Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...
Atomic Absorption Spectroscopy: Interference01:25

Atomic Absorption Spectroscopy: Interference

Interference leads to systematic error in atomic absorption (AA) measurements by enhancing or diminishing the analytical signal or the background. These interferences can be grouped into three main categories: spectral interference, chemical interference, and physical interference.
Spectral interference occurs when signals from other elements or molecules overlap with the analyte signal, falsely elevating or masking the analyte's absorbance. This interference can be corrected using Zeeman,...
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used.
Atomic Emission Spectroscopy: Interference01:30

Atomic Emission Spectroscopy: Interference

In atomic emission spectroscopy (AES), high-temperature atomizers excite a broad range of elements and molecules that generate complex emissions from sources such as oxides, hydroxides, and flame combustion products in the flame or plasma. Several strategies can be employed to minimize spectral interferences caused by overlapping emission lines or bands. These include increasing instrument resolution, choosing alternative emission lines, optimally placing the detector in low-background regions,...

You might also read

Related Articles

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

Sort by
Same author

Endobiliary Photodynamic Therapy in Cholangiocarcinoma: Clinical Outcomes, Patient Selection, and Procedural Context.

Current oncology (Toronto, Ont.)·2026
Same author

Fe(III)-Induced Satellite Structural Evolution of Ag@G Nanoparticles Toward Ultrasensitive Detection of Trace Drugs in Mice Serum.

Chemistry (Weinheim an der Bergstrasse, Germany)·2026
Same author

Electron-permeable graphitic atomic barrier confers paradoxical enhancement of fibrosarcoma apoptosis by Ptzymes.

Biomaterials·2026
Same author

Dihydromyricetin attenuates LPS-induced liver injury in chicks through the JNK signaling pathway.

Research in veterinary science·2026
Same author

Metformin Induces Ferroptosis and Inhibits Malignant Progression in Diabetic Breast Cancer.

Applied biochemistry and biotechnology·2026
Same author

Experimental hepatitis E virus genotype 1 infection in three types of wild rodents.

PLoS pathogens·2026

Related Experiment Video

Updated: Jun 6, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Asymmetric least squares for multiple spectra baseline correction.

Jiangtao Peng1, Silong Peng, An Jiang

  • 1Institute of Automation, Chinese Academy of Sciences, Beijing 100190, PR China. jiangtao.peng@ia.ac.cn

Analytica Chimica Acta
|November 25, 2010
PubMed
Summary

A novel algorithm using asymmetric least squares smoothing corrects multiple spectra baselines by penalizing differences, effectively removing scatter effects. This efficient method simultaneously processes multiple spectra, demonstrating strong performance on simulated and real data.

More Related Videos

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
06:03

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells

Published on: June 23, 2023

Related Experiment Videos

Last Updated: Jun 6, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
06:03

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells

Published on: June 23, 2023

Area of Science:

  • Spectroscopy
  • Chemometrics
  • Data Analysis

Background:

  • Baseline drift and scatter effects are common challenges in spectroscopic data analysis.
  • Accurate baseline correction is crucial for reliable quantitative and qualitative analysis of spectral data.
  • Existing methods may struggle with complex spectral matrices or exhibit limited efficiency.

Purpose of the Study:

  • To develop a new, efficient algorithm for correcting baselines in multiple spectra simultaneously.
  • To address and mitigate scatter effects present in spectroscopic signals.
  • To improve the accuracy and reliability of spectral data analysis.

Main Methods:

  • A novel algorithm based on asymmetric least squares smoothing is proposed.
  • The algorithm estimates baselines by penalizing differences in baseline-corrected signals, leveraging spectral similarity.
  • An optimization model incorporating a relaxation factor and an alternate iteration strategy is employed.

Main Results:

  • The algorithm effectively eliminates scatter effects from spectroscopic data.
  • It demonstrates the capability to output multiple baselines concurrently.
  • Experimental validation on both simulated and real datasets confirms its effectiveness and efficiency.

Conclusions:

  • The proposed asymmetric least squares-based algorithm provides an effective and efficient solution for multiple spectra baseline correction.
  • The method successfully handles scatter effects and offers simultaneous baseline estimation.
  • This approach enhances the utility of spectroscopic techniques in various scientific domains.