A multi-sensor device includes a housing having multiple cavities and one or more sensor modules. Each sensor module is configured to occupy one of the cavities, and each sensor module is configured to sense at least one plant-related parameter when the multi-sensor device is positioned proximate to a plant. The multi-sensor device also includes a control unit configured to control operation of the one or more sensor modules and a location tracking system configured to track a location of the multi-sensor device. The multi-sensor device further includes a communications interface configured to transmit information including data from the one or more sensor modules. In addition, the multi-sensor device includes an electrical power connector configured to connect the multi-sensor device to a power source.

A multi-sensor device includes a housing having multiple cavities and one or more sensor modules. Each sensor module is configured to occupy one of the cavities, and each sensor module is configured to sense at least one plant-related parameter when the multi-sensor device is positioned proximate to a plant. The multi-sensor device also includes a control unit configured to control operation of the one or more sensor modules and a location tracking system configured to track a location of the multi-sensor device. The multi-sensor device further includes a communications interface configured to transmit information including data from the one or more sensor modules. In addition, the multi-sensor device includes an electrical power connector configured to connect the multi-sensor device to a power source.

A mobile sensory platform includes a propulsion system configured to move the mobile sensory platform along a surface of a growing area. The mobile sensory platform also includes multiple sensors configured to capture measurement data associated with multiple plants in the growing area. The mobile sensory platform further includes a communication interface configured to support two-way communication over a wireless network. In addition, the mobile sensory platform also includes a power supply and a control system configured to control movement of the mobile sensory platform and operation of the sensors. The multiple sensors include one or more microclimate sensors configured to generate microclimate sensor data based on changes in a microclimate around individual ones of the multiple plants.

A mobile sensory platform includes a propulsion system configured to move the mobile sensory platform along a surface of a growing area. The mobile sensory platform also includes multiple sensors configured to capture measurement data associated with multiple plants in the growing area. The mobile sensory platform further includes a communication interface configured to support two-way communication over a wireless network. In addition, the mobile sensory platform also includes a power supply and a control system configured to control movement of the mobile sensory platform and operation of the sensors. The multiple sensors include one or more microclimate sensors configured to generate microclimate sensor data based on changes in a microclimate around individual ones of the multiple plants.

A vegetable production method includes seeding, causing a cotyledon to sprout from a seed in a first period, growing a vegetable in a second period subsequent to the first period, further growing the vegetable in a third period subsequent to the second period, and harvesting the vegetable. The vegetable is grown with first light having a first maximum value of a light intensity in a wavelength range of 420 to 490 nm and including at least portion of light in a wavelength range of 500 to 600 nm in a later part of the second period, and is grown with second light having a second maximum value of a light intensity in a wavelength range of 590 to 650 nm, having a peak light intensity less than the second maximum value in a visible light wavelength range of less than or equal to 500 nm.

A vegetable production method includes seeding, causing a cotyledon to sprout from a seed in a first period, growing a vegetable in a second period subsequent to the first period, further growing the vegetable in a third period subsequent to the second period, and harvesting the vegetable. The vegetable is grown with first light having a first maximum value of a light intensity in a wavelength range of 420 to 490 nm and including at least portion of light in a wavelength range of 500 to 600 nm in a later part of the second period, and is grown with second light having a second maximum value of a light intensity in a wavelength range of 590 to 650 nm, having a peak light intensity less than the second maximum value in a visible light wavelength range of less than or equal to 500 nm.

A system for agricultural irrigation water oxygenation for enriching soil oxygen level comprises a source of compressed oxygen (and not compressed air) coupled to a water line feeding an irrigation system, such as a drip irrigation system. The coupling system may include a pressure sensor for measuring the pressure in the water line, a solenoid safety valve, a control valve, a flow meter and a controller that controls the flow of oxygen from the source of compressed liquid oxygen to the water line using the components of the coupling system, without using a special cavitation valve and using off-the-shelf components while achieving the same benefits as a system incorporating the special cavitation valve.

An ecological restoration method for a lake wetland against effects of water level rise in a dry season includes: collecting basic data of a lake; determining wetland phytoremediation species of the lake; determining characteristic water levels of the lake under a baseline scenario and under different water level rise scenarios; determining a restoration range based on wetland types corresponding to different characteristic water levels; selecting an experimental restoration area from the restoration range, and performing ecological restoration; and monitoring a plant community state and waterbird biodiversity, judging whether the restoration reaches a preset goal, and adjusting the method if the restoration does not reach the preset goal. According to the method, the effects of water level rise in the dry season on wetland habitat, biodiversity, ecosystem services and the like can be relieved to the greatest extent, so that an ecological restoration effect of the lake wetland is improved.

An ecological restoration method for a lake wetland against effects of water level rise in a dry season includes: collecting basic data of a lake; determining wetland phytoremediation species of the lake; determining characteristic water levels of the lake under a baseline scenario and under different water level rise scenarios; determining a restoration range based on wetland types corresponding to different characteristic water levels; selecting an experimental restoration area from the restoration range, and performing ecological restoration; and monitoring a plant community state and waterbird biodiversity, judging whether the restoration reaches a preset goal, and adjusting the method if the restoration does not reach the preset goal. According to the method, the effects of water level rise in the dry season on wetland habitat, biodiversity, ecosystem services and the like can be relieved to the greatest extent, so that an ecological restoration effect of the lake wetland is improved.

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.