observed and thus the model appears of little value. In contrast, a 'log-Gaussian distribution in k(o)' model does produce the trends observed with real optical oxygen sensors; although it is technically restricted in use to those in which the kinetics of luminescence decay are good first order in the absence of oxygen. The latter model gives a good fit to the major response features of sensors which show the latter feature, most notably the [Ru(dpp)(3)(2+)(Ph4B-)(2)] in cellulose optical oxygen sensors. The scope of a log-Gaussian model for further expansion and, therefore, application to optical oxygen sensors, by combining both a log-Gaussian distribution in k(o) with one in tau(o) is briefly discussed.

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The monitoring of water uptake in plants is becoming increasingly important. Optical sensors offer considerable advantages over conventional methods and several sensors have been developed including an optical potometer that monitors water uptake from individual roots, the detection of xylem cavitation using audio acoustic emissions with an interferometric force feedback microphone, and an optical fiber displacement transducer that detects changes in leaf thickness in relation to leaf-water potential.

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The aim of this study was to develop and evaluate a variable dose rate application of herbicides using an online electronic control based system with optical sensors for weed detection in forested areas. The proposed concept was to apply a basic dose on 100% of the area (aiming to control small weeds) and to apply a complementary patch-spraying dose only on areas with higher weed infestation. For that purpose, a conventional spray boom was adjusted to apply 40% of the herbicide dose on the full area and the optical sensors were used to control the application of the complementary dose (60%) only on areas with higher infestation. The results showed that the system performed adequately. Field applications presented herbicide savings around 20 to 30%, with a similar weed control performance as compared to the full dose application on 100% of the area.

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Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

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Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.

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Adjusting N fertilizer application to crop requirements is a key issue to improve fertilizer efficiency, reducing unnecessary input costs to farmers and N environmental impact. Among the multiple soil and crop tests developed, optical sensors that detect crop N nutritional status may have a large potential to adjust N fertilizer recommendation (Samborski et al. 2009). Optical readings are rapid to take and non-destructive, they can be efficiently processed and combined to obtain indexes or indicators of crop status. However, other physiological stress conditions may interfere with the readings and detection of the best crop nutritional status indicators is not always and easy task. Comparison of different equipments and technologies might help to identify strengths and weakness of the application of optical sensors for N fertilizer recommendation. The aim of this study was to evaluate the potential of various ground-level optical sensors and narrow-band indices obtained from airborne hyperspectral images as tools for maize N fertilizer recommendations. Specific objectives were i) to determine which indices could detect differences in maize plants treated with different N fertilizer rates, and ii) to evaluate its ability to identify N-responsive from non-responsive sites.