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Mass Estimation of Soft Fruit via Oscillatory Plant Dynamics

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conference contribution
posted on 2025-01-21, 10:30 authored by Nikolaus Wagner, Grzegorz CielniakGrzegorz Cielniak

Yield forecasting is an essential task in modern agriculture, as it enables farmers and food economists to manage crop and its distribution precisely and effectively. Traditionally, most methods for yield forecasting are based on historical data and yield estimates from manually collected samples. More modern approaches often rely on computer vision-based fruit counting algorithms, which do not take individual crop weights into account.In this paper, we propose a novel, non-destructive method to estimate the mass of individual pieces of fruit by exploiting the dynamic properties of plants. By observing short-term oscillatory plant motion through RGB-D video data, we formulate an approach for mass estimation based on determining the parameters of a damped harmonic oscillator model.We test the proposed algorithm by collecting a dataset of around 300 video samples of strawberries on a real strawberry farm and apply our method. With a semi-automated toolchain, capable of inferring the key parameters from video data and calculating the mass of individual berries from those, we were able to estimate the mass of all berries in our dataset with a median error of 1.16g, outperforming a baseline utilising vision-based volume estimation to infer the mass. These insights hold valuable improvements for the development of yield forecasting systems and selective harvesters, which help to address the sustainability of food production and labour shortages.

History

School affiliated with

  • Lincoln Institute for Agri-Food Technology (Research Outputs)

Publication Title

2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)

Pages/Article Number

3278-3283

Publisher

IEEE

ISSN

2161-8070

eISSN

2161-8089

ISBN

979-8-3503-5852-0

eISBN

979-8-3503-5851-3

Date Accepted

2024-08-28

Date of Final Publication

2024-10-23

Event Name

2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)

Event Dates

28 August 2024 - 01 September 2024

Open Access Status

  • Not Open Access

Date Document First Uploaded

2024-12-20

Publisher statement

© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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  • Yes

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