There is provided a spectroscopy apparatus for measuring fluorescence signals from a photosynthetic object. The spectroscopy apparatus comprises: one or more light excitation sources (26,28) operable to carry out time-varying excitation of the fluorescence from the photosynthetic object; and one or more fluorescence-sensitive detection channels (36,38,44,46) configured to simultaneously record the fluorescence as a function of time with a microsecond to millisecond time resolution and as a function of wavelength with a wavelength resolution of 10 nm or better, responsive to the excitation of the fluorescence from the photosynthetic object by the or each light excitation source (26,28).

A method and system for detecting Fusarium moniliforme species of rice seeds are provided, relating to the field of rapid quality detection of rice seeds. The method includes: inputting a hyperspectral image of to-be-tested rice seeds to a model for detecting Fusarium moniliforme species of rice seed, to determine a test result of the rice seeds, where the test result is no Fusarium moniliforme or a Fusarium species. The model for detecting Fusarium moniliforme species of rice seed is determined based on activated wavelengths and an original deep convolutional neural network; the activated wavelengths are wavelengths activated by a trained deep convolutional neural network upon correct classification; and the trained deep convolutional neural network is a neural network obtained by training the original deep convolutional neural network based on the training set.

High-throughput hyperspectral imaging systems are provided. According to an aspect of the invention, a system includes an excitation light source; an objective that is configured to image excitation light onto the sample, such that the excitation light causes the sample to emit fluorescence light; a channel separator that is configured to separate the fluorescence light into a plurality of spatially dispersed spectral channels; and a sensor. The excitation light source includes a light source and a plurality of lenslet arrays. Each of the lenslet arrays is configured to receive light from the light source and to generate a pattern of light, and the patterns of light generated by the lenslet arrays are combined to form the excitation light. The objective is configured to simultaneously image each of the patterns of light to form a plurality of parallel lines or an array of circular spots at different depths of the sample.

Methods and apparatus for rapid, culture free pathogen detection. The methods utilize optical spectroscopy techniques to identify and/or characterize pathogens in a sample via the detection of unique properties and/or analytes that are specific to particular pathogens.

An apparatus (100) for optically characterizing a textile sample (106) comprises a presentation subsystem (102) comprising a viewing window (108). A radiation subsystem (114) comprises a radiation source (120) for directing a first, ultraviolet radiation (122) and a second, visible radiation (123) toward the sample (106), and causing the sample (106) to produce a fluorescent radiation (124) and a reflected radiation (125). A sensing subsystem (126) comprises an imager (130) for capturing the fluorescent radiation (124) and the reflected radiation (125) in an array of pixels (408). A control subsystem (132) comprises a processor (136) for controlling the presentation subsystem (102), the radiation subsystem (114), and the sensing subsystem (126), and for creating a fluorescent and reflected radiation image (400) containing both spectral information and spatial information in regard to the fluorescent radiation (124) and the reflected radiation (125).

A spectroscopic analysis apparatus, a spectroscopic analysis method, and a program capable of appropriately analyzing a sample are provided. The spectroscopic analysis apparatus according to an embodiment includes: a light source (13) generates light to be incident on a sample including a plurality of substances labeled by a plurality of labeled substances; a spectrometer (14) disperse observed light generated in the sample by the light incident on the sample; a detector (15) detects the observed light dispersed by the spectrometer (14) to output observed spectral data; and a processor (16) analyzes the plurality of substances included in the sample based on the observed spectral data output from the detector (15), the processor (16) analyzing the substances included in the sample using a generalized inverse of a matrix having, as elements, reference spectral data set for the plurality of labeled substances and data of a noise component.

A method for determining a property of an object is disclosed, which includes: recording a first image of the object from a first direction; recording a second image of the object from a second direction; determining a first position in the first image, the first position representing a location of the object, and a second position in the second image, the second position representing the same location of the object, for a multiplicity of locations of the object; and calculating a value of an object property for each of the multiplicity of locations of the object. The value assigned to a location of the multiplicity of locations of the object is calculated using an intensity value at the first position, which represents the location, in the first image and an intensity value at the second position, which represents the location, in the second image.

Systems and methods for determining properties of gemstones based, inter alia, on fluorescence properties of the gemstones, are presented. In one aspect, properties of at least one gemstone can be determined. In another aspect, a relationship between at least two gemstones can be determined. In one example, a first and a second gemstones are illuminated with illuminating light of at least one fluorescence-exciting wavelength range; corresponding at least one first fluorescence-emission light and at least one second fluorescence-emission light spectrum, emitted from the first and second gemstones respectively are detected and analyzed, either independently or by comparison, to determine the relationship between the first and second gemstones. In some examples, data indicative of visible light absorbance or three-dimensional models of the gemstones is combined with the fluorescence data to determine the properties or the relationship.

Methods, apparatus, and systems provide improved identification of selected biohazard and/or biohazard signatures from complex in vivo or in vitro samples and include deep UV native fluorescence spectroscopic analysis for multiple locations of a sample wherein classification results for individual locations are combined and spatially correlated to provide a positive or negative conclusion of biohazard signature presence (e.g., for signatures for viruses, bacteria, and diseases including SARS-CoV-2 and its variants and COVID-19 and its variants). Improvements include one or more of reduced sample processing time (minutes to fractions of a minute), reduced sampling cost (dollars to fractions of a dollar), high conclusion reliability (rivaling real time RT-PCR). Some embodiments may incorporate a stage or scanning mirror system to provide movement of a sample relative to an excitation exposure location. Some embodiments may incorporate Raman or phosphorescence spectroscopic analysis as well as imaging systems.

Systems and methods include a fluorescence measurement apparatus. A single-wavelength light source generates an excitation light source. A sample holder holds a sample and includes a surface transparent to the excitation light source. Mounts attached to the single-wavelength light source(s) or the sample holder change an incident angle of the excitation light source on the surface. Optical components positioned in a path of a fluorescence emission emitted from the surface guide the fluorescence emission to a detector that obtains spectra from at least first and second angles-of-incidence. A device records spectra obtained by the detector from the first and second angles-of-incidence, normalizes and analyzes intensities of the spectra, subtracts a first spectrum corresponding to the first angle-of-incidence from a second spectrum corresponding to the second angle-of-incidence to obtain a difference, identifying a sample type of the sample based on an API gravity mapped to the difference.