A cultivation-target crop selection assisting apparatus 10 includes: an information collection unit 11 configured to collect information regarding a specific cultivated land; a prediction value calculation unit 12 configured to calculate a prediction value of actual performance of cultivation of one or a plurality of varieties of crops in the specific cultivated land by applying the information collected by the information collection unit 11 to a prediction model 14 created by performing machine learning on a relationship between information regarding a sample cultivated land and actual performance information regarding a crop produced in the sample cultivated land; and a crop selection unit 13 configured to select a crop that is suitable for being cultivated in the specific cultivated land based on the prediction value calculated for the one or plurality of varieties of crops.

A cultivation-target crop selection assisting apparatus 10 includes: an information collection unit 11 configured to collect information regarding a specific cultivated land; a prediction value calculation unit 12 configured to calculate a prediction value of actual performance of cultivation of one or a plurality of varieties of crops in the specific cultivated land by applying the information collected by the information collection unit 11 to a prediction model 14 created by performing machine learning on a relationship between information regarding a sample cultivated land and actual performance information regarding a crop produced in the sample cultivated land; and a crop selection unit 13 configured to select a crop that is suitable for being cultivated in the specific cultivated land based on the prediction value calculated for the one or plurality of varieties of crops.

A computer system is provided comprising a classification model management server computer configured, by instructions, to: receive a new image from a user device; apply a first digital model to first regions within the new image for classifying each of the first regions into a particular class; apply a second digital model to second regions within the new image for classifying each of the second regions into a particular class; and transmit classification data related to the class of the first regions and the class of the second regions to the user device. In connection therewith, the second regions each generally correspond to a combination of multiple first regions.

One variation of a method for automating transfer of plants within an agricultural facility includes: dispatching a loader to autonomously deliver a first moduledefining a first array of plant slots at a first density and loaded with a first set of plants at a first growth stagefrom a first grow location within an agricultural facility to a transfer station within the agricultural facility; dispatching the loader to autonomously deliver a second moduledefining a second array of plant slots at a second density less than the first density and empty of plantsto 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.

One variation of a method for automating transfer of plants within an agricultural facility includes: dispatching a loader to autonomously deliver a first moduledefining a first array of plant slots at a first density and loaded with a first set of plants at a first growth stagefrom a first grow location within an agricultural facility to a transfer station within the agricultural facility; dispatching the loader to autonomously deliver a second moduledefining a second array of plant slots at a second density less than the first density and empty of plantsto 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.

The present invention provides a system for identifying individual crowns of individual fruit trees using aerial images. A crown identification device 40 of the present invention includes an identification criterion determination unit 41 and a crown identification unit 42. The identification criterion determination unit 41 includes a first image acquisition section 411 that acquires a first aerial image including a plurality of individual fruit trees in a deciduous period in a fruit farm field, a skeleton extraction section 412 that processes the first aerial image to extract a whole crown skeleton including the plurality of individual fruit trees, a vertex extraction unit 413 that extracts vertexes of each crown skeleton corresponding to each individual fruit tree, and an identification criterion extraction section 414 that extracts a crown candidate region of a minimum polygonal shape including all the vertexes as an identification criterion for each individual fruit tree and extracts a centroid of the crown candidate region. The crown identification unit 42 includes a second image acquisition section 421 that acquires a second aerial image of the fruit tree farm field at the time of identifying a crown at the same scale as the first aerial image, a whole crown extraction section 422 that processes the second aerial image to extract a whole crown image including the plurality of individual fruit trees, and a crown identification section 423 that collates the crown candidate region and the centroid of the identification criterion with the whole crown image to identify a crown region of each individual fruit tree in the second aerial image.

The present invention provides a system for identifying individual crowns of individual fruit trees using aerial images. A crown identification device 40 of the present invention includes an identification criterion determination unit 41 and a crown identification unit 42. The identification criterion determination unit 41 includes a first image acquisition section 411 that acquires a first aerial image including a plurality of individual fruit trees in a deciduous period in a fruit farm field, a skeleton extraction section 412 that processes the first aerial image to extract a whole crown skeleton including the plurality of individual fruit trees, a vertex extraction unit 413 that extracts vertexes of each crown skeleton corresponding to each individual fruit tree, and an identification criterion extraction section 414 that extracts a crown candidate region of a minimum polygonal shape including all the vertexes as an identification criterion for each individual fruit tree and extracts a centroid of the crown candidate region. The crown identification unit 42 includes a second image acquisition section 421 that acquires a second aerial image of the fruit tree farm field at the time of identifying a crown at the same scale as the first aerial image, a whole crown extraction section 422 that processes the second aerial image to extract a whole crown image including the plurality of individual fruit trees, and a crown identification section 423 that collates the crown candidate region and the centroid of the identification criterion with the whole crown image to identify a crown region of each individual fruit tree in the second aerial image.

A plant framing apparatus that provides aesthetic appearance and overcome water evaporation issues includes a first frame section, a second frame section, a plurality of locking mechanisms, and a plant opening. The first frame section and the second frame section are attached to each other by the plurality of locking mechanisms so that the first frame section and the second frame section can surround a plant base. The overall profile of the plant opening is formed by an inner lateral wall of the first frame section and the second frame section so that the plant base can project through the plant framing apparatus. Furthermore, the plant framing apparatus can include an interchangeable watering system to overcome drought conditions of the plant and/or an interchangeable lighting system to improve the aesthetic appearance of the plant.

A system and method of abating air pollution and stimulating crop growth. A reagent is introduced to a crop canopy to neutralize air pollutants within said canopy, wherein the reagent induces an oxidation-reduction chemical reaction with the air pollution present throughout the acreage of crops, and by means of the reaction effectually neutralizes the harmful effects of the air pollutants on the crops. The reagent is diluted using a venturi valve or other means. The flow rate of said reagent is regulated using an electronic control unit, based on data collected from at least one type of sensor in the canopy that is in communication with the control unit.

A cultivation floor system with a floor includes a watertight basin with a watertight groundsheet, a water-permeable structure in the basin, and a permeable top sheet which lies substantially horizontally over the water-permeable structure and forms the top side of the floor on which plant containers are optionally placed. The basin has a water-barrier structure which protrudes above the floor and delimits the compartment which is present on the floor. The water-barrier structure includes a horizontal beam with a top side, a water-barrier profile with a bottom side, and fastening means which fasten the water-barrier profile to the horizontal beam. The top side of the beam is substantially level with the top side of the floor formed by the permeable top sheet. The bottom side of the water-barrier profile is pulled onto the top side of the horizontal beam while clamping the watertight groundsheet and the permeable top sheet.