Evidence map›Paper›PMID 31844597›Full record

ArticlePeerJ2019

Quantitative estimation of wastewater quality parameters by hyperspectral band screening using GC, VIP and SPA.

Zheng Xing, Junying Chen, Xiao Zhao, Yu Li, Xianwen Li, Zhitao Zhang, Congcong Lao, Haifeng Wang

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
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

3 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Article
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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

8 authors at 1 institution in 1 country.

Zheng XingKey Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, Shaanxi, China.
Junying ChenKey Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, Shaanxi, China.
Xiao ZhaoKey Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, Shaanxi, China.
Yu LiCollege of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi, China.
Xianwen LiCollege of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi, China.
Zhitao ZhangKey Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, Shaanxi, China.
Congcong LaoCollege of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi, China.
Haifeng WangCollege of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi, China.ORCID 0000-0002-3771-4504
Northwest A&F University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water pollution has been hindering the world's sustainable development. The accurate inversion of water quality parameters in sewage with visible-near infrared spectroscopy can improve the effectiveness and rational utilization and management of water resources. However, the accuracy of spectral models of water quality parameters is usually prone to noise information and high dimensionality of spectral data. This study aimed to enhance the model accuracy through optimizing the spectral models based on the sensitive spectral intervals of different water quality parameters. To this end, six kinds of sewage water taken from a biological sewage treatment plant went through laboratory physical and chemical tests. In total, 87 samples of sewage water were obtained by adding different amount of pure water to them. The raw reflectance (R

Indexed as

Band screenExtreme learning machineGray correlation methodHyperspectral remote sensingSet pair analysisVariable importance projection analysis

Identifiers

PMID31844597
PMCPMC6911691
OpenAlexW2995308072

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.