Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Quantitative Analysis

Quantitative Analysis

Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...

Atomic Spectroscopy: Absorption, Emission, and Fluorescence

Atomic Spectroscopy: Absorption, Emission, and Fluorescence

Atomic spectroscopy is a vital tool in elemental analysis, both qualitatively and quantitatively. It can be broadly divided into optical spectroscopy, mass spectroscopy, and X-ray spectroscopy methods. The optical spectroscopic methods are atomic absorption spectroscopy (AAS), atomic emission spectroscopy (AES), and atomic fluorescence spectroscopy (AFS). The first step in all three methods is atomization, where the solid, liquid, or solution-phase samples are converted into gas-phase atoms and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Apoptosis-inducing effect and structural basis of Polygonatum cyrtonema lectin and chemical modification properties on its mannose-binding sites.

BMB reports·2008

Same author

The catalytic intermediate stabilized by a "down" active site loop for diaminopimelate decarboxylase from Helicobacter pylori. Enzymatic characterization with crystal structure analysis.

The Journal of biological chemistry·2008

Same author

Monitoring prostate thermal therapy with diffusion-weighted MRI.

Magnetic resonance in medicine·2008

Same author

Removal of ammonia nitrogen in wastewater by microwave radiation.

Journal of hazardous materials·2008

Same author

[Three-dimensional anatomical position of rotatory center in cervical rotatory and local manipulation].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University·2008

Same author

Dysregulation of CREB binding protein triggers thrombin-induced proliferation of vascular smooth muscle cells.

Molecular and cellular biochemistry·2008

Search research articles

Related Experiment Video

Updated: Aug 12, 2025

Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants

Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants

Published on: September 23, 2013

Quantitative analysis of fertilizer using laser-induced breakdown spectroscopy combined with random forest algorithm.

Lai Wei^1,2,3, Yu Ding^1,2,3, Jing Chen^1,2,3

¹Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China.

Frontiers in Chemistry

|January 30, 2023

Summary

Laser-induced breakdown spectroscopy combined with the random forest (RF) algorithm offers a rapid and accurate method for determining soil chemical fertilizer content. This approach significantly outperforms partial least squares (PLS) models for soil analysis.

Keywords:

LIBS PLS RF fertilizer pH

More Related Videos

Quantitative Analysis of Vacuum Induction Melting by Laser-induced Breakdown Spectroscopy

Quantitative Analysis of Vacuum Induction Melting by Laser-induced Breakdown Spectroscopy

Published on: June 10, 2019

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

Related Experiment Videos

Last Updated: Aug 12, 2025

Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants

Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants

Published on: September 23, 2013

Quantitative Analysis of Vacuum Induction Melting by Laser-induced Breakdown Spectroscopy

Quantitative Analysis of Vacuum Induction Melting by Laser-induced Breakdown Spectroscopy

Published on: June 10, 2019

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

Area of Science:

Agricultural Science
Analytical Chemistry
Spectroscopy

Background:

Chemical fertilizers are crucial for enhancing soil fertility, crop growth, and yield.
Accurate and rapid methods for measuring soil fertilizer content are essential for optimizing agricultural practices.

Purpose of the Study:

To develop and evaluate a rapid method for determining soil chemical fertilizer content and pH.
To compare the predictive performance of partial least squares (PLS) and random forest (RF) models using laser-induced breakdown spectroscopy (LIBS).

Main Methods:

Analysis of 20 soil samples using laser-induced breakdown spectroscopy (LIBS).
Development and comparison of partial least squares (PLS) and random forest (RF) chemometric models.
Evaluation of model performance using R-squared (R²) and root mean square error (RMSE) metrics.

Main Results:

The random forest (RF) model demonstrated superior prediction performance for both chemical fertilizer content and soil pH compared to the PLS model.
RF model achieved an R² of .9471 for fertilizer content and .9517 for soil pH, with significant reductions in RMSE.
PLS model yielded R² values of .7852 for fertilizer content and .7290 for soil pH.

Conclusions:

The combination of laser-induced breakdown spectroscopy (LIBS) with the random forest (RF) algorithm is a feasible and effective method for the rapid determination of soil fertilizer content.
The RF model significantly improves prediction accuracy and efficiency over the PLS model for LIBS-based soil analysis.