Methods of deep ultraviolet fluorescence (DUVF) and multi spectral imaging (MSI) detection are disclosed herein for the detection and identification of pathogens on plants. DUV light and visible or near-infrared light are used to illuminate plants or plant leaves such that the light intensity reflected or emitted by the plant or plant leaves can be used to identify the type of pathogen and measure the amount of pathogen on the plant or plant leaves and, additionally, be used to measure the plant's stress response to such pathogen. Also provided herein is a biophotonic analyzer device that uses both DUVF and MSI detection for the monitoring and surveillance of plant health and for the identification and enumeration of pathogens on plants or plant leaves.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

An apparatus for analyzing a plant specimen is disclosed which includes a housing assembly adapted to be in i) an open configuration adapted to receive a plant specimen, and ii) a closed configuration wherein ambient light is controlled therein, a light source disposed in or coupled to the housing assembly, the light source adapted to shine light onto or through the plant specimen when the housing assembly is in the closed configuration, and a camera assembly coupled to the housing assembly, the camera assembly having an image sensor adapted to receive light from the plant specimen in i) a transmittance mode where light transmits through the plant specimen, or ii) a reflectance mode where light is reflected from the plant specimen, the image sensor adapted to thereby capture hyperspectral images of the plant specimen.

The present disclosure relates to methods and systems for obtaining image information of an organism including a set of optical data; calculating a growth index based on the set of optical data; and calculating an anticipated harvest time based on the growth index, where the image information includes at least one of: (a) visible image data obtained from an image sensor and non-visible image data obtained from the image sensor, and (b) a set of image data from at least two image capture devices, where the at least two image capture devices capture the set of image data from at least two positions.

A plant cultivation method includes the steps of: applying supplementary light treatment to a selected plant with UVA, measuring a maximum quantum yield of the selected plant; and determining a cultivation step of the plant according to the measured maximum quantum yield.

A method of harvesting plant product from a plant in a single pass using a combine harvester is disclosed. In the method, the plant has a protein content gradient that varies along a height of the plant. The method includes identifying, along a longitudinally-extending stalk of the plant, an upper protein gradient of the plant including high protein plant product and a lower protein gradient of the plant including lower protein plant product, wherein the high protein plant product from the upper protein gradient of the plant meets a threshold protein content that is higher than that of the lower protein plant product. The method also includes separately and substantially simultaneously harvesting the high protein plant product from the upper protein gradient and the lower protein plant product from the lower protein gradient in the single pass, and isolating the high protein plant product from the lower protein plant product.

A prediction server includes: a data save unit that acquires diagnosis data from a diagnosis server; a training unit that constructs a prediction model that predicts a possibility of occurrence of the disorder in an arbitrary area and on an arbitrary date by training a learning model about a correlation among an area indicated by first position information, a date indicated by a diagnosis date, and a type of disorder in a machine learning manner, in which the type of the disorder is a diagnosis result estimated by the diagnosis server based on a diseased portion image by using a diagnosis model trained about a correlation between the diseased portion image and the disorder in the machine learning manner.

The present invention relates to a method for in situ sensing of water stress in a plant by contacting a plant with a biosensor, where the biosensor comprises a material capable of giving a detectable response to changes in local water potential in the plant and detecting the detectable response thereby sensing water stress in the plant. The invention further relates to a method for determining water potential in a substance, a biosensor, a system for determining water potential in a substance, a method for determining water potential in a substance, a water potential measurement computing device, and a non-transitory computer readable medium having stored thereon instructions for determining water potential in a substance.

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.

An approach to remotely and noninvasively detect and evaluate the response of a plant or plant population to a man-made or natural treatment regime (e.g., herbicide, fungicide or fertilizer treatment) via spectral imaging methods and systems comprising the capture of a plurality of spectral images for a common plant scene, each associated with a selected wavelength region of the electromagnetic spectrum, the formulation of an index function from the spectral information indicative of the plant response over time, and the assessment of mathematical parameters quantifying the time-varying plant response to the treatment regime. The plant response to a treatment regime may be quantified in illustrative embodiments in a fraction of the time previously required by many conventional approaches. Applying varying herbicide dosages to segments of the same plant population enables easy determination of a dose-response curve.