Objectives
The aim of this project is to create variable seed rate maps using canopy sensing information to maximise ear number and ultimately yield. The project is using existing technology (canopy sensing) in a new and innovative way to predict the optimum seed rate required to develop variable seed rate maps for cereal crops (winter wheat, winter barley, spring barley). This is an innovative and novel method for predicting optimum seed rate which will use estimations of shoot number derived from RGB and multispectral information.
The project will have four objectives to meet the aim of the project:
Objective 1: Determine the most appropriate method for measuring shoot number in the field.
Objective 2: Develop algorithms for predicting optimum seed rate based on shoot number.
Objective 3: Create, test and validate variable seed rate maps created using the algorithm.
Objective 4: Transfer new technology to farmers
Objectives
The aim of this project is to create variable seed rate maps using canopy sensing information to maximise ear number and ultimately yield. The project is using existing technology (canopy sensing) in a new and innovative way to predict the optimum seed rate required to develop variable seed rate maps for cereal crops (winter wheat, winter barley, spring barley). This is an innovative and novel method for predicting optimum seed rate which will use estimations of shoot number derived from RGB and multispectral information.
The project will have four objectives to meet the aim of the project:
Objective 1: Determine the most appropriate method for measuring shoot number in the field.
Objective 2: Develop algorithms for predicting optimum seed rate based on shoot number.
Objective 3: Create, test and validate variable seed rate maps created using the algorithm.
Objective 4: Transfer new technology to farmers
Activities
This project will produce a practical affordable tool that uses remotely sensed measurements of intra-field variation in shoot number and canopy size to create reliable variable seed rate maps for winter and spring cereal crops. The project will utilise established agronomic and physiological theory to optimise seed rate in order to achieve the necessary shoot number and canopy size required for potential yield across all parts of a field. The project will build upon existing scientific understanding to produce algorithms relating remotely sensed optical data, collected by a drone, with shoot number and other crop canopy traits. This information will then be used to describe spatial variation in shoot number and canopy characteristics which will be used to produce variable seed rate maps for following crops. The project will use field scale trials to ground truth, test and validate the innovative algorithms and seed rate maps.
Activities
This project will produce a practical affordable tool that uses remotely sensed measurements of intra-field variation in shoot number and canopy size to create reliable variable seed rate maps for winter and spring cereal crops. The project will utilise established agronomic and physiological theory to optimise seed rate in order to achieve the necessary shoot number and canopy size required for potential yield across all parts of a field. The project will build upon existing scientific understanding to produce algorithms relating remotely sensed optical data, collected by a drone, with shoot number and other crop canopy traits. This information will then be used to describe spatial variation in shoot number and canopy characteristics which will be used to produce variable seed rate maps for following crops. The project will use field scale trials to ground truth, test and validate the innovative algorithms and seed rate maps.
Project details
- Main funding source
- Other EU research and development funds
- Agricultural sectors
- Cereals
1 Practice Abstracts
This project will produce a practical affordable tool that uses remotely sensed measurements of intra-field variation in shoot number and canopy size to create reliable variable seed rate maps for winter and spring cereal crops. The project will utilise established agronomic and physiological theory to optimise seed rate in order to achieve the necessary shoot number and canopy size required for potential yield across all parts of a field. The project will build upon existing scientific understanding to produce algorithms relating remotely sensed optical data, collected by a drone, with shoot number and other crop canopy traits. This information will then be used to describe spatial variation in shoot number and canopy characteristics which will be used to produce variable seed rate maps for following crops. The project will use field scale trials to ground truth, test and validate the innovative algorithms and seed rate maps.
Contacts
Project coordinator
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ADAS Gleadthorpe
Project coordinator
Project partners
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Manfield and Knapton
Project partner
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Southwell and Knapton
Project partner