The present disclosure relates to an inspection apparatus, a sensing apparatus, a sensitivity control apparatus, an inspection method, and a program that perform inspection with improved accuracy. The inspection apparatus includes a detection section for detecting a plurality of different wavelength region components of ambient light reflected from an inspection target to be inspected, and a control section for controlling the sensitivity of each of the different wavelength region components. The control section controls the sensitivity by calculating a histogram indicating the detection level in every wavelength region of light reflected from the inspection target that is detected by the detection section, and determining, based on histograms of particular spectroscopic components, whether or not the sensitivity is properly set for the detection section. The present technology is applicable, for example, to an inspection apparatus that inspects vegetation.

Apparatus (100) for determining presence of a gas (103) is provided, the apparatus (100) comprising: one or more retarders (109) to spectrally modulate polarisation of received radiation in accordance with a plurality of polarised spectral modulation profiles which are offset in phase from each other, the radiation output from the one or more retarders (109) comprising radiation having polarisation spectrally modulated in accordance with the said plurality of polarised spectral modulation profiles in a common beam of radiation; one or more polarisers (147, 148); and radiation detectors (142, 144) to detect radiation output from the one or more retarders (109) filtered for respective polarisation states by the one or more polarisers (147, 148), the detectors (142, 144) selectively and separately detecting on different detectors at the same time polarised radiation conforming to each of at least first and second of the said polarised spectral modulation profiles to thereby provide at least respective first and second polarisation-dependent radiation intensity measurements from which the presence of the gas (103) can be determined.

A method for determining a quality condition of an agricultural product comprises: receiving a received light at a light detector, the received light comprising reflected, scattered, refracted, and/or deflected light from the agricultural product; transmitting the received light to a spectrometer; producing agricultural product (AP) spectral data of the received light using the spectrometer; with a computer in electrical communication with the spectrometer, comparing the AP spectral data to reference spectral data to determine whether the agricultural product has the quality condition, the reference spectral data corresponding to known quality conditions of the agricultural product; and with the computer, generating an output signal corresponding to the quality condition of the agricultural product.

A method for determining national crop yields during the growing season is provided. In an embodiment, a server computer system receives agricultural data records for a particular year that represent covariate data values related to plants at a specific geo-location at a specific time. The system aggregates the records to create geo-specific time series for a geo-location over a specified time. The system creates aggregated time series from a subset of the geo-specific time series. The system selects a representative feature from the aggregated time series and creates a covariate matrix for each specific geographic area in computer memory. The system determines a specific state crop yield for a specific year using linear regression to calculate the specific state crop yield from the covariate matrix. The system determines a national crop yield for the specific year using the sum of the state crop yields for the specific year nationally adjusted.

A chlorophyll fluorescence measuring system having at least one spectrometer coupled to a data logger. The data logger provides direct control of the spectrometer and includes on-board memory for storage of target and reference spectrum data obtained by the spectrometer. The data logger may be coupled to an external computer that receives and analyzes target and reference spectrum data to determine SIF using a spectral fitting algorithm. The system may include a spectrometer aiming system coupled to and controlled by the data logger. The system may also include one or more environmental sensors configured to measure environment variables. The environmental sensors may be coupled to the data logger for control and data storage. The environmental data may be communicated to the external computer for use in the spectral fitting algorithm. The data logger may be connected to a network for remote monitoring and control.

An image processing method includes acquiring an image obtained by imaging of an object, ambient light data during the imaging, and reflection characteristic data and transmission characteristic data which depend on a concentration of a material contained in the object, and separating a reflected light component and a transmitting light component in the image using the ambient light data, the reflection characteristic data, and the transmission characteristic data.

An object state detection and transmission system includes a spectrometer configured to measure a reflectance spectrum based on reflected light reflected by a target object, a spectroscopic terminal apparatus integrally provided with an electronic device, the spectroscopic terminal apparatus being configured to receive a measured reflection spectrum; and a server apparatus connected to the spectroscopic terminal apparatus via a communication line. The electronic device includes a photographic camera configured to photograph the target object to capture a photographed image; a Global Positioning System (GPS) communication unit configured to measure a position of the target object; a sensor configured to measure an azimuth and an angle of the target object; a Central Processing Unit (CPU) configured to clock a current time of the photographing and the measurement; and a wireless communication unit configured to transmit resultant data to the server apparatus.

A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

A spectral imaging system configured to obtain spectral measurements in a plurality of spectral regions is described herein. The spectral imaging system comprises at least one optical detecting unit having a spectral response corresponding to a plurality of absorption peaks of a target chemical species. In an embodiment, the optical detecting unit may comprise an optical detector array, and one or more optical filters configured to selectively pass light in a spectral range, wherein a convolution of the responsivity of the optical detector array and the transmission spectrum of the one or more optical filters has a first peak in mid-wave infrared spectral region between 3-4 microns corresponding to a first absorption peak of methane and a second peak in a long-wave infrared spectral region between 6-8 microns corresponding to a second absorption peak of methane.

A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.