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Related Concept Videos

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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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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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

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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...
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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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IR Frequency Region: X–H Stretching01:24

IR Frequency Region: X–H Stretching

1.1K
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...
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Fourier transform infrared spectrum pre-processing technique selection for detecting PYLCV-infected chilli plants.

Dyah K Agustika1, Ixora Mercuriani2, Chandra W Purnomo3

  • 1School of Engineering, University of Warwick, Coventry CV4 7AL, UK; Department of Physics Education, Universitas Negeri Yogyakarta, Yogyakarta, 55281 Indonesia.

Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|May 10, 2022
PubMed
Summary
This summary is machine-generated.

Optimizing pre-processing techniques for Fourier transform infrared (FTIR) spectroscopy significantly enhances the detection of pepper yellow leaf curl virus (PYLCV)-infected chilli plants. The Savitzky-Golay 1st derivative method achieved 100% accuracy in classification.

Keywords:
ClassificationFourier transform infrared spectroscopyPlant disease detectionPre-processing

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Area of Science:

  • Agricultural Science
  • Spectroscopy
  • Plant Pathology

Background:

  • Fourier transform infrared (FTIR) spectroscopy is valuable for analyzing plant health.
  • Effective pre-processing is essential to reduce noise and improve accuracy in spectral analysis.
  • Detecting plant diseases like pepper yellow leaf curl virus (PYLCV) in chilli plants requires robust analytical methods.

Purpose of the Study:

  • To optimize pre-processing techniques for FTIR spectroscopy to detect PYLCV-infected chilli plants.
  • To evaluate the impact of different pre-processing methods on classification accuracy.
  • To identify the most effective pre-processing strategy for simplified and accurate disease detection.

Main Methods:

  • Applied various pre-processing techniques: baseline correction, normalization (SNV, vector, min-max), and de-noising (Savitzky-Golay (SG) smoothing, 1st/2nd derivatives).
  • Utilized discrete wavelet transform (DWT) for dimension reduction on spectral data (mid-IR and biofingerprint regions).
  • Employed classification algorithms: multilayer perceptron neural network, support vector machine, and linear discriminant analysis.

Main Results:

  • The Savitzky-Golay (SG) 1st derivative method, applied to both spectral ranges, achieved 100% classification accuracy.
  • Principal component analysis (PCA) clustering supported the high accuracy of the selected pre-processing method.
  • Optimized pre-processing simplified the classification process and increased success rates.

Conclusions:

  • The correct selection and optimization of pre-processing techniques are critical for enhancing FTIR spectroscopy-based plant disease detection.
  • The SG 1st derivative method offers a highly effective and accurate approach for identifying PYLCV infection in chilli plants.
  • This study demonstrates the potential of optimized FTIR spectroscopy for efficient and accurate agricultural disease diagnostics.