The present invention relates to an automated analytical system and an automated method for separating and detecting an analyte, as well as an automated analytical instrument.

Embodiments described herein provide for multi-media structures 100 with growth enhancement additives for multiple stages of growth of an organism such as a plant, fungus or bacteria, including the production of individual media structures and multi-media structures 100 for multi-stage growth. Methods for the production of individual media structure and multi-media structures 100 with growth enhancement additives are provided. Methods for using multi-media structures 100 to grow an organism through multiple stages of growth such as root production, vegetative growth and flowering are also provided.

Embodiments described herein provide for multi-media structures 100 with growth enhancement additives for multiple stages of growth of an organism such as a plant, fungus or bacteria, including the production of individual media structures and multi-media structures 100 for multi-stage growth. Methods for the production of individual media structure and multi-media structures 100 with growth enhancement additives are provided. Methods for using multi-media structures 100 to grow an organism through multiple stages of growth such as root production, vegetative growth and flowering are also provided.

A system for creating three-dimensional grass graphics can include a means for cutting grass with an adjustable cutting height, a chlorophyll-based agent for coloring grass, and at least one stencil. The chlorophyll-based agent can be non-detrimental to a health of the grass and can be available in multiple shades. The stencil can be securable to the grass and can define a graphic to be painted on the grass using the chlorophyll-based agent. The means for cutting the grass can be able to pass over and around the stencil without damaging the stencil. Application of different shades of the chlorophyll-based agent to varying heights of grass can produce a three-dimensional effect for the graphic when viewed.

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.

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.

Crop loss estimation allows a user to monitor and estimate damage to the crops due to various natural events/factors. State of the art systems used for the crop loss estimation have the disadvantage that they do not convey to the users extent of damage. In addition to this, the existing methods do not take into account the recovery factor of the crops due to multiple factors and end up in overestimating the loss. The disclosure herein generally relates to crop monitoring, and, more particularly, to a method and system for crop loss estimation. In this method, crop loss is assessed based on real-time weather parameters and remote sensing data collected and processed, and crops are classified as being in one of a repairable damage class and a permanent damage class. The system also quantifies the crop loss, which allows the user to understand magnitude of the crop loss.

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.

Described herein are mobile sensing units for capturing raw data corresponding to certain characteristics of plants and their growing environment. Also described are computer devices and related methods for collecting user inputs, generating information relating to the plants and/or growing environment based on the raw data and user inputs, and displaying same.