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Benchmarking new methods for estimation of weight of mango fruit on tree

Central Queensland University
Maisa Pereira (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25946/29483708.v1&rft.title=Benchmarking new methods for estimation of weight of mango fruit on tree&rft.identifier=https://doi.org/10.25946/29483708.v1&rft.publisher=Central Queensland University&rft.description=This research aimed to recommend methods, equipment, and protocols to Australian mango farmers for the forward estimation of at-harvest fruit load, with a focus on fruit size forecasting. A comparison of field temperature measurement systems for growing degree days (GDD) estimation was undertaken, with recommendations based on accuracy and cost. Existing GDD targets for key cultivars were validated. Recommendations for allometric models to estimate fruit weight from dimensions were made, with cultivar-specific parameters. A comparison of fruit growth models was undertaken, with recommendations for forecasting accuracy at different pre-harvest intervals. Recommendations for improvements to machine vision-based fruit sizing tools were also made. Together, these activities provided a holistic approach to forecasting fruit size at harvest.&rft.creator=Maisa Pereira&rft.date=2025&rft_rights=GPL 2.0+&rft_subject=Stone fruit (excl. avocado)&rft_subject=Fruit&rft_subject=sizing&rft_subject=mango&rft_subject=fruit growth&rft_subject=Post harvest horticultural technologies (incl. transportation and storage)&rft.type=dataset&rft.language=English Access the data

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This research aimed to recommend methods, equipment, and protocols to Australian mango farmers for the forward estimation of at-harvest fruit load, with a focus on fruit size forecasting. A comparison of field temperature measurement systems for growing degree days (GDD) estimation was undertaken, with recommendations based on accuracy and cost. Existing GDD targets for key cultivars were validated. Recommendations for allometric models to estimate fruit weight from dimensions were made, with cultivar-specific parameters. A comparison of fruit growth models was undertaken, with recommendations for forecasting accuracy at different pre-harvest intervals. Recommendations for improvements to machine vision-based fruit sizing tools were also made. Together, these activities provided a holistic approach to forecasting fruit size at harvest.

Issued: 2025-07-11

Created: 2025-07-11

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