Evidence map›Paper›PMID 33073164›Full record

ArticlePlant direct2020

Voxel carving-based 3D reconstruction of sorghum identifies genetic determinants of light interception efficiency.

Mathieu Gaillard, Chenyong Miao, James C Schnable, Bedrich Benes

Abstract read
In one paragraph

Article in Plant direct, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mathieu GaillardDepartment of Computer Graphics Technology Purdue University West Lafayette IN USA.ORCID https://orcid.org/0000-0003-0840-5654
Chenyong MiaoCenter for Plant Science Innovation and Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE USA.ORCID https://orcid.org/0000-0002-0904-3707
James C SchnableCenter for Plant Science Innovation and Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE USA.ORCID https://orcid.org/0000-0001-6739-5527
Bedrich BenesDepartment of Computer Graphics Technology Purdue University West Lafayette IN USA.ORCID https://orcid.org/0000-0002-5293-2112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in canopy architecture traits have been shown to contribute to yield increases. Optimizing both light interception and light interception efficiency of agricultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three-dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two-dimensional (2D) structure to make large scale measurement, selective breeding, and gene identification logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving algorithm to allow for fully automatic reconstruction of hundreds of plants. It was employed to generate 3D reconstructions of individual plants within a sorghum association population at the late vegetative stage of development. Light interception parameters estimated from these reconstructions enabled the identification of known and previously unreported loci controlling light interception efficiency in sorghum. The approach is generalizable and scalable, and it enables 3D reconstructions from existing plant high throughput phenotyping datasets. We also propose a set of best practices to increase 3D reconstructions' accuracy.

Indexed as

3D plant reconstructionphenotypingquantitative geneticssorghum

Identifiers

PMID33073164
PMCPMC7541904

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.