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Related Concept Videos

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
The...
IR Spectrum01:19

IR Spectrum

When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0% (complete...
Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

The non-destructive nature and ability to provide valuable chemical information make IR spectroscopy a versatile technique with broad applications in various scientific and industrial fields. IR spectroscopy is commonly used to identify and characterize organic and inorganic compounds. It provides information about the functional groups present in a molecule and the bonding between atoms. This helps in the structural elucidation of compounds during organic synthesis, pharmaceutical research,...
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...
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in the 3500–3100 cm−1 range. Even though both O−H and N−H bonds vibrate at a similar...

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Related Experiment Video

Updated: Jun 19, 2026

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
08:57

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions

Published on: January 10, 2019

[NIR spectral analysis for soil textural classification].

Qing-Meng Zeng1, Yu-Rui Sun, Hong-Bing Yan

  • 1College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China. zengqingmeng@yahoo.com.cn

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|October 6, 2009
PubMed
Summary
This summary is machine-generated.

Near-infrared (NIR) spectroscopy shows potential for soil texture classification, with improved accuracy when considering specific soil compositions and advanced spectral data acquisition methods.

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Last Updated: Jun 19, 2026

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
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Published on: January 10, 2019

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

Published on: November 8, 2019

Area of Science:

  • Soil Science
  • Analytical Chemistry
  • Spectroscopy

Context:

  • Soil texture is a fundamental property influencing soil behavior and function.
  • Accurate soil textural classification is crucial for various agricultural and environmental applications.
  • Traditional methods for soil texture analysis can be time-consuming and labor-intensive.

Purpose:

  • To investigate the efficacy of Near-Infrared (NIR) spectroscopy for soil textural classification.
  • To evaluate the influence of different spectral methods, ranges, and sampling intervals on classification accuracy.
  • To identify factors that can enhance the predictive performance of NIR spectroscopy for soil texture.

Summary:

  • The study utilized 25 soil samples with known compositions and explored two NIR instruments, three spectral methods, three spectral ranges, and three sampling intervals.
  • Results indicated that spectral curve peaks relate to chemical information, while slope and intercept reflect physical soil properties, with varying intensities across spectra.
  • NIR's distinguishing ability was found to be limited by the classification criteria, achieving a maximum prediction probability of 72%, but reaching 85% for specific sand and clay content ranges.
  • Acquiring surface scatter information or extending spectral bands showed potential for improving prediction accuracy.

Impact:

  • Demonstrates the feasibility of using NIR spectroscopy as a rapid, non-destructive method for soil textural analysis.
  • Highlights the importance of selecting appropriate spectral analysis techniques and data processing for optimal classification.
  • Suggests avenues for future research, such as incorporating scatter information and broader spectral bands to enhance predictive models for soil texture.