Evidence map›Paper›PMID 39564483›Full record

ArticleFrontiers in microbiology2024

Prediction of the impact of tobacco waste hydrothermal products on compost microbial growth using hyperspectral imaging combined with machine learning.

Dandan Liu, Xinxin Ma, Changwen Ye, Yiying Jin, Kuo Huang, Chenqi Niu, Ge Zhang, Dong Li, Linzhi Ma, Suxiao Li and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 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

11 authors.

Dandan LiuChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.
Xinxin MaSchool of Environment, Tsinghua University, Beijing, China.
Changwen YeChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.
Yiying JinSchool of Environment, Tsinghua University, Beijing, China.
Kuo HuangChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.
Chenqi NiuChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.
Ge ZhangChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.
Dong LiChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.
Linzhi MaCollege of Physical Engineering, Zhengzhou University, Zhengzhou, China.
Suxiao LiCollege of Physical Engineering, Zhengzhou University, Zhengzhou, China.
Guotao YangChina Tobacco Standardization Research Center, Zhengzhou Tobacco Research Institute, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The insufficient understanding of the impact of hydrothermal products on the growth characteristics of compost microorganisms presents a significant challenge to the broader implementation of hydrothermal coupled composting for tobacco waste. Traditional biochemical detection methods are labor-intensive and time-consuming, highlighting the need for faster and more accurate alternatives. This study investigated the effects of hydrothermal treatment on tobacco straw products and their influence on compost microorganism growth, using hyperspectral imaging (HSI) technology and machine learning algorithms. Sixty-one tobacco straw samples were analyzed with a hyperspectral camera, and image processing was used to extract average spectra from regions of interest (ROI). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to assess four key variables: nicotine content, total humic acid content,

Indexed as

compostinghydrothermalhyperspectral imagingmachine learningtobacco waste

Identifiers

PMID39564483
PMCPMC11573759

What OpenQuestion holds

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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.