Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < < 0.96, < 0.001). When all the indices formulated as A/B, A/(A + B) or (A - B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < < 0.98, < 0.001). Comparison of near-infrared/red index to chlorophyll concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, 0.97, < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.
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http://dx.doi.org/10.3390/plants10020341 | DOI Listing |
J Clin Med
December 2024
Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia in Katowice, 10 Jednosci Street, 41-208 Sosnowiec, Poland.
The techniques of choice used in the treatment of extensive vascular lesions of the face are methods based on high-energy light sources, such as lasers and IPL (intense pulsed light). The techniques commonly employed to detect blood vessel abnormalities in skin primarily rely on semi-quantitative or qualitative scales. The study was conducted on a group of 38 volunteers; a series of three treatments was performed using an IPL source (Lumecca, Inmode, Israel).
View Article and Find Full Text PDFACS Sens
December 2024
Department of Physics, Dongguk university, Seoul 04620, Republic of Korea.
The mantis shrimp is recognized to have one of the most powerful vision systems in nature, with up to 16 color-perceiving channels and the perception of linear and circular polarization detection. Inspired by its biostructure, we developed a snapshot polarization-hyperspectral camera (pHScam) to detect linear polarization in four directions and spectral signature in 21 bands of incident light, resulting in a 4D polar-spectral hypercube, represented as (,,,→). We introduced two bio-mimetic encoding mechanisms, viz.
View Article and Find Full Text PDFComput Biol Med
December 2024
Carol Davila University of Medicine and Pharmacy, Blvd Eroii Sanitari 8, Bucharest, Romania.
The diagnosis of melanoma traditionally relies on visual inspection or on the use of the dermoscope, which do not have capabilities for early and precise detection. In this review, we aimed to explore other imaging technologies that can provide non-invasive and detailed information on skin lesions, such as multispectral, hyperspectral and thermal imaging. In this regard, the systems were evaluated in terms of hardware, performance and clinical applications.
View Article and Find Full Text PDFSensors (Basel)
December 2024
RLP AgroScience, 67435 Neustadt an der Weinstrasse, Germany.
Apple proliferation is among the most important diseases in European fruit production. Early and reliable detection enables farmers to respond appropriately and to prevent further spreading of the disease. Traditional phenotyping approaches by human observers consider multiple symptoms, but these are difficult to measure automatically in the field.
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