Evidence map›Paper›PMID 37693634›Full record

ArticleHardwareX2023

SPOT: Scanning plant IoT facility for high-throughput plant phenotyping.

Stephen Lantin, Kelli McCourt, Nicholas Butcher, Varun Puri, Martha Esposito, Sasha Sanchez, Francisco Ramirez-Loza, Eric McLamore, Melanie Correll, Aditya Singh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in HardwareX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Stephen LantinDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
Kelli McCourtDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
Nicholas ButcherDepartment of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA.
Varun PuriDepartment of Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA.
Martha EspositoDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
Sasha SanchezDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
Francisco Ramirez-LozaDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
Eric McLamoreDepartment of Agricultural Sciences, Clemson University, SC 29634, USA.
Melanie CorrellDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
Aditya SinghDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many plant phenotyping platforms have been kept out of the reach of smaller labs and institutions due to high cost and proprietary software. The Scanning Plant IoT (SPOT) Facility, located at the University of Florida, is a mobile, laboratory-based platform that facilitates open-source collection of high-quality, interoperable plant phenotypic data. It consists of three main sensors: a hyperspectral sensor, a thermal camera, and a LiDAR camera. Real-time data from the sensors can be collected in its 10 ft. × 10 ft. scanning region. The mobility of the device allows its use in large growth chambers, environmentally controlled rooms, or greenhouses. Sensors are oriented nadir and positioned via computer numerical control of stepper motors. In a preliminary experiment, data gathered from SPOT was used to autonomously and nondestructively differentiate between cultivars.

Indexed as

Hyperspectral imagingPlant breedingPlant phenotypingRemote sensingThermal imaging

Identifiers

PMID37693634
PMCPMC10485143

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.