ArticleAnalytical and bioanalytical chemistry2019
Application of laser-induced breakdown spectroscopy (LIBS) coupled with PCA for rapid classification of soil samples in geothermal areas.
Article in Analytical and bioanalytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- LIBS-Based Chemometric and Machine-Learning Approach for Detecting Adulteration in Açaí Pulp.ACS omega · 2026Article
- Article
- Application and Research Progress of Laser-Induced Breakdown Spectroscopy in Agricultural Product Inspection.ACS omega · 2024Review
- Rapid classification of whole milk powder and skimmed milk powder by laser-induced breakdown spectroscopy combined with feature processing method and logistic regression.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2024Article
- Quantitative analysis of fertilizer using laser-induced breakdown spectroscopy combined with random forest algorithm.Frontiers in chemistry · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Manuguru geothermal area, located in the Telangana state, is one of the least explored geothermal fields in India. In this study, characterization of the soil samples is carried out by laser-induced breakdown spectroscopy (LIBS) coupled with analytical spectral-dependent principal component analysis. A total of 20 soil samples were collected both from near the thermal discharges as well as away from the thermal manifestations. LIBS spectra were recorded for all the collected soil samples and principal component analysis (PCA) was applied to easily identify the emission lines majorly responsible for variety classification of the soil samples. In this submission, a modified PCA was developed which is based on the spectral truncation method to reduce the huge number of spectral data obtained from LIBS. The PCA bi-plot on the LIBS data reveals the presence of two different clusters. One cluster represents the soil samples collected from the close vicinity of the thermal manifestations whereas the other cluster contains the soil samples collected away from the thermal sprouts. PCA performed on the chemical dataset of the soil samples also reveals the same clustering of the soil samples. Both LIBS and chemical analysis data shows that soil samples near the thermal waters are found to be enriched in B, Sr, Cs, Rb, Fe, Co, Al, Si, Ti, Ru, Mn, Mg, Cu, and Eu concentrations compared to the soil samples located away from thermal manifestations. This study demonstrates the potential use of LIBS coupled with PCA as a tool for variety discrimination of soil samples in a geothermal area. LIBS is shown to be a viable real-time elemental characterization technology for these samples, avoiding the rigorous dissolution required by other analytical techniques.
Indexed as
Identifiers
30879114What OpenQuestion holds
Registered trials
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.