A method comprising: receiving, as input, a plurality of spectral data samples, wherein each of the spectral data samples represents spectral reflectance from a plant; at a training stage, training a machine learning model on a training set comprising: (i) the spectral data samples, and (ii) labels associated with stomatal conductance in each of the plants; and at an inference stage, applying the machine learning model to a target spectral data sample associated with a target plant, to predict a stomatal conductance value for the target plant.

A method is provided for hyperspectral inversion of a phosphorus content of rubber tree leaves. The method includes: acquiring hyperspectral data of to-be-detected rubber tree leaves; extracting key wavelengths of the rubber tree leaves according to the hyperspectral data and a pre-established wavelength extraction model, where the key wavelengths are related to the phosphorus content of the rubber tree leaves, and the pre-established wavelength extraction model is obtained by learning and training hyperspectral sample data and sample phosphorus content data pairs in a pre-established sample database by adopting a competitive adaptive reweighted sampling (CARS) algorithm and a successive projection algorithm (SPA); and inputting the key wavelengths into a pre-established phosphorus content prediction model to calculate the phosphorus content of the to-be-detected rubber tree leaves. Moreover, the CARS algorithm and the SPA are comprehensively applied to extract the key wavelengths closely related to the phosphorus content of the rubber tree leaves.

An inspection unit for performing an optical inspection on a grain to be transferred by transfer means includes a visible light source, a near-infrared light source, a visible light detection unit, and a near-infrared light detection unit. A determination unit plots wavelength components of red (R), green (G), and blue (B), and a near-infrared light component in a three-dimensional space, to create a three-dimensional optical correlation diagram, for a plurality of good product samples and defective product samples, and sets a threshold value, in which: the wavelength components are detected by the visible light detection unit; and the near-infrared light component is detected by the near-infrared light detection unit.

Provided are an image processing apparatus, an image processing method, and an image processing program capable of achieving high accuracy in an index representing vegetation. An image processing apparatus (1) includes a normal map generation unit (12) and a reflection characteristic model generation unit (18). The normal map generation unit (12) obtains a normal vector characteristic based on a polarized image acquired. The reflection characteristic model generation unit (18) estimates a reflection characteristic model based on the normal vector characteristic obtained by the normal map generation unit (12).

A method of measuring element concentration in plant leaves comprises steps of: (a) gathering leaves of plants to be tested; (b) conditioning specimens of said leaves; (c) obtaining raw count-per-second XRF datasets of said specimens; (d) obtaining raw NIR datasets of said specimens; (e) obtaining raw analytical datasets; and (f) assessing concentrations of minerals within said specimens on the basis of said count-per-second XRF, NIR and analytical datasets. The aforesaid method further comprises steps of obtaining white reference radiance datasets and normalizing said raw NIR datasets on the basis thereof and providing NIR reflectance datasets.

A bale monitoring system includes an imaging device that is operable to capture a stereoscopic image of a bale. A computing compares the stereoscopic image of the bale to a three-dimensional standard to identify a deviation of the bale from the three-dimensional standard. The computing device may then assign the bale a shape quality score based on the deviation of the bale from the three-dimensional standard. The shape quality score may indicate a magnitude of the deviation of the bale from the three-dimensional standard. Additionally, the stereoscopic image may be analyzed to identify characteristics of the bale, such as a broken wrap material or an improperly formed bale.

A system for managing ripeness of perishable goods including: a storage device to store perishable good requirements, ripening capability parameters, ripening schedules, and perishable good parameters associated with the perishable goods; and a ripeness management system coupled to the storage device. The ripeness management system including: a current ripeness determination module to determine current ripeness levels in response to at least one of the perishable good parameters, the perishable good requirements, and the ripening schedules; a ripeness schedule module to determine predicted ripeness levels in response to at least one of the current ripeness levels, the ripening capability parameters, and the ripening schedules; and a meshing module to determine ripening schedule adjustments in response to at least one of the current ripeness levels, the perishable good parameters, the ripening schedules, and the ripening capability parameters.

A high-power-microscope-assisted identification method of maize haploid plants is provided, the method is implemented by a device including a high power microscope, a main frame disposed on an objective table of the high power microscope and a computer and includes four procedures of sample information input, automatic testing of a batch of samples, automatic analysis and comparison, and automatic generation of data results. Vertical sliding grooves are symmetrically formed in the main frame, and a vertical supporting plate is disposed at an upper end of the main frame. Horizontal sliding grooves are symmetrically formed in the vertical supporting plate, and a horizontal supporting plate is disposed on the vertical supporting plate.

A sensor apparatus for detecting constituents of a material, the apparatus comprising: a first sensor, which interacts with the material, configured to measure an optical spectrum of the material and is coupled to an evaluation device that is configured to output an output value relating to the level of the one or more constituents in the material with the aid of the measured spectrum and calibration data; a second sensor configured to analyse the material examined by the first sensor and to output a signal relating to the level of the one or more constituents in the material; and a calibration data generating device configured to generate the calibration data for the evaluation device with the aid of the signal of the second sensor.

A method and system are disclosed for providing consistent images of leaves of plants, including articulating a lower case of a housing with respect to an upper case via an imaging chamber articulation mechanism from i) a closed state to ii) an open state, the articulable space forms an imaging chamber which is dark when the imaging chamber articulation mechanism is in the closed state, placing the leaf within the imaging chamber, articulating the imaging chamber articulation mechanism to the closed state, activating one or more light sources, actuating a linear actuator to thereby linearly move a camera from i) an initial position to ii) an end position, obtaining images from the camera, re-actuating the linear actuator to thereby linearly move the camera from the end position to the initial position, re-articulating the lower case to the open state, and removing the leaf.