We report on a computational technique that recovers Raman peaks embedded in highly fluorescent contaminated spectra. The method uses a second derivative technique to identify the most intense Raman peak, and a modified Savisty Golay algorithm to filter and recover the embedded Raman peaks iteratively. This technique is an improvement on existing background removal algorithms in both performance and user objectivity.
Rapid urbanization and its associated pollution can affect water quality in mosquito breeding habitats and, as a result, the ecology and control of mosquito vectors. To understand the effects of pollution on mosquito vectors, an accurate assessment of water quality in breeding habitats is needed. Presently, water quality assessment of mosquito breeding habitats is usually based on the measurement of individual physicochemical parameters. However, several parameters are sometimes difficult to interpret or may not give a clear picture of the overall water quality of the breeding habitats, especially when the pollutants are in complex mixtures. This study employed the use of Laser-Induced Fluorescence (LIF) spectroscopy to assess water quality in breeding habitats of Anopheles, Aedes, and Culex mosquitoes in urban areas in Cape Coast, Ghana. The LIF spectra, using a 445-nm diode laser, were measured from field-collected water samples in the laboratory. The LIF spectra showed the presence of dissolved organic matter (DOM) and chlorophyll in the breeding habitats. The DOM and chlorophyll fluorescence signals were normalised by the Raman vibrational signals to determine water quality in each habitat. The overall water quality was better in Aedes breeding habitats than in Anopheles and Culex breeding habitats. The poor water quality in Anopheles and Culex breeding habitats was due to the presence of high fulvic acid and chlorophyll content, which often reflect pollutants from anthropogenic sources. Anopheles and Aedes habitats were made up of mainly An. coluzzii and Ae. aegypti respectively while Culex species were identified to genus level. The results add up to the growing concern about the breeding of Anopheles in polluted habitats. The study demonstrated for the first time the ability of LIF spectroscopy to assess water quality in mosquito breeding habitats.
Well-water contaminated by microbial bacteria has been purified using LEDs radiating in the ultra-violet and visible spectral regions. The contaminated water sample was exposed to the LEDs in specially constructed chambers and the purification process carried on for 3 days. The efficiency of the process was determined using a 445 nm diode laser to induce fluorescence (LIF) and the monitoring of coliform bacteria count (Total coliform, Fecal coliform and Escherichia coli) as well as Total Heterotrophic Bacteria (THB). The LIF peak fluorescence intensities at 526 nm (Raman water peak) and dissolved organic matter fluorescence intensity at 550 nm were determined. Using the fluorescence intensity of purified drinking water as reference, a fluorescence intensity ratio was calculated. A decrease in this ratio with time, at the two wavelengths indicated a proof of purification. Using the values of the slopes, the red and green LEDs proved most efficient while the UV was the least. From the counts of coliform bacteria and THB, the light sources registered zero after the first day of purification, but counts were recorded thereafter for some of the bacterial for some light sources. This may be attributable to bio-films formation on internal surfaces of the purification chamber due to excessive temperatures. A reduction in fluorescence intensity observed in the sample stored in dark environment could be attributed to the stationary and logarithmicdecline phases of the growth curve of bacterial population. This purification technique is inexpensive and can easily be adapted for domestic water purification for reducing waterborne bacteria.
Shelf life of bottled natural fruit juice (BNFJ) provides relevant information on quality and authenticity for consumer protection. However, existing techniques for monitoring the shelf life of BNFJ are destructive and time-consuming. We report on using laser-induced autofluorescence (LIAF) spectroscopic technique in combination with multivariate analysis for shelf life monitoring of BNFJ. The LIAF spectra data were acquired for nine (9) continuous days on three batches of BNFJ samples purchased from a certified retailer. Deconvolution of the LIAF spectra revealed underlying peaks representing constituents of the BNFJ. Principal component analysis (PCA) was able to monitor the trend in the changes of the BNFJ as it aged. Partial least square regression (PLSR) predicted the exact day from the production of the BNFJ accurately at 96.6% and 98.8% in the training and testing sets, respectively. We, therefore, propose the LIAF combined with multivariate analysis as a potential tool for nondestructive, rapid, and relatively inexpensive monitoring of the shelf life of BNFJ.
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