Evidence map›Paper›PMID 39324688›Full record

ArticleAnalytical chemistry2024

Computer Vision-Assisted Robotized Sampling of Volatile Organic Compounds.

Ching-Chi Chan, Noor Hidayat Abu Bakar, Chamarthi Maheswar Raju, Pawel L Urban

Abstract read
In one paragraph

Article in Analytical chemistry, 2024. 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

4 authors.

Ching-Chi ChanDepartment of Chemistry, National Tsing Hua University, 101, Section 2, Kuang-Fu Rd., Hsinchu 300044, Taiwan.
Noor Hidayat Abu BakarDepartment of Chemistry, National Tsing Hua University, 101, Section 2, Kuang-Fu Rd., Hsinchu 300044, Taiwan.
Chamarthi Maheswar RajuDepartment of Chemistry, National Tsing Hua University, 101, Section 2, Kuang-Fu Rd., Hsinchu 300044, Taiwan.
Pawel L UrbanDepartment of Chemistry, National Tsing Hua University, 101, Section 2, Kuang-Fu Rd., Hsinchu 300044, Taiwan.ORCID 0000-0003-3471-045X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In conventional chemical analysis, samples are homogenized, extracted, purified, and injected into an analytical instrument manually or with a certain degree of automation. Such complex methods can provide superior performance in terms of sensitivity or selectivity. However, in some cases, it would be advantageous to possess a method that circumvents those preparatory steps, which require much attention. Here, we present a facile analytical approach to sampling volatile organic compounds (VOCs). Solid specimens emitting VOCs can be dropped onto the drop-off zone at a random position without any special alignment. A computer vision system recognizes specimen position, and a robotic arm places a sampling probe in the proximity of the specimen. The probe aspirates the VOCs─emitted by the specimen─with the aid of a suction force. A portion of the gaseous extract is transferred to the tritium-based ion source of a drift-tube ion mobility spectrometer. The ion mobility spectrum is immediately displayed in the customized graphical user interface (GUI). The sampling system also features a function for flushing extract ducts with hot nitrogen gas. Multiple specimens can be dropped for analysis at the same time. In one embodiment, the system can distinguish fresh meat from spoiled meat. When two meat specimens are placed on the drop-off zone, they are immediately sampled by the robotic arm, analyzed, and labeled on the digital image displayed on the GUI. Thus, the developed autosampling platform provides a hassle-free way of qualitative or semiquantitative analysis of raw specimens.

Identifiers

PMID39324688
PMCPMC11483429

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.