Projects
Turning images into action: precision orcharding and variability mapping to improve returns in tree fruit orchards
The project aimed to demonstrate the practical application of precision horticultural technologies to enhance returns in apple and pear orchards.
The project involved demonstrations of orchard scanning and grid-based soil mapping at two commercial apple orchards in the Goulburn Valley, Victoria. The Green Atlas Cartographer, a ground-based scanning system using LIDAR and camera technologies, was employed to measure tree and fruit characteristics such as fruit number, size, colour, and degree of clustering, as well as tree size metrics like height, canopy area, and leaf area. Soil samples were collected on a 50-meter grid basis and analysed to produce data on individual soil nutrients and ratios.
By layering the Green Atlas and soil data in GIS software, the project identified correlations between soil nutrient variability and fruit and tree characteristics. This information helped develop a business case for growers to invest in variable-rate fertilizer application, highlighting the extent of variability and the likely costs involved. The data collected also improved the accuracy of crop estimates and prediction of packhouse outcomes.
The project demonstrated the potential benefits of precision horticultural technologies, including more accurate crop estimation and better management of soil nutrition to improve fruit quality and consistency. The findings were shared with growers through field events and articles in industry publications, fostering greater awareness and adoption of these technologies.
Overall, the project successfully showcased the practical applications of precision horticultural technologies, providing valuable insights into the benefits of integrating soil and vision technologies for improving apple production.
The project involved demonstrations of orchard scanning and grid-based soil mapping at two commercial apple orchards in the Goulburn Valley, Victoria. The Green Atlas Cartographer, a ground-based scanning system using LIDAR and camera technologies, was employed to measure tree and fruit characteristics such as fruit number, size, colour, and degree of clustering, as well as tree size metrics like height, canopy area, and leaf area. Soil samples were collected on a 50-meter grid basis and analysed to produce data on individual soil nutrients and ratios.
By layering the Green Atlas and soil data in GIS software, the project identified correlations between soil nutrient variability and fruit and tree characteristics. This information helped develop a business case for growers to invest in variable-rate fertilizer application, highlighting the extent of variability and the likely costs involved. The data collected also improved the accuracy of crop estimates and prediction of packhouse outcomes.
The project demonstrated the potential benefits of precision horticultural technologies, including more accurate crop estimation and better management of soil nutrition to improve fruit quality and consistency. The findings were shared with growers through field events and articles in industry publications, fostering greater awareness and adoption of these technologies.
Overall, the project successfully showcased the practical applications of precision horticultural technologies, providing valuable insights into the benefits of integrating soil and vision technologies for improving apple production.
