A monitoring device 100 for agricultural use comprising a housing 12 adapted to accommodate at least a solar radiation sensor positioned in the top portion of the housing 12, the housing 12 comprising an aperture at the top end 18 adapted to allow the solar radiation sensor to be exposed through the aperture. The housing is attached to a hanger 22 located at the same level or below the top end 18 of the housing 12 and adapted to hang the housing 12 on a hanging element such as a cable. The housing 12 may further comprises a leveling component 34 for leveling the solar radiation sensor or the entire monitoring device 100. The monitoring device 100 optionally comprises a shading sleeve 48 compatible with passing the hanging element through the monitoring device 100.

A system for identifying ponding water located on a field from image data is described. In an approach, an image of an agricultural field is analyzed using a classifier that has been trained based on the spectral bands of labeled image pixels to identify a probability for each pixel within the image that the pixel corresponds to water. A flow simulation is performed to determine regions of the field that are likely to pool water after rainfall based on precipitation data, elevation data, and soil property data of the field. A graph of vertices representing the pixels and edges representing connections between neighboring pixels is generated. The probability of each pixel within the graph being ponding water is set based on the probability pixel being water, the likelihood that water will pool in the area represented by the pixel, the probability of neighboring pixels being ponding water, and a cropland mask that identifies which pixels correspond to cropland. A class for each pixel is then determined that maximizes the joint probability over the graph.

In embodiments, acquiring sensor data associated with a plant growing in a field, and analyzing the sensor data to extract one or more phenotypic traits associated with the plant from the sensor data. Indexing the one or more phenotypic traits to one or both of an identifier of the plant or a virtual representation of a part of the plant, and determining one or more plant insights based on the one or more phenotypic traits, wherein the one or more plant insights includes information about one or more of a health, a yield, a planting, a growth, a harvest, a management, a performance, and a state of the plant. One or more of the health, yield, planting, growth, harvest, management, performance, and the state of the plant are included in a plant insights report that is generated.

In embodiments, acquiring sensor data associated with a plant growing in a field, and analyzing the sensor data to extract one or more phenotypic traits associated with the plant from the sensor data. Indexing the one or more phenotypic traits to one or both of an identifier of the plant or a virtual representation of a part of the plant, and determining one or more plant insights based on the one or more phenotypic traits, wherein the one or more plant insights includes information about one or more of a health, a yield, a planting, a growth, a harvest, a management, a performance, and a state of the plant. One or more of the health, yield, planting, growth, harvest, management, performance, and the state of the plant are included in a plant insights report that is generated.

A method of detecting a potato virus in a crop image depicting at least one potato plant includes storing the crop image in a memory, identifying a first region of the crop image depicting potato plant leaves, identifying a plurality of edges within the first region, determining whether an image segment of the crop image within the first region satisfies one or more leaf creasing criteria symptomatic of leaf creasing caused by the virus based on the edges that are located within the image segment, determining whether the image segment satisfies one or more color criteria symptomatic of discoloration caused by the virus, and determining whether the segment displays symptoms of potato virus based on whether the image segment satisfies one or more of the leaf creasing criteria and the color criteria. A system and computer readable medium are also disclosed.

A method of detecting a potato virus in a crop image depicting at least one potato plant includes storing the crop image in a memory, identifying a first region of the crop image depicting potato plant leaves, identifying a plurality of edges within the first region, determining whether an image segment of the crop image within the first region satisfies one or more leaf creasing criteria symptomatic of leaf creasing caused by the virus based on the edges that are located within the image segment, determining whether the image segment satisfies one or more color criteria symptomatic of discoloration caused by the virus, and determining whether the segment displays symptoms of potato virus based on whether the image segment satisfies one or more of the leaf creasing criteria and the color criteria. A system and computer readable medium are also disclosed.

To provide a vascular sap flow speed sensor having a size allowing measurement of the flow speed of vascular sap in a part of a plant such as a stem and capable of being manufactured at low cost. A vascular sap flow speed sensor 1 includes a heater sensor HS and a reference sensor RS. The heater sensor HS includes: a first probe unit 10a including a heat transfer plate 11 and a probe 12; a heater 20; a first temperature sensor 30a; and a first housing 40a in which the heat transfer plate 11, the heater 20, and the first temperature sensor 30a are housed. The reference sensor RS includes: a second probe unit 10b including a heat transfer plate 11 and a probe 12; a second temperature sensor 30b; and a second housing 40b in which the heat transfer plate 11 and the second temperature sensor 30b are housed. Each of the first probe unit 10a and the second probe unit 10b is made of a metallic material.

To provide a vascular sap flow speed sensor having a size allowing measurement of the flow speed of vascular sap in a part of a plant such as a stem and capable of being manufactured at low cost. A vascular sap flow speed sensor 1 includes a heater sensor HS and a reference sensor RS. The heater sensor HS includes: a first probe unit 10a including a heat transfer plate 11 and a probe 12; a heater 20; a first temperature sensor 30a; and a first housing 40a in which the heat transfer plate 11, the heater 20, and the first temperature sensor 30a are housed. The reference sensor RS includes: a second probe unit 10b including a heat transfer plate 11 and a probe 12; a second temperature sensor 30b; and a second housing 40b in which the heat transfer plate 11 and the second temperature sensor 30b are housed. Each of the first probe unit 10a and the second probe unit 10b is made of a metallic material.

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.

A system for utilizing waves in an assembly line grow pod includes a plurality of carts, a wave generator and a master controller. The plurality of carts carries a plurality of plants including a first plant and a second plant. The wave generator generates sound waves having a different range of frequency. The master controller is communicatively coupled to the wave generator and comprising a processor and a memory storing a wave recipe and instructions. The wave recipe correlates the plurality of plants with different characteristics of sound waves including frequency. The wave generator generates a first sound wave having the characteristic correlated to the first plant and a second sound wave having the characteristic correlated to the second plant.