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Related Concept Videos

Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

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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,...
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Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

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Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
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IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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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...
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IR Spectrometers01:25

IR Spectrometers

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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

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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...
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Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

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The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
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Related Experiment Video

Updated: Jan 7, 2026

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
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STAR: Soil texture analysis recognizer integrating domain-adaptive transfer learning with NIR spectroscopy.

Yuchen Luo1, Zeyuan Zhang1, Siyu Liu1

  • 1School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Journal of Environmental Management
|December 26, 2025
PubMed
Summary

A new Soil Texture Analysis Recognizer (STAR) uses near-infrared (NIR) spectroscopy and deep learning for accurate soil classification. This intelligent device overcomes data limitations, enabling precise soil analysis in diverse agricultural and environmental applications.

Keywords:
Near-infrared spectraSelective enhanced transfer adaptive boostingSoil textures classificationTransfer learningTransfer multiplicative scatter correction

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Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
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Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
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Area of Science:

  • Soil Science
  • Spectroscopy
  • Artificial Intelligence

Background:

  • Soil texture is crucial for agriculture and land management.
  • Near-infrared (NIR) spectroscopy offers a rapid, non-destructive alternative to traditional soil analysis.
  • Current NIR methods face challenges in model generalization and data dependency.

Purpose of the Study:

  • To introduce the Soil Texture Analysis Recognizer (STAR), an intelligent NIR-based device for precise soil texture classification.
  • To develop a domain-adaptive deep learning strategy to improve model generalization and reduce cross-domain inconsistencies.
  • To address limitations in current NIR spectroscopy applications for soil analysis.

Main Methods:

  • Development of the Soil Texture Analysis Recognizer (STAR) device.
  • Implementation of a transfer learning-based spectral preprocessing method (Transfer Multiplicative Scatter Correction - TMSC).
  • Utilizing the Selective Enhanced Transfer Adaptive Boosting (SETAB) framework for enhanced model adaptability.

Main Results:

  • STAR achieved 85.0% overall classification accuracy and a Kappa coefficient of 0.78 for 5 soil texture classes.
  • Successfully identified previously unseen soil types, including loamy sand (100.0%) and sandy loam (66.7%).
  • Demonstrated robust generalization capability and practical utility for soil texture analysis.

Conclusions:

  • The STAR device and its domain-adaptive deep learning strategy offer a significant advancement in soil texture analysis.
  • The proposed methods provide a feasible solution for bridging deep learning-assisted spectral modeling with real-world applications.
  • STAR presents a scalable platform for broader NIR-based soil property measurements.