Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form
Abstract Reliable phenotyping methods that are simple to operate and inexpensive to deploy are critical for studying quantitative traits in plants. Traditional fruit shape phenotyping relies on human raters or 2D analyses to assess form, e.g., size and shape. Systems for 3D imaging using multi‐view...
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Format: | Article |
Language: | English |
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Wiley
2022-01-01
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Series: | Plant Phenome Journal |
Online Access: | https://doi.org/10.1002/ppj2.20029 |
_version_ | 1797976303699230720 |
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author | Mitchell J. Feldmann Amy Tabb |
author_facet | Mitchell J. Feldmann Amy Tabb |
author_sort | Mitchell J. Feldmann |
collection | DOAJ |
description | Abstract Reliable phenotyping methods that are simple to operate and inexpensive to deploy are critical for studying quantitative traits in plants. Traditional fruit shape phenotyping relies on human raters or 2D analyses to assess form, e.g., size and shape. Systems for 3D imaging using multi‐view stereo have been implemented, but frequently rely on commercial software and/or specialized hardware, which can lead to limitations in accessibility and scalability. We present a complete system constructed of consumer‐grade components for capturing, calibrating, and reconstructing the 3D form of small‐to‐moderate sized fruits and tubers. Data acquisition and image capture sessions are 9 seconds to capture 60 images. The initial prototype cost was $1600 USD. We measured accuracy by comparing reconstructed models of 3D printed ground truth objects to the original digital files of those same ground truth objects. The R2 between length of the primary, secondary, and tertiary axes, volume, and surface area of the ground‐truth object and the reconstructed models was >0.97 and root‐mean square error (RMSE) was < 3 mm for objects without locally concave regions. Measurements from 1 mm and 2 mm resolution reconstructions were consistent (R2 > 0.99). Qualitative assessments were performed on 48 fruit and tubers, including 18 strawberries, 12 potatoes, five grapes, seven peppers, and four Bosc and two red Anjou pears. Our proposed phenotyping system is fast, relatively low cost, and has demonstrated accuracy for certain shape classes, and could be used for the 3D analysis of fruit form. |
first_indexed | 2024-04-11T04:48:51Z |
format | Article |
id | doaj.art-77cb53f546b7426e9625f58fd9b72497 |
institution | Directory Open Access Journal |
issn | 2578-2703 |
language | English |
last_indexed | 2024-04-11T04:48:51Z |
publishDate | 2022-01-01 |
publisher | Wiley |
record_format | Article |
series | Plant Phenome Journal |
spelling | doaj.art-77cb53f546b7426e9625f58fd9b724972022-12-27T06:00:35ZengWileyPlant Phenome Journal2578-27032022-01-0151n/an/a10.1002/ppj2.20029Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit formMitchell J. Feldmann0Amy Tabb1Dep. of Plant Sciences Univ. of California Davis CA USAUSDA‐ARS, Applachian Fruit Research Station Kearneysville WV USAAbstract Reliable phenotyping methods that are simple to operate and inexpensive to deploy are critical for studying quantitative traits in plants. Traditional fruit shape phenotyping relies on human raters or 2D analyses to assess form, e.g., size and shape. Systems for 3D imaging using multi‐view stereo have been implemented, but frequently rely on commercial software and/or specialized hardware, which can lead to limitations in accessibility and scalability. We present a complete system constructed of consumer‐grade components for capturing, calibrating, and reconstructing the 3D form of small‐to‐moderate sized fruits and tubers. Data acquisition and image capture sessions are 9 seconds to capture 60 images. The initial prototype cost was $1600 USD. We measured accuracy by comparing reconstructed models of 3D printed ground truth objects to the original digital files of those same ground truth objects. The R2 between length of the primary, secondary, and tertiary axes, volume, and surface area of the ground‐truth object and the reconstructed models was >0.97 and root‐mean square error (RMSE) was < 3 mm for objects without locally concave regions. Measurements from 1 mm and 2 mm resolution reconstructions were consistent (R2 > 0.99). Qualitative assessments were performed on 48 fruit and tubers, including 18 strawberries, 12 potatoes, five grapes, seven peppers, and four Bosc and two red Anjou pears. Our proposed phenotyping system is fast, relatively low cost, and has demonstrated accuracy for certain shape classes, and could be used for the 3D analysis of fruit form.https://doi.org/10.1002/ppj2.20029 |
spellingShingle | Mitchell J. Feldmann Amy Tabb Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form Plant Phenome Journal |
title | Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form |
title_full | Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form |
title_fullStr | Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form |
title_full_unstemmed | Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form |
title_short | Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form |
title_sort | cost effective high throughput phenotyping system for 3d reconstruction of fruit form |
url | https://doi.org/10.1002/ppj2.20029 |
work_keys_str_mv | AT mitchelljfeldmann costeffectivehighthroughputphenotypingsystemfor3dreconstructionoffruitform AT amytabb costeffectivehighthroughputphenotypingsystemfor3dreconstructionoffruitform |