An approach to the prediction of soil density and subsoil crop growth may be provided. The approach may include subsoil sensor which can monitor changes in soil pressure and moisture conditions. The sensor data can be sent to a computer module which can process the data using a machine learning model predicting the soil density around a subsoil crop and the yield of the subsoil crop. A soil maintenance plan can be generated from the soil density prediction and/or the crop yield prediction. The soil maintenance plan can be sent to soil management robots, which can execute the soil maintenance plan.

Crops for human and animal consumption of many types are well known by their respective growers. Years of experience in the field provide the grower knowledge about a range of conditions that lead to the full spectrum of crop yields and crop quality, and each grower creates a store of knowledge which they can combine with the available measures of those conditions. This disclosure provides a method for indicating the onset of water stress in one or more plants located in a soil the roots of which are within the measurement zone of a soil moisture sensor located in the soil, by determining if there was no recorded water into soil event in the prior 24 hour period of a respective one 24 hour period; determining from representative data whether there are two respective 24 hour periods of the prior seven consecutive 24 hour periods also have evapotranspiration values within a predetermined range; determining from representative data the rate of soil moisture depletion during the plant moisture uptake period within each respective 24 hour period adjusted for drainage; determining whether the rate of soil moisture depletion during the plant moisture uptake period within each respective 24 hour period reduces by a pre-determined level compared to the other of the respective 24 hour period; and indicating the most recent of the respective two 24 hour periods as a period of water stress of the one or more plants.

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.

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 system for plant parameter detection, including: a plant morphology sensor having a first field of view and configured to record a morphology measurement of a plant portion and an ambient environment adjacent the plant, a plant physiology sensor having a second field of view and configured to record a plant physiology parameter measurement of a plant portion and an ambient environment adjacent the plant, wherein the second field of view overlaps with the first field of view; a support statically coupling the plant morphology sensor to the physiology sensor, and a computing system configured to: identify a plant set of pixels within the physiology measurement based on the morphology measurement; determine physiology values for each pixel of the plant set of pixels; and extract a growth parameter based on the physiology values.

A system for plant parameter detection, including: a plant morphology sensor having a first field of view and configured to record a morphology measurement of a plant portion and an ambient environment adjacent the plant, a plant physiology sensor having a second field of view and configured to record a plant physiology parameter measurement of a plant portion and an ambient environment adjacent the plant, wherein the second field of view overlaps with the first field of view; a support statically coupling the plant morphology sensor to the physiology sensor, and a computing system configured to: identify a plant set of pixels within the physiology measurement based on the morphology measurement; determine physiology values for each pixel of the plant set of pixels; and extract a growth parameter based on the physiology values.

A method for determining the growth stage of a plant is disclosed. The method comprises illuminating the plant with illumination light. The illumination light causes response light from the plant. The method further comprises detecting the response light from the plant, and, based on the detected response light, determining the growth stage of the plant. In this method, (i) illuminating the plant comprises illuminating with at least partially polarized illumination light, and/or (ii) detecting the response light comprises polarization filtering the response light.

A method for determining the growth stage of a plant is disclosed. The method comprises illuminating the plant with illumination light. The illumination light causes response light from the plant. The method further comprises detecting the response light from the plant, and, based on the detected response light, determining the growth stage of the plant. In this method, (i) illuminating the plant comprises illuminating with at least partially polarized illumination light, and/or (ii) detecting the response light comprises polarization filtering the response light.

The invention provides a horticulture system (1) comprising a plurality of repeating horticulture system units (100) and a control system (300), wherein: each horticulture system unit (100) comprises (i) a horticulture unit space (110) and (ii) a radio transmission pair (120) arranged to monitor the horticulture unit space (110), wherein the radio transmission pair (120) comprises a radio transmitter and a radio receiver arranged in radio signal receiving relationship; the control system (300) is configured to execute in a unit sensing stage (230) a measurement in at least one of the horticulture unit spaces (110) with the respective radio transmission pair (120); the control system (300) is further configured in an operational mode to: (i) execute a first signal sensing stage (231), wherein the first signal sensing stage (231) comprises the unit sensing stage (230) with a first radio transmission pair (121) related to first horticulture unit space (111) thereby providing a first signal (241) to the control system (300); and (ii) determine a plant-related parameter data based on (a) the first signal (241) and (b) a baseline signal (245), wherein the baseline signal (245) is based on a second signal (242) obtained with an execution of a second signal sensing stage (232), wherein the second signal sensing stage (232) comprises the unit sensing stage (230) with a second radio transmission pair (122) related to a second horticulture unit space (112) thereby providing the second signal (242).

In some embodiments, this disclosure provides a method for creating a design layer to adhere to a living body, said method comprising: drawing a design on a surface layer by placing a dye on the surface layer in advance; and placing an adhesive layer thereon; and adhering the dye so that it is sandwiched between the surface layer and the adhesive layer.