ISHS Acta Horticulturae 1403: XIV International Pear Symposium
A ground-based platform for estimates of fruit size in pear orchards – accuracy of block average, spatial variability and classification |
| Authors: | A. Scalisi, L. McClymont, P. Morton, S. Scheding, J. Underwood, I. Goodwin |
| Keywords: | fruit diameter, machine vision, orchard fruit grading, precision horticulture, size distribution |
| DOI: | 10.17660/ActaHortic.2024.1403.20 |
| Abstract:
The pear industry would greatly benefit from obtaining orchard fruit size estimates and forecasts to inform logistics and the supply chain in advance. Measurements of fruit size in orchards are typically carried out with callipers on small samples. Promising technology available today has great potential to generate “Big Data” that can be used to maximise fruit growing efficiency and profit. This study evaluated the reliability of a commercial, sensorised, ground-based platform equipped with a network of proximal sensors – namely Green Atlas Cartographer – to estimate fruit size in pear orchards. The aim of the study was to measure the reliability of the predictions of fruit size and to evaluate spatial variability using orchard heatmaps. The study was conducted over the 2020-2021 and 2021-2022 seasons at the Tatura SmartFarm and in two commercial orchards in the Goulburn Valley, Victoria, Australia. Two cultivars were used for this experiment – the blush pear ‘ANP-0131’ and the uniformly dark red pear ‘PremP009’. In the first season, fruit diameter estimates on tagged fruit were compared to manual measurements of fruit equatorial diameter obtained with a digital calliper. In the second season, estimates of fruit size in detection zones (i.e., 6-10 m orchard row sections) were compared to fruit diameters obtained with digital callipers and with a commercial fruit grader. Fruit diameter prediction errors were consistently below 5 mm in both seasons. Remarkably, estimates of fruit size distribution classes showed errors below 2%. Early data on the expected fruit size at harvest has the potential to inform packhouses and the supply chain to direct the produce to the most profitable markets. | |
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