A method for assessing spectroscopic sensor accuracy, includes building an a priori simulation of generalized etalon drift. A spectroscopic sensor is tested to determine use parameters. A specific drift model is generated by applying the determined use parameters to the built a priori simulation of generalized etalon drift. The specific drift model is analyzed to determine whether the spectroscopic sensor is satisfactory.

A spectrometry method used by a spectrometry apparatus including a spectrometry section including a spectrometer and an imaging device that captures a spectroscopic image, a spectroscopic controller that controls the action of the spectrometer, and an image generator that generates the spectroscopic image, the method including generating the spectroscopic image, dividing the range of the spectroscopic image into a plurality of regions including at least a first region, determining a reference value of a color value, generating a first region spectrum based on the spectroscopic image of the first region, calculating first region tristimulus values based on the first region spectrum, calculating a first region color value based on the first region tristimulus values, and calculating a first region color difference that is the color difference between the first region color value and the reference value by using a color difference formula.

Carbon fiber characterization processes are described that include multi-condition Raman spectroscopy-based examination combined with multivariate data analyses. Methods are a nondestructive material characterization approach that can provide predictions as to carbon fiber bulk physical properties, as well as identification of unknown carbon fiber materials for quality control purposes. The framework of the multivariate analysis methods includes a principal component-based identification protocol including comparison of Raman spectral data from an unknown carbon fiber with a data library of multiple principal component spaces.

A system includes a tunable Fabry-Perot etalon, a detector, and a processor. The tunable Fabry-Perot etalon has a settable gap. The detector measures light intensity transmitted through the tunable Fabry-Perot etalon. The processor is configured to determine the calibrated spectral measurement, wherein the calibrated spectral measurement is based at least in part on a measurement set of detected light intensities for a selected set of settable gaps and a reconstruction matrix. The reconstruction matrix is based at least in part on calibration measurements using one or more field material targets, prior stored full calibrations for each of the one or more field material targets, and the selected set of settable gaps.

It is possible to more appropriately perform fluorescence separation. An information processing apparatus according to an embodiment includes: a fluorescence signal acquisition unit (112) that acquires a plurality of fluorescence spectra corresponding to each of a plurality of excitation lights having different wavelengths and irradiated to a fluorescence stained specimen (30), the fluorescence stained specimen (30) being created by staining a specimen (20) with a fluorescence reagent (10); a link unit (131) that generates a linked fluorescence spectrum by linking at least parts of the plurality of fluorescence spectra to each other in a wavelength direction; a separation unit (132) that separates the linked fluorescence spectrum into spectra for every fluorescent substance using a reference spectrum including a linked autofluorescence reference spectrum in which spectra of autofluorescent substances in the specimen are linked to each other in the wavelength direction and a linked fluorescence reference spectrum in which spectra of fluorescent substances in the fluorescence stained specimen are linked to each other in the wavelength direction; and an extraction unit (132) that updates the linked autofluorescence reference spectrum using the spectra for every fluorescent substance separated by the separation unit.

A calibration method includes placing an LED light source having a given wavelength range inside a reference apparatus; acquiring first data as an emission intensity of light at a wavelength, a light amount of the light being adjusted in stages by changing the light amount output from the LED light source; storing the first data in a memory; placing the LED light source in a calibration target apparatus; acquiring second data as an emission intensity of light at a wavelength, a light amount of the light being adjusted in the stages by changing the light amount output from the LED light source; and calculating a calibration formula based on the first data stored in the memory and the second data.

An optical measuring device includes a light measurement unit, an acceleration sensor for detecting the acceleration of the optical measuring device, a storage for storing reference data obtained from the light measurement unit by measuring light from a reference object at a first timing and storing the acceleration detected by the acceleration sensor as history information, a first determination unit for determining whether the result of comparison between measurement data obtained from the light measurement unit by measuring light from the reference object at a second timing later than the first timing and the reference data satisfies a first malfunction condition, a second determination unit for determining whether the acceleration included in the history information satisfies a second malfunction condition, and an output unit for outputting that the optical measuring device malfunctions when the first malfunction condition and the second malfunction condition are satisfied.

A system for performing advanced spectrometry using a camera of a personal electronic device. Light from a sample is captured via a light dispersion device that diffracts the light in accordance with the wavelength of that light. A sample spectrum image is captured using a camera of a personal electronic device. Spectral data is extracted from the sample spectrum image and the spectral data is wavelength calibrated by mapping each pixel position in the sample spectrum image to a wavelength. Features are extracted from the wavelength calibrated spectral data and used by classification module, trained on a dataset of features extracted from spectral data of known samples, to classify the sample. In some embodiments, a calibration spectrum image captured from a calibration light source having a known spectrum (e.g., in the same image frame using a bifurcated fiber optic cable) is used to wavelength calibrate the spectral data.

A device may obtain a master calibration set, associated with a master calibration model of a master instrument, that includes spectra, associated with a set of samples, generated by the master instrument. The device may identify a selected set of master calibrants based on the master calibration set. The device may obtain a selected set of target calibrants that includes spectra, associated with the subset of the set of samples, generated by the target instrument. The device may create a transfer set based on the selected set of master calibrants and the selected set of target calibrants. The device may create a target calibration set, corresponding to the master calibration set, based on the transfer set. The device may generate, using an optimization technique associated with the transfer set and a support vector regression modeling technique, a transferred calibration model, for the target instrument, based on the target calibration set.

A method and apparatus for field spectroscopic characterization of seafood is disclosed. A portable NIR spectrometer is connected to an analyzer configured for performing a multivariate analysis of reflection spectra to determine qualitatively the true identities or quantitatively the freshness of seafood samples.