Cost‐effective, high‐throughput phenotyping system for 3D reconstruction of fruit form. Issue 1 (18th February 2022)

• Record Type: Journal Article
• Authors: Feldmann, Mitchell J.; Tabb, Amy
• Is Part Of: Plant phenome journal. Volume 5:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-18
• Subjects: Phenotype -- Periodicals; Plant genetics -- Periodicals; Periodicals; 581.35
• DOI: 10.1002/ppj2.20029
• Languages: English
• ISSNs: 2578-2703

Abstract

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 R 2 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 ( R 2 > 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. Core Ideas: A low‐cost 3D fruit phenotyping system is presented. Image capture using the proposed approach lasts for only 9 s. Accuracy is measured against 3D printed ground‐truth objects. Camera calibration, background segmentation, and reconstruction does not rely on commercial software. An RMSE less than 3 mm was obtained for ground truth objects without locally concave regions.