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.

A method of underground watering utilizes a pouch-like container product made by joining a first sheet having SAP particles adhered to a first surface with a second sheet to form a container partially filled with such particles. The application of pressure, for example by passing the product through a roll nip, facilitates joining of the sheets and causes the particles to break through at least the one of the sheets to create an opening whereby free volume is created to permit the particles to expand when in contact with a liquid. The resultant product is used to collect, store, and dispense water-containing liquids into the soil for watering of agricultural plants, trees, and the like. A composite underground watering element is also included in an embodiment of the invention. The inventive products may also be used as a pad, including a propagation pad, to collect, store, and dispense water-containing-liquids into plant vessels to provide watering of plants. Also included are underground watering of athletic fields and golf course greens, erosion control products and plant root balls having a watering collar.

Systems and methods for processing image data for crops are provided. One example computer-implemented method includes accessing image data specific to a corn plant, where the image data includes an image of the corn plant and depth data indicative of a range between the corn plant and a camera, which captures said image, and identifying, by a computing device, using a trained model, a feature of the corn plant, the feature including an ear of the corn plant and/or a node from which the ear emerges. The method also includes transforming, by the computing device, coordinates specific to the feature into a height of the feature of the corn plant and storing, by the computing device, the height of the feature of the corn plant in a memory.

Systems and methods for processing image data for crops are provided. One example computer-implemented method includes accessing image data specific to a corn plant, where the image data includes an image of the corn plant and depth data indicative of a range between the corn plant and a camera, which captures said image, and identifying, by a computing device, using a trained model, a feature of the corn plant, the feature including an ear of the corn plant and/or a node from which the ear emerges. The method also includes transforming, by the computing device, coordinates specific to the feature into a height of the feature of the corn plant and storing, by the computing device, the height of the feature of the corn plant in a memory.

A method of preserving the pollen viability of maize, especially under heat stress, comprising treating the maize plants with a protein hydrolysate.

A method of preserving the pollen viability of maize, especially under heat stress, comprising treating the maize plants with a protein hydrolysate.

The present disclosure is related to terrein functioning as a biopesticide formulation in drought resistance and growth promotion of crops. The formulation containing terrein can be treated by soaking or spraying on the crops. It is especially suitable for drought and water shortage conditions, promoting growth of plant root length, seedling height, fresh weight, and dry weight, greatly increasing crop yield, and significantly improving drought resistance of crop plants. Under the condition of seed soaking treatment with 10 g/mL terrein, promotion rates of root length, seedling height, fresh weight, and dry weight of pakchoi are 99.19%, 15.66%, 40.34%, and 49.12%, respectively. The source of terrein is easy to obtain and the cost is low. It has a simple structure and is easily soluble in water. In the actual application process, it only needs to simply prepare an aqueous solution or mix with other pesticide formulations for seed soaking or spraying treatment.

The present disclosure is related to terrein functioning as a biopesticide formulation in drought resistance and growth promotion of crops. The formulation containing terrein can be treated by soaking or spraying on the crops. It is especially suitable for drought and water shortage conditions, promoting growth of plant root length, seedling height, fresh weight, and dry weight, greatly increasing crop yield, and significantly improving drought resistance of crop plants. Under the condition of seed soaking treatment with 10 g/mL terrein, promotion rates of root length, seedling height, fresh weight, and dry weight of pakchoi are 99.19%, 15.66%, 40.34%, and 49.12%, respectively. The source of terrein is easy to obtain and the cost is low. It has a simple structure and is easily soluble in water. In the actual application process, it only needs to simply prepare an aqueous solution or mix with other pesticide formulations for seed soaking or spraying treatment.

A method for cultivating alcohol-brewing sorghum on the basis of a biodegradable mulching film includes five steps such as farmland preparation, film mulching, sowing operation, field management and harvesting. Compared with a traditional alcohol-brewing sorghum planting method, the method of the present invention can effectively bring forward the planting time of alcohol-brewing sorghum, reduce the sowing amount of alcohol-brewing sorghum, assist in increasing the germination rate of alcohol-brewing sorghum, and promote the growth and development of alcohol-brewing sorghum; moreover, the method of the present invention effectively reduces the labor intensity and cost of a weeding operation in field management.