Hyperspectral imaging as a tool for profiling basidiomycete decay of Pinus sylvestris L.

Given the right climatic and environmental conditions, a range of microorganisms can deteriorate wood. Decay by basidiomycete fungi accounts for significant volumes of wood in service that need to be replaced. In this study, a short-wave infrared hyperspectral camera was used to explore the possibilities of using spectral imaging technology for the fast and non-destructive detection of fungal decay. The study encompassed different degradation stages of Scots pine sapwood (Pinus sylvestris L.) specimens inoculated with monocultures of either a brown rot fungus (Rhodonia placenta Fr.) or a white rot fungus (Trametes versicolor L.). The research questions were if the hyperspectral camera can profile fungal wood decay and whether it also can differentiate between decay mechanisms of brown rot and white rot decay. The data analysis employed Partial Least Squares (PLS) regression with the mass loss percentage as the response variable. For all models, the mass loss could be predicted from the wavelength range 1460–1600 nm, confirming the reduction in cellulose. A single PLS component could describe the mass loss to a high degree (90%). The distinction between decay by brown or white rot fungi was made based on spectral peaks around 1680 and 2240 nm, related to lignin.publishedVersio

LUMIO: achieving autonomous operations for Lunar exploration with a CubeSat

The Lunar Meteoroid Impacts Observer (LUMIO) is one of the four projects selected within ESA’s SysNova competition to develop a small satellite for scientific and technology demonstration purposes to be deployed by a mother ship around the Moon. The mission utilizes a 12U form-factor CubeSat which carries the LUMIO-Cam, an optical instrument capable of detecting light flashes in the visible spectrum to continuously monitor and process the meteoroids impacts. In this paper, we will describe the mission concept and focus on the performance of a novel navigation concept using Moon images taken as byproduct of the LUMIO-Cam operations. This new approach will considerably limit the operations burden on ground, aiming at autonomous orbit-attitude navigation and control. Furthermore, an efficient and autonomous strategy for collection, processing, categorization, and storage of payload data is also described to cope with the limited contact time and downlink bandwidth. Since all communications have to go via a Lunar Orbiter (mothership), all commands and telemetry/data will have to be forwarded to/from the mother ship. This will prevent quasi-real time operations and will be the first time for CubeSats as they have never flown so far from Earth

Hyperspectral imaging as a tool for profiling basidiomycete decay of Pinus sylvestris L.

Given the right climatic and environmental conditions, a range of microorganisms can deteriorate wood. Decay by basidiomycete fungi accounts for significant volumes of wood in service that need to be replaced. In this study, a short-wave infrared hyperspectral camera was used to explore the possibilities of using spectral imaging technology for the fast and non-destructive detection of fungal decay. The study encompassed different degradation stages of Scots pine sapwood (Pinus sylvestris L.) specimens inoculated with monocultures of either a brown rot fungus (Rhodonia placenta Fr.) or a white rot fungus (Trametes versicolor L.). The research questions were if the hyperspectral camera can profile fungal wood decay and whether it also can differentiate between decay mechanisms of brown rot and white rot decay. The data analysis employed Partial Least Squares (PLS) regression with the mass loss percentage as the response variable. For all models, the mass loss could be predicted from the wavelength range 1460–1600 nm, confirming the reduction in cellulose. A single PLS component could describe the mass loss to a high degree (90%). The distinction between decay by brown or white rot fungi was made based on spectral peaks around 1680 and 2240 nm, related to lignin

Hyperspectral imaging as a tool for profiling basidiomycete decay of Pinus sylvestris L.

Given the right climatic and environmental conditions, a range of microorganisms can deteriorate wood. Decay by basidiomycete fungi accounts for significant volumes of wood in service that need to be replaced. In this study, a short-wave infrared hyperspectral camera was used to explore the possibilities of using spectral imaging technology for the fast and non-destructive detection of fungal decay. The study encompassed different degradation stages of Scots pine sapwood (Pinus sylvestris L.) specimens inoculated with monocultures of either a brown rot fungus (Rhodonia placenta Fr.) or a white rot fungus (Trametes versicolor L.). The research questions were if the hyperspectral camera can profile fungal wood decay and whether it also can differentiate between decay mechanisms of brown rot and white rot decay. The data analysis employed Partial Least Squares (PLS) regression with the mass loss percentage as the response variable. For all models, the mass loss could be predicted from the wavelength range 1460–1600 nm, confirming the reduction in cellulose. A single PLS component could describe the mass loss to a high degree (90%). The distinction between decay by brown or white rot fungi was made based on spectral peaks around 1680 and 2240 nm, related to lignin

Hyperspectral imaging as a tool for profiling basidiomycete decay of Pinus sylvestris L.

Given the right climatic and environmental conditions, a range of microorganisms can deteriorate wood. Decay by basidiomycete fungi accounts for significant volumes of wood in service that need to be replaced. In this study, a short-wave infrared hyperspectral camera was used to explore the possibilities of using spectral imaging technology for the fast and non-destructive detection of fungal decay. The study encompassed different degradation stages of Scots pine sapwood (Pinus sylvestris L.) specimens inoculated with monocultures of either a brown rot fungus (Rhodonia placenta Fr.) or a white rot fungus (Trametes versicolor L.). The research questions were if the hyperspectral camera can profile fungal wood decay and whether it also can differentiate between decay mechanisms of brown rot and white rot decay. The data analysis employed Partial Least Squares (PLS) regression with the mass loss percentage as the response variable. For all models, the mass loss could be predicted from the wavelength range 1460–1600 nm, confirming the reduction in cellulose. A single PLS component could describe the mass loss to a high degree (90%). The distinction between decay by brown or white rot fungi was made based on spectral peaks around 1680 and 2240 nm, related to lignin