Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

A method including: recording a first image of a first field region; automatically treating a plant within the first region in-situ based on the first image; automatically verifying the plant treatment with a second image of the first region; and automatically treating a second region concurrently with treatment verification.

A system for removing seeds includes a track, one or more carts moveably disposed on the track, one or more sensors, a removing device, and a controller. The controller includes one or more processors, one or more memory modules, and machine readable instructions stored in the one or more memory modules that, when executed by the one or more processors, cause the controller to determine a location of one or more of one or more contaminated seeds and one or more contaminated plants on the one or more carts based on information received from the one or more sensors and instruct the removing device to remove one or more of the one or more contaminated seeds and the one or more contaminated plants based on the location.

A system for removing seeds includes a track, one or more carts moveably disposed on the track, one or more sensors, a removing device, and a controller. The controller includes one or more processors, one or more memory modules, and machine readable instructions stored in the one or more memory modules that, when executed by the one or more processors, cause the controller to determine a location of one or more of one or more contaminated seeds and one or more contaminated plants on the one or more carts based on information received from the one or more sensors and instruct the removing device to remove one or more of the one or more contaminated seeds and the one or more contaminated plants based on the location.

Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

A defoliator having a frame suitable for mounting to a vehicle supports an elongated main support arm which extends substantially horizontally, and which has a tine-bearing main shaft which rotates to have the tines knock at least some leaves (or portions thereof) from plants beneath. The main support arm rides on wheels, and may pivot and vertically translate with respect to the frame such that the main support arm (and the tined main shaft) will generally follow the elevation and contour of the ground beneath. To defoliate greater areas, one or both ends of the main shaft may be connected to a boom arm hearing a rotating tined arm shaft, which extends the effective length of the main support arm and tined main shaft. The boom arms are preferably capable of folding rearwardly to reduce the effective size of the defoliator for easier transport.

Apparatus, systems and methods are provided for crop stand optimization. In some embodiments a field is planted at a first population prescription determined based on a first data set including forecasted weather. A subsequently determined second population prescription is determined based on a second data set determined after planting, and the planted crop is thinned according to the second population prescription. In some embodiments the crop is selectively thinned to remove plants having a plant removal index below a threshold.

Apparatus, systems and methods are provided for crop stand optimization. In some embodiments a field is planted at a first population prescription determined based on a first data set including forecasted weather. A subsequently determined second population prescription is determined based on a second data set determined after planting, and the planted crop is thinned according to the second population prescription. In some embodiments the crop is selectively thinned to remove plants having a plant removal index below a threshold.

Apparatus, systems and methods are provided for crop stand optimization. In some embodiments a field is planted at a first population prescription determined based on a first data set including forecasted weather. A subsequently determined second population prescription is determined based on a second data set determined after planting, and the planted crop is thinned according to the second population prescription. In some embodiments the crop is selectively thinned to remove plants having a plant removal index below a threshold.

Apparatus, systems and methods are provided for crop stand optimization. In some embodiments a field is planted at a first population prescription determined based on a first data set including forecasted weather. A subsequently determined second population prescription is determined based on a second data set determined after planting, and the planted crop is thinned according to the second population prescription. In some embodiments the crop is selectively thinned to remove plants having a plant removal index below a threshold.