A computing system includes a processor; and one or more non-transitory, computer-readable storage media storing: a trained machine learning model; and machine-readable instructions that, when executed by the one or more processors, cause the computing system to: process agronomic input feature vectors to generate one or more predicted corn growth efficiency values; and provide the corn growth efficiency values as output. A computing system includes a processor; and one or more non-transitory, computer-readable storage media storing machine-readable instructions that, when executed by the one or more processors, cause the computing system to: process labeled agronomic data with a machine learning model to generate one or more predicted corn growth efficiency values; and modify a parameter of the machine learning model. A computer-implemented method includes processing labeled agronomic data with a machine learning model to generate corn growth efficiency values; and modifying a parameter of the machine learning model.

A computing system includes a processor; and one or more non-transitory, computer-readable storage media storing: a trained machine learning model; and machine-readable instructions that, when executed by the one or more processors, cause the computing system to: process agronomic input feature vectors to generate one or more predicted corn growth efficiency values; and provide the corn growth efficiency values as output. A computing system includes a processor; and one or more non-transitory, computer-readable storage media storing machine-readable instructions that, when executed by the one or more processors, cause the computing system to: process labeled agronomic data with a machine learning model to generate one or more predicted corn growth efficiency values; and modify a parameter of the machine learning model. A computer-implemented method includes processing labeled agronomic data with a machine learning model to generate corn growth efficiency values; and modifying a parameter of the machine learning model.

This invention relates to methods and compositions for providing a benefit to a plant by associating the plant with a beneficial endophyte of the genus Streptomyces, including benefits to a plant derived from a seed or other plant element treated with said endophyte. For example, this invention provides purified endophytes, synthetic combinations comprising endophytes, and methods of making and using the same. In particular, this invention relates to compositions and methods of improving soybean and maize plants.

A digital detection method and system for predicting drug resistance of transgenic maize are disclosed. The method includes acquiring an RGB image, three-dimensional point cloud data and chlorophyll relative content of a maize plant after medicament spraying at a current moment; calculating a pixel ratio and morphological feature according to the RGB image and three-dimensional point cloud data; inputting a detection parameter of the maize plant at the current moment into a series model to predict the detection parameter of the maize plant at a next moment to obtain a graph of change in the detection parameter in a next period; estimating a drug resistance characteristic according to the graph of the change in the detection parameter of the maize plant; and inputting the detection parameter of the maize plant at the current moment into a parallel model to predict the variety of the maize plant.

A digital detection method and system for predicting drug resistance of transgenic maize are disclosed. The method includes acquiring an RGB image, three-dimensional point cloud data and chlorophyll relative content of a maize plant after medicament spraying at a current moment; calculating a pixel ratio and morphological feature according to the RGB image and three-dimensional point cloud data; inputting a detection parameter of the maize plant at the current moment into a series model to predict the detection parameter of the maize plant at a next moment to obtain a graph of change in the detection parameter in a next period; estimating a drug resistance characteristic according to the graph of the change in the detection parameter of the maize plant; and inputting the detection parameter of the maize plant at the current moment into a parallel model to predict the variety of the maize plant.

Methods for providing compositions to corn fields prior to harvesting are provided herein. These methods provide an extended time period for the use of lower height or standard height farm equipment in-season in corn fields, while reducing the risk of damage to the corn plants. These methods also allow for late season access with lower height or standard height farm equipment, while reducing the risk of damage to the corn plants.

Methods for providing compositions to corn fields prior to harvesting are provided herein. These methods provide an extended time period for the use of lower height or standard height farm equipment in-season in corn fields, while reducing the risk of damage to the corn plants. These methods also allow for late season access with lower height or standard height farm equipment, while reducing the risk of damage to the corn plants.

Methods for improving the efficiency and productivity of hybrid corn seed production are provided herein. Various methods to improve the transfer of pollen from male corn plants to female corn plants, and thus increase yield, are provided herein. Without being limiting, these methods include varying the height of male and female corn plants in a field, as well as varying the number, arrangement, and ratio of male-to-female rows in a field.

The present disclosure relates to the technical field of wheat planting, and in particular to a uniform monoseeding and cultivation method of winter wheat in Huang-huai-hai region. The cultivation method includes seedbed finishing and precision seeding; after seedbed finishing during winter wheat seeding creates excellent seedbed conditions, precision monoseeding of winter wheat is implemented by a seeder according to precise agronomic index requirements including plant spacing, row spacing, seeding depth, and seeding rate, concurrently achieving the objectives of consistent covering depth and deep placement of bottom fertilizer. The cultivation method can make the most of light, heat, water, and fertilizer resources, and precisely optimize the plant spacing, row spacing, and seeding depth during seeding to integrate mechanized seeding management of winter wheat in Huang-huai-hai region, achieving objectives of building excellent crop community and increasing yield and efficiency.

The present disclosure relates to the technical field of wheat planting, and in particular to a uniform monoseeding and cultivation method of winter wheat in Huang-huai-hai region. The cultivation method includes seedbed finishing and precision seeding; after seedbed finishing during winter wheat seeding creates excellent seedbed conditions, precision monoseeding of winter wheat is implemented by a seeder according to precise agronomic index requirements including plant spacing, row spacing, seeding depth, and seeding rate, concurrently achieving the objectives of consistent covering depth and deep placement of bottom fertilizer. The cultivation method can make the most of light, heat, water, and fertilizer resources, and precisely optimize the plant spacing, row spacing, and seeding depth during seeding to integrate mechanized seeding management of winter wheat in Huang-huai-hai region, achieving objectives of building excellent crop community and increasing yield and efficiency.