Articles
The use of predictive technology to estimate yield from flower counts in high density almond (Prunus dulcis [Mill.] D.A. Webb) orchards
Article number
1395_36
Pages
275 – 282
Language
English
Abstract
The Australian almond industry has increased 17-fold between 2000 and 2022 with over 60,000 ha in plantings.
Accurate seasonal yield prediction is necessary to assist in resource management, especially tree nitrogen demand, and aid in harvest logistics.
To enable timely nitrogen management, accurate yield predictions need to be done early in the growing season.
The ability to predict crop size from flower counts will assist in early season nitrogen application adjustments.
Technology has rapidly increased in the capability to capture and analyse large data sets to assist in orchard management decisions and increase horticulture productivity.
The ground-based platform Cartographer (Green Atlas) utilises RGB cameras, LiDAR and GPS to accurately determine tree attributes like flower counts as well as tree geometry at a commercial scale.
The study was conducted on the Mildura SmartFarm higher density planting an experimental orchard consisting of 36 cultivar, rootstock and tree density treatment combinations.
This work validated the use of the Cartographer machine vision system to accurately estimate the spatial distribution of flower counts in almonds.
Predicted flower counts were ground truthed with manual flower counts and related to the measured yield.
Accurate seasonal yield prediction is necessary to assist in resource management, especially tree nitrogen demand, and aid in harvest logistics.
To enable timely nitrogen management, accurate yield predictions need to be done early in the growing season.
The ability to predict crop size from flower counts will assist in early season nitrogen application adjustments.
Technology has rapidly increased in the capability to capture and analyse large data sets to assist in orchard management decisions and increase horticulture productivity.
The ground-based platform Cartographer (Green Atlas) utilises RGB cameras, LiDAR and GPS to accurately determine tree attributes like flower counts as well as tree geometry at a commercial scale.
The study was conducted on the Mildura SmartFarm higher density planting an experimental orchard consisting of 36 cultivar, rootstock and tree density treatment combinations.
This work validated the use of the Cartographer machine vision system to accurately estimate the spatial distribution of flower counts in almonds.
Predicted flower counts were ground truthed with manual flower counts and related to the measured yield.
Authors
Z. Coetzee, A. Scalisi, J. Underwood, P. Morton, S. Scheding, I. Goodwin
Keywords
almond flower prediction model, flower density, pollination, fruit retention rate, crop load
Groups involved
- Division Temperate Tree Nuts
- Division Vine and Berry Fruits
- Division Temperate Tree Fruits
- Division Precision Horticulture and Engineering
- Division Plant-Environment Interactions in Field Systems
- Division Tropical and Subtropical Fruit and Nuts
- Working Group Precision Management of Orchards and Vineyards
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