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

UV–Vis Spectroscopy: Woodward–Fieser Rules01:29

UV–Vis Spectroscopy: Woodward–Fieser Rules

25.2K
UV–Visible absorption spectra of conjugated dienes arise from the lowest energy π → π* transitions. The light-absorbing part of the molecule is called the chromophore, and the substituents directly attached to the chromophore are called auxochromes. A strong correlation exists between the absorption maxima, λmax, and the structure of a conjugated π system. The Woodward–Fieser rules predict the value of λmax for a given...
25.2K
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

1.0K
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...
1.0K
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

499
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...
499
Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview01:02

Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview

2.9K
Ultraviolet–visible (UV–visible or UV–Vis) spectroscopy is an analytical technique that investigates the interaction between matter and UV–Vis light within the electromagnetic spectrum. This method is widely used for its versatility, simplicity, and relatively quick data acquisition, making it valuable for both qualitative and quantitative analysis. When UV–Vis radiation passes through a material,  molecules absorb light depending on the energy required for...
2.9K
Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

986
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,...
986
UV–Vis Spectroscopy of Conjugated Systems01:32

UV–Vis Spectroscopy of Conjugated Systems

7.2K
Organic compounds with conjugated double bonds show strong absorption features in the UV–visible region of the electromagnetic spectrum attributed to π → π* electronic excitations. Generally, a UV–vis absorption spectrum is recorded as a plot of absorbance vs wavelength. The wavelength of maximum absorbance, which manifests as a peak in the absorption spectrum, is denoted as λmax.
One of the factors influencing λmax is the extent...
7.2K

You might also read

Related Articles

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

Sort by
Same author

Fabricating pentaazatetraethylene modified sulfonated polyacrylamide for dye adsorption from aqueous media: isotherms and kinetics models.

Environmental science and pollution research international·2024
Same author

Urban Heat Island Monitoring and Impacts on Citizen's General Health Status in Isfahan Metropolis: A Remote Sensing and Field Survey Approach.

Remote sensing·2022
Same author

Scenario-based discrimination of common grapevine varieties using in-field hyperspectral data in the western of Iran.

International journal of applied earth observation and geoinformation : ITC journal·2022
Same author

Eco-Friendly Estimation of Heavy Metal Contents in Grapevine Foliage Using In-Field Hyperspectral Data and Multivariate Analysis.

Remote sensing·2022
Same author

Transboundary Basins Need More Attention: Anthropogenic Impacts on Land Cover Changes in Aras River Basin, Monitoring and Prediction.

Remote sensing·2022
Same author

Optimizing cropping pattern to improve the performance of irrigation network using system dynamics-Powell algorithm.

Environmental science and pollution research international·2022

Related Experiment Video

Updated: Aug 29, 2025

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

10.7K

Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques.

Mozhgan Abbasi1, Jochem Verrelst2, Mohsen Mirzaei3

  • 1Faculty of Natural Resource and Earth Science, Shahrekord University, Shahrekord 8815648456, Iran.

Remote Sensing
|September 9, 2022
PubMed
Summary
This summary is machine-generated.

Hyperspectral imaging effectively maps orchard tree species using optimized wavelengths. This precision agriculture approach aids sustainable management by distinguishing almond, walnut, and grape varieties.

Keywords:
ANOVA–RFC–PCAPLSdiscriminant analysisfield spectroscopyoptimal spectral wavelengthsorchards species

More Related Videos

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols
11:37

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Published on: August 8, 2017

16.3K
O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

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

Published on: November 8, 2019

6.7K

Related Experiment Videos

Last Updated: Aug 29, 2025

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

10.7K
RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols
11:37

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Published on: August 8, 2017

16.3K
O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

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

Published on: November 8, 2019

6.7K

Area of Science:

  • Agricultural Science
  • Remote Sensing
  • Spectroscopy

Background:

  • Sustainable orchard management relies on accurate tree species identification.
  • Precision agriculture programs benefit from detailed tree inventory data.
  • Hyperspectral imagery offers a promising tool for orchard tree species mapping.

Purpose of the Study:

  • To identify optimal wavelengths for discriminating between dominant orchard tree species using hyperspectral data.
  • To develop and compare two multivariable methods for band selection in hyperspectral analysis.
  • To assess the spectral separability of almond, walnut, and grape species.

Main Methods:

  • Field spectroscopy was conducted on 165 leaf samples across the 350-2500 nm range.
  • Two multivariable approaches were employed: ANOVA-RFC-PCA and Partial Least Squares (PLS).
  • Discriminant analysis (DA) was used to evaluate species separation and identify optimal wavelengths.

Main Results:

  • Distinct spectral behaviors were observed in the visible, red edge, and near-infrared ranges.
  • The ANOVA-RFC-PCA method reduced wavelengths to five key values (363, 423, 721, 1064, 1388 nm).
  • The PLS-DA model achieved 100% accuracy with optimal wavelengths at 397, 515, 647, 1386, and 1919 nm.

Conclusions:

  • Hyperspectral data combined with optimized band selection effectively distinguishes orchard tree species.
  • The identified optimal wavelengths provide a basis for developing accurate tree species mapping algorithms.
  • This research supports precision agriculture and sustainable orchard management practices.