An optical system for imaging. The optical system includes light emitting diodes to provide light of predetermined wavelengths. The optical system further includes a charge-coupled device to receive the light emitted by one or more light emitting diodes and reflected by an object for fluorescence imaging of the object. The optical system additionally includes a broadband light source to provide broadband light. Furthermore, the optical system includes a spectrometer to receive the broadband light emitted by the broadband light source and reflected by the object for visible-near infrared-shortwave infrared spectroscopy of the object. Additionally, the optical system includes a hyperspectral camera to receive the broadband light emitted by the broadband light source and reflected by the object for hyperspectral imaging of the object as well as a controller coupled to the light emitting diodes, the broadband light source, the charge-coupled device, the spectrometer and the hyperspectral camera.

A device consisting of a digital camera with a microscope objective lens, a disc where plant material can be mounted and automatically rotated, and two other cameras for determining the plant material's shape and size, that allows images of intact cannabis trichomes to be taken, without destruction or damage to the plant material, and automatically counts and calculates the density of the trichomes on the inflorescence surface. This does not require taking any plant cuttings, does not require the use of a microscope or microscope slides, and allows multiple measurements to be taken of a single inflorescence sample in quick succession, without the need for manual image analysis.

Certain disclosed method embodiments concern performing a stalk puncture test to determine force and displacement data. Plant features, such as rind thickness, stalk radius, stalk diameter, section modulus and/or integrative puncture score, primarily applicable to corn, sorghum, sunflower, wheat or rice, can be calculated using the force and displacement data. The calculated plant features are used to select plants for selective breeding to produce lodging-resistant crop hybrids. The present invention also provides embodiments of a hand-held puncture device that can be used to practice disclosed method embodiments.

A farming machine is configured to identify and treat plants in a field. The farming machine includes one or more light sensors for measuring a characteristic of light. The one or more light sensors are coupled to the farming machine and are directed a substantially upwards orientation away from the plants. A control system adjusts settings of an image acquisition system based on a characteristic of light measured by the one or more light sensors. The image acquisition system captures an image of a plant using one or more image sensors coupled to the farming machine, the one or more image sensors directed in a substantially downwards orientation towards the plants. The control system identifies a plant in the image and actuates a treatment mechanism to treat the identified plant.

One variation of a method includes accessing an image of a plant canopy in an environment inhabited by: a population of microbe sensors of a microbe type including a microbe promoter-reporter pair configured to generate microbe-reporter signals representing presence of a stressor in the environment; and a set of sensor plants of a sensor plant type including a plant promoter-reporter pair configured to signal presence of microbe-reporter signals at the set of sensor plants. The method further includes: accessing a reporter model linking features extracted from images of sensor plants of the sensor plant type to pressures of the set of stressors based on plant-reporter signals generated by the plant promoter-reporter pair and microbe types of microbe sensors inhabiting the environment; and interpreting a pressure of the stressor in the environment based on the reporter model, the microbe type, and features extracted from the image.

An inspection system is presented for use in monitoring plants' conditions in a plant growing area. The inspection system comprises: an optical probe comprising at least one imaging set, each imaging set comprising: a flash illuminator unit; an imaging unit configured with a predetermined resolution; and a sensing unit; the optical probe being configured and operable to perform one or more imaging sessions on a target in a plant growing area at a target location during a movement of the optical probe along a movement path in a vicinity of the target location, said sensing unit comprising a distance sensing element configured and operable to determine an instantaneous distance between the imaging unit and the target being imaged, and generate distance sensing data indicative thereof; and a control unit configured and operable to be responsive to the distance sensing data to initiate the imaging session and synchronize operation of the flash illuminator unit and the imaging unit to capture images of the target by the optical probe, thereby enabling analyzing the images and determining a condition of the target being indicative of at least one of pest, insect and disease presence at the target.

The invention relates to a device for crumbling root crops into substantially equal sized pieces, comprising: a main frame having an inlet side and an outlet side; a root crop supply at the inlet side; at least one crumbling shaft rotatable supported in the main frame, the crumbling shaft being provided with a plurality of curved hooks, which are curved into a direction of rotation of the crumbling shaft; and a non-rotating cutting rake having a plurality of protrusions and recesses and forming a counter blade for the hooks, wherein the hooks are arranged for interlaced movement with said recesses of the non-rotating rake. The invention moreover concerns a system and a corresponding method.

Various embodiments are disclosed for a machine learning system for automatic genotype selection and performance evaluation using multi-source and spatiotemporal remote sensing data collected from an unmanned aerial system (UAS). A computing device may be configured to access images of a field having a first genotype and a second genotype of at least one crop or plant planted therein. The computing device may apply an image processing routine to the images to analyze the images of the field and determine characteristics of the first genotype and the second genotype of the at least one crop or plant planted in the field. The computing device may then apply a machine learning routine to forecast a first estimated yield of the first genotype and a second estimated yield of the second genotype using the identified characteristics of the first genotype and the second genotype.

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.

A portable apparatus for analyzing a plant specimen. A housing assembly defines a sensing volume and controls entry of ambient light into the sensing volume when the housing is closed. A specimen support positions a plant specimen within the sensing volume whereby light emitted from at least one light emitter is incident upon the plant specimen. An image sensor senses light from the at least one light emitter that has been incident on the plant specimen. A processor analyzes data obtained from the light sensor to assess one or more properties of the plant specimen. There may be more than one light emitter, e.g., a halogen lamp and LED array, and the apparatus may acquire images under more than one lighting condition. The apparatus may include a mechanism for moving the plant specimen relative to the optical path to take images at multiple regions of interest on the specimen.