Projects
Large scale automated visual yield estimation in table grape vineyards
This project led by the Australian Table Grape Association (ATGA), aimed to enhance yield estimation in table grape vineyards using advanced digital technologies.
The project focused on the use of Bitwise Agronomy's GreenView platform, which employs GoPro cameras to collect images and specific algorithms to convert these images into bunch number estimates. This technology was tested across various vineyards in Victoria, New South Wales, and Queensland. The project successfully demonstrated that the GreenView platform is fit for purpose, particularly in a service provider model, although it required adjustments for wider adoption in the table grape industry.
Key achievements include the identification and overcoming of barriers to adoption, such as internet constraints and the capacity of owner-operators to dedicate time. The project involved larger businesses with the necessary technology hardware, software capabilities, and dedicated staff. This approach proved effective, with an 80% adoption rate compared to 33% in the earlier round.
The project also conducted a cost-benefit analysis, which showed that the technology enables larger production areas to be surveyed with relatively accurate data output for yield estimation. This allows producers to address crop variability and predict quality and yield more accurately based on larger data sets.
Throughout the project, the team held workshops and field days to showcase the technology and gather feedback. Participants appreciated the opportunity to trial the technology without initial financial outlay and provided valuable feedback that will help improve the technology further.
Overall, the project provided valuable insights into the practical adoption of automated visual yield estimation technologies in the table grape industry, setting a foundation for future projects and wider adoption across the sector.
The project focused on the use of Bitwise Agronomy's GreenView platform, which employs GoPro cameras to collect images and specific algorithms to convert these images into bunch number estimates. This technology was tested across various vineyards in Victoria, New South Wales, and Queensland. The project successfully demonstrated that the GreenView platform is fit for purpose, particularly in a service provider model, although it required adjustments for wider adoption in the table grape industry.
Key achievements include the identification and overcoming of barriers to adoption, such as internet constraints and the capacity of owner-operators to dedicate time. The project involved larger businesses with the necessary technology hardware, software capabilities, and dedicated staff. This approach proved effective, with an 80% adoption rate compared to 33% in the earlier round.
The project also conducted a cost-benefit analysis, which showed that the technology enables larger production areas to be surveyed with relatively accurate data output for yield estimation. This allows producers to address crop variability and predict quality and yield more accurately based on larger data sets.
Throughout the project, the team held workshops and field days to showcase the technology and gather feedback. Participants appreciated the opportunity to trial the technology without initial financial outlay and provided valuable feedback that will help improve the technology further.
Overall, the project provided valuable insights into the practical adoption of automated visual yield estimation technologies in the table grape industry, setting a foundation for future projects and wider adoption across the sector.
