In an embodiment, yield data representing yields of crops that have been harvested from an agricultural field and field characteristics data representing characteristics of the agricultural field is received and used to determine a plurality of management zone delineation options. Each option, of the plurality of management zone delineation options, comprises zone layout data for an option. The plurality of management zone delineation options is determined by: determining a plurality of count values for a management class count; generating, for each count value, a management delineation option by clustering the yield data from and the field characteristics data, assigning zones to clusters, and including the zones in a management zone delineation option. One or more options from the plurality of management zone delineation options are selected and used to determine one or more planting plans. A graphical representation of the options and the planting plans is displayed for a user.

The invention provides for computational and networking environment arrangements to co-coordinate the activities, roles, operation, maintenance, and optimal use of multiple plant-cultivation enhancement and monitoring technology subsystems including mechanical, illumination, chemical, biochemical, hydraulic, thermal, pneumatic, electronic, electrical, computational, informational, sensor, measurement, control, analysis, modeling, logging, database, and networking, as well as other technologies. Additionally, sensors and/or plant environment equipment items can be an Internet of Things (IoT) entity. Individual plants can be assigned an identification “ID” that can be used to track individual plants as to environment, history, introduction, removal, and health. Individual plants can be provided with RFID tags or tags that operate as an Internet of Things (IoT) entity. The invention provides for strategies for a wide range of user interfaces types and provides for flexible readily-customizable implementations. Example GUI types include capabilities for user settings, operating mode, configuration, monitoring, logging, analysis, testing, and diagnostics.

The invention provides for computational and networking environment arrangements to co-coordinate the activities, roles, operation, maintenance, and optimal use of multiple plant-cultivation enhancement and monitoring technology subsystems including mechanical, illumination, chemical, biochemical, hydraulic, thermal, pneumatic, electronic, electrical, computational, informational, sensor, measurement, control, analysis, modeling, logging, database, and networking, as well as other technologies. Additionally, sensors and/or plant environment equipment items can be an Internet of Things (IoT) entity. Individual plants can be assigned an identification “ID” that can be used to track individual plants as to environment, history, introduction, removal, and health. Individual plants can be provided with RFID tags or tags that operate as an Internet of Things (IoT) entity. The invention provides for strategies for a wide range of user interfaces types and provides for flexible readily-customizable implementations. Example GUI types include capabilities for user settings, operating mode, configuration, monitoring, logging, analysis, testing, and diagnostics.

A method of cultivating a fruit vegetable plant, in which at least two parts of a plurality of ground parts generated from one plant seedling of the fruit vegetable plant are cultivated in different environments, and a tomato fruit.

A microbial sensor, microbial sensing system, and method that can be used to determine the chemical environment of unsaturated soils, rhizosphere, and/or plants are disclosed. The microbial sensing system can be used for monitoring the health of plants including nutrients, salinity, contaminants, chemicals (pesticides, herbicides) and diseases. A microbial sensing system can include one or more indicator electrodes and a reference electrode. The microbial sensing system can include a signal acquisition and/or communication module to allow the real-time collection of data from field deployments and laboratory investigations.

A microbial sensor, microbial sensing system, and method that can be used to determine the chemical environment of unsaturated soils, rhizosphere, and/or plants are disclosed. The microbial sensing system can be used for monitoring the health of plants including nutrients, salinity, contaminants, chemicals (pesticides, herbicides) and diseases. A microbial sensing system can include one or more indicator electrodes and a reference electrode. The microbial sensing system can include a signal acquisition and/or communication module to allow the real-time collection of data from field deployments and laboratory investigations.

The accuracy of an index indicating growth conditions of a crop obtained from a shot image is improved, while reducing the flight time of an aircraft shooting the crop. Crop image acquisition unit acquires an image of a crop region shot by drone. Index calculation unit calculates an index indicating growth conditions of a crop shot in the image based on the acquired image of the crop region. Flight instruction unit instructs, if a portion (low index region) regarding which the calculated index is less than a predetermined index threshold is present in the crop region, drone to shoot the low index region while increasing the resolution of the image. Specifically, flight instruction unit makes an instruction to shoot the portion while performing a low-altitude flight at an altitude lower than that when the image regarding which the index of the low index region has been calculated has been shot.

The accuracy of an index indicating growth conditions of a crop obtained from a shot image is improved, while reducing the flight time of an aircraft shooting the crop. Crop image acquisition unit acquires an image of a crop region shot by drone. Index calculation unit calculates an index indicating growth conditions of a crop shot in the image based on the acquired image of the crop region. Flight instruction unit instructs, if a portion (low index region) regarding which the calculated index is less than a predetermined index threshold is present in the crop region, drone to shoot the low index region while increasing the resolution of the image. Specifically, flight instruction unit makes an instruction to shoot the portion while performing a low-altitude flight at an altitude lower than that when the image regarding which the index of the low index region has been calculated has been shot.

The patent discloses a method for efficiently collecting and purifying Orobanche cumana (O. cumana) germination stimulants using aeroponic system and solid-phase extraction (SPE), including the following steps: (1) sunflower seeds germination, then planting sunflower seedlings in aeroponic device, and cultivating the sunflower seedlings in the aeroponic system; at the aeroponic stage, phosphorus-containing aeroponic nutrient solution is first used to cultivate the sunflower seedlings for 20 to 25 days, and phosphorus-free aeroponic nutrient solution is then used instead to subject the sunflower seedlings to starvation cultivation for 5 to 7 days; and (2) passing all nutrient solutions in the aeroponic device through an SPE cartridge for SPE to extract O. cumana germination stimulants. The obtained O. cumana germination stimulants are diversified, and have high concentration and purity.

One variation of a method for automating transfer of plants within an agricultural facility includes: dispatching a loader to autonomously deliver a first module—defining a first array of plant slots at a first density and loaded with a first set of plants at a first growth stage—from a first grow location within an agricultural facility to a transfer station within the agricultural facility; dispatching the loader to autonomously deliver a second module—defining a second array of plant slots at a second density less than the first density and empty of plants—to the transfer station; recording a module-level optical scan of the first module; extracting a viability parameter of the first set of plants from features detected in the module-level optical scan; and if the viability parameter falls outside of a target viability range, rejecting transfer of the first set of plants from the first module.