1142results about "Investigation of vegetal material" patented technology

An apparatus is described for assessing plant status using biophysical and biochemical properties of the plant remotely sensed by the invention thereby allowing selective monitoring, elimination or treatment of individual plants. In a preferred embodiment, a single polychromatic emitter provides coincident light beams; one beam substantially in the visible portion of the spectrum (400 nm to 700 nm) and the other in the near infrared (NIR) portion of the spectrum (700 nm to 1100 nm). This light beam illuminates a small surface area on the ground, which may be bare ground, desired plants or undesired weeds. The beam of light may be focused, collimated or non-focused. A detector array, usually composed of a visible detector and a NIR detector, detects portions of this polychromatic light beam reflected by the surface area and provides a signal indicative of whether the detected light was reflected by a plant or by some non-plant object such as soil. A controller analyzes this signal and, assuming a plant is detected, responds by activating a device to take some action with respect to the plant or stores the analyzed signal with corresponding DGPS position in the controller's memory for later analysis. A number of actions may be taken by the controller. For instance, if the plant is a weed, the desired action might be to spray herbicide on the weed. Or, if the plant is a crop that is determined to be lacking in nutrient, the desired action may be to apply fertilizer. Additionally, if the plant under test is a turf landscape, such as found on golf courses and sporting fields, plant biomass may be mapped and geo-located using GPS for later, comparative analysis.

This disclosure is of 1) the utilization of the spectrum from 250 nm to 1150 nm for measurement of prediction of one or more parameters, e.g., brix, firmness, acidity, density, pH, color and external and internal defects and disorders including, for example, surface and subsurface braises, scarring, sun scald, punctures, in N—H, C—H and O—H samples including fruit; 2) an apparatus and method of detecting emitted light from samples exposed to the above spectrum in at least one spectrum range and, in the preferred embodiment, in at least two spectrum ranges of 250 to 499 nm and 500 nm; 3) the use of the chlorophyl band, peaking at 690 nm, in combination with the spectrum from 700 nm and above to predict one or more of the above parameters; 4) the use of the visible pigment region, including xanthophyll, from approximately 250 nm to 499 nm and anthocyanin from approximately 500 to 550 nm, in combination with the chlorophyl band and the spectrum from 700 nm and above to predict the all of the above parameters.

The invention provides a wood defect detection method based on deep learning. The method comprises the following steps of collecting images; segmenting the images into image blocks with a same size; selecting defect image blocks with different types and non-defective image blocks as a training sample set; using the training sample set to train a deep learning algorithm in an off-line mode; and using a trained deep learning algorithm to detect and identify defects of a wood image in an online mode and the like. In the invention, through the powerful deep learning algorithm, defects on different complex texture wood surfaces are detected and identified in high precision and online modes and a problem that a traditional image processing algorithm can not solve is solved. The invention also provides a wood defect detection system based on deep learning. Through cooperation among an image acquisition module, a deep learning algorithm processing module and a control execution module, a detection speed can be effectively accelerated and practicality is increased.

The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality.

A device to provide hyperspectral reflection spectrum, hyperspectral depolarization, and hyperspectral fluorescence spectrum data in a portable, remote sensing instrument. The device can provide a large range of remotely-sensed optical property data, presently only obtainable in laboratories, in a low-cost field instrument. Among its many uses, the present invention can be used by farmers as a tool for determining the nitrogen content of crops to optimize fertilizer laydown.

A portable Chlorophyll Fluorescence Imaging Time (CFIT) system for use in determining plant health. The system includes an enclosure for placement around a plant to be imaged in-situ. There is a controlled light source that controllably provides to the plant light of a desired wavelength range, to controllably irradiate the plant within the enclosure. The chlorophyll fluorescence emitted from the plant both spatially and temporally is captured, and the captured fluorescence information is analyzed to provide plant health information.

The present invention relates to systems and methods for monitoring agricultural products. In particular, the present invention relates to monitoring fruit production, plant growth, and plant vitality. According to embodiments of the invention, a plant analysis system is configured determine a spectral signature of a plant based on spectral data, and plant color based on photographic data. The spectral signatures and plant color are associated with assembled point cloud data. Morphological data of the plant can be generated based on the assembled point cloud data. A record of the plant can be created that associates the plant with the spectral signature, plant color, spectral data, assembled point cloud data, and morphological data, and stored in a library.

A method and system of treating plants is provided. The method includes measuring optical properties of a plant using a plurality of spectral bands. The method further includes calculating in a computational device at least two vegetative indexes using the optical properties, each of the at least two vegetative indexes correlating to one or more plant growth parameters. The method further includes calculating in the computational device a water invariant chlorophyll index from at least two vegetative indexes using the plurality of spectral bands. The also provides for treating one or more of the plants based on the water invariant chlorophyll index.

A sorting system (110) conveys articles, such as peaches (114) on a conveyor belt (112) past an inspection zone (126) that is lighted by an illumination source (90) radiating a number of emission peaks over visible and infrared portions of the spectrum. The illumination source generates the radiation from an Indium Iodide lamp (92) that is reflected off a parabolic reflector (94) and through a "soda straw" collimator (100) to illuminated the peaches. A detector system (118) employs line scanning visible and infrared cameras (142, 140) to sense visible and IR wavelength reflectance values for the peach meat (124) and peach pit or pit fragments (126). Various image processing and analysis methologies, such as subtraction, ratio, logarithmic, regression, combination, angle, distance, and shape may be employed to enhance the image contrast and classify the resulting data for sorting the peaches. Employing subtraction also cancels "glint" caused by specular reflections of the illumination source off the peaches and into the cameras.

An automated relative maturity system for measuring the relative maturity of a large number of plots of diverse varieties of plants growing in a field or fields. A field to be evaluated is laid out in multiple plots with a specific variety assigned to a preselected plot or plots and with areas set aside throughout the field for planting of check varieties of known relative maturity. High-precision GPS is used with a planter to record the location of each plot within the field on a map. When leaf senescence is under way throughout the field, a radiometric crop sensor mounted on a vehicle also equipped with high-precision GPS is used to scan the plants in the plots to record readings of the plants synchronized to the GPS map locations, including the check plants of known relative maturity. Software is used to calculate the relative maturity of each variety.

A system is provided to monitor targeted pest populations, disease, presence of transgenic and non-transgenic plants, or targeted pest population in a transgenic crop using remote imagery to discern differences in crops along with pest infestation in all crop varieties. The system relies on the fact that plant leaves are known to change color based on stress, herbivory, and other environmental factors. The system provides a special camera that can see reflected light energy across the visible and near infrared (about 400-1000 nm) to identify these effects.

A portable fluorescence and transmittance imaging spectroscopy system for use in diagnosing plant health. The system has a primary LED light source array with spectral wavelengths in the 400-600 nm range, a focus cone that collects the LED light source output and focuses it, a controller that controls the primary LED array to turn it on and off, or certain of the spectral wavelengths on and off such that the primary LED array controllably emits light of a desired wavelength in the range, the light irradiating the plant through the focus cone, a digital imaging device that both spatially and temporally captures a fluorescence image comprising chlorophyll fluorescence emitted by the plant due to the emitted light from the LED array, a leaf holder located proximate to the output of the focus cone to maintain a consistent position and distance between the digital imaging device, the LED light source and the leaf and providing for fixed position and non-destructive leaf imaging and testing, a secondary light source for providing broad-band transmissive light through the leaf, a lens for focusing onto the imaging device the light emitted from the secondary light source, and one or more memory devices that store the fluorescence image and the transmitted light data received by the digital imaging device and store a library of plant fluorescence-intensity data indicative of both healthy plants and stressed or diseased plants, and plant light transmittance data indicative of certain plant conditions.

The invention discloses a miniaturized unmanned aerial vehicle crop information obtaining and fertilization irrigation guiding apparatus and belongs to the technical field of crop monitoring, for solving the problems high cost and poor reliability existing in conventional crop monitoring. The apparatus comprises an information acquisition module, a ground sensor, a database, a ground station and an unmanned aerial vehicle, wherein the ground station carries out course planning and information acquisition point setting on a crop area to be detected; a flight controller of the unmanned aerial vehicle, according to a planned course, controlling flight of the unmanned aerial vehicle, and when the unmanned aerial vehicle arrives at information acquisition points, the information acquisition module acquires air indexes of the information acquisition points, and at the same time, performs hyperspectal shooting on crops at the information acquisition points so as to obtain growth information of the crops; the database stores data corresponding to the year with previous optimal output; the ground sensor is arranged at the crop area to be detected for measuring soil indexes; and the ground station, according to the air indexes acquired at the corresponding information acquisition points, the crop growth information and the soil indexes, makes a comparison with corresponding data in the database so as to obtain fertilization and irrigation instructions.

The present invention relates to a method for controlling of a growth cycle for a plant being arranged in a controlled environment and subject to light emitted by at least one artificial lighting arrangement. The invention also relates to a corresponding system device and to a computer program product.

An apparatus (22) for selectively discriminating vegetation or plant matter (28) comprises a light emitting means (24), a light sensing means (30) and a distance sensing means (34). The light emitting means generates a beam of light (26) that can be directed onto plants or plant matter moving relative to the apparatus. The light sensing means senses light transmitted from said light emitting means and reflected from the plants or plant matter, and generates a reflection signal in response to the sensing of the reflected light. The distance sensing means senses the relative distance moved and generates a distance signal. A processing means (32) is operatively connected to the light sensing means and the distance sensing means to combine the reflection signal and distance signal to discriminate different types of plants or plant matter.

From the crop of a predetermined area in a plant field under exposure to natural light, a reflectivity of the light having relation to crop information such as nitrogen content rate is measured by a camera; the crop information as first crop information is obtained from the first crop related formula established in advance for obtaining the crop information from the reflectivity; light is irradiated on crop leaf blades in the same area as the predetermined area and an amount of the light is measured; the crop information as second crop information is obtained from the second crop related formula established in advance for obtaining the crop information from the amount of the light; differences are calculated from the first crop information and the second crop information; the first crop information is obtained from the unknown crop in the predetermined area within the crop field of the same area; the first crop information is corrected based on the differences; and the nutritious diagnosis of the crop in the field is conducted by the corrected first crop information. In conducting diagnosis of crop by measuring the reflection light amount from the crop, since compensation or correction is performed, no great errors occur caused by differences in the measurement locations and the planting densities, and the diagnosis of the crop is simple and easy and, more over, the precision in the measuring is enhanced.

The present invention relates to a method for determining a growth status of a plant comprising chlorophyll, the method comprising the steps of: illuminating the plant (102) with input light including a light intensity modulation component (205, 206, 207, 208); detecting light emitted from the plant; determining (S702) an offset light intensity (204) surrounding the plant, the offset light intensity being a static component of the input light; determining (S718) a phase and a gain between the input light and the detected light, determining (S720) a growth status of the plant based on a predetermined relationship between input light and detected light, and on the phase and the gain. The invention also relates to a corresponding system and to a computer program product.

Systems and methods of determining nitrogen levels from a digital image and in-season nitrogen measurement and fertilization of non-leguminous crops from digital image analysis are disclosed herein. In particular, a method of determining leaf nitrogen concentration and yield from a digital photograph of a fully developed leaf (collared leaf) of a crop of non-legumes, such as corn, wheat, rice, cotton, potatoes sugarcane, turfgrass or forage grass species. The digital image is processed to determine a dark green color index (“DGCI”), which is closely related to leaf nitrogen concentration and yield. Standardized color disks having known DGCI values are included in the digital photograph and serve as an comparative standard. The comparative standard allows correction of DGCI of samples when using different cameras and/or when lighting conditions change. The DGCI values can then be used to determine the amount of nitrogen fertilizer that should be applied to recover crop yield potential.

The invention discloses a high-throughput plant phenotype analysis device based on an optical imaging technique.The device comprises a light shading cover, a base, a top frame, a material carrying table, a sensor panel, a chlorophyll fluorescence imager, a near-infrared multi-spectral facial form imager, an infrared thermal imager, a three-dimensional reconstruction imager and a light source set; the base is installed in the light shading cover, and a working position is arranged in the middle of the base; the top frame is installed in the light shading cover and fixed over the base; the material carrying table is installed on the working position of the base; the sensor panel is installed on the top frame through a translation mechanism; the chlorophyll fluorescence imager, the near-infrared multi-spectral facial form imager, the infrared thermal imager and the three-dimensional reconstruction imager are installed on the sensor panel; the light source set is installed on the sensor panel and supplies exciting light and illuminating light to the imagers.The invention further discloses a high-throughput plant phenotype analysis method based on the optical imaging technique.According to the device and method, use is convenient, complete plant phenotype data can be acquired, and the test result is accurate.