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

Moisture Content and Bulking of Aggregate01:10

Moisture Content and Bulking of Aggregate

599
The moisture content of aggregates is a crucial factor in construction, particularly in concrete mixing, as it influences the total water required in the mix. Moisture content represents the water coated on the exterior surface of the aggregate existing in a saturated and surface-dry condition. The total water content of a moist aggregate is the sum of its moisture content and water absorption.
When aggregates are exposed to rain or sit in stockpiles, they absorb moisture, which must be...
599
UV–Vis Spectroscopy: Woodward–Fieser Rules01:29

UV–Vis Spectroscopy: Woodward–Fieser Rules

29.7K
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 structure by adding the...
29.7K
IR and UV–Vis Spectroscopy of Aldehydes and Ketones01:29

IR and UV–Vis Spectroscopy of Aldehydes and Ketones

7.9K
Infrared spectroscopy, also known as vibrational spectroscopy, is mainly used to determine the types of bonds and functional groups in molecules. In aldehydes and ketones, the carbonyl (C=O) bond shows an absorption around 1710 cm-1. The C=O bond vibration of an aldehyde occurs at lower frequencies than that of a ketone. In addition to the C=O absorption in an aldehyde, the aldehydic C–H bond also gives two peaks in the 2700–2800 cm-1 range. This absorption, coupled with the...
7.9K
IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

3.8K
A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to...
3.8K
UV–Vis Spectroscopy of Conjugated Systems01:32

UV–Vis Spectroscopy of Conjugated Systems

9.2K
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 of conjugation in...
9.2K
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

1.6K
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...
1.6K

You might also read

Related Articles

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

Sort by
Same author

Performance Improvement of Handheld Raman Spectrometer for Mixture Components Identification Using Fuzzy Membership and Sparse Non-Negative Least Squares.

Applied spectroscopy·2022
Same author

Preexisting human antibodies neutralize recently emerged H7N9 influenza strains.

The Journal of clinical investigation·2015
Same author

Inhibitory effects of B-cell lymphoma 2 on the vasculogenic mimicry of hypoxic human glioma cells.

Experimental and therapeutic medicine·2015
Same author

Simultaneous determination of seven taxoids in rat plasma by UPLC-MS/MS and pharmacokinetic study after oral administration of Taxus yunnanensis extracts.

Journal of pharmaceutical and biomedical analysis·2015
Same author

Core muscle strength and endurance measures in ambulatory persons with multiple sclerosis: validity and reliability.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation·2015
Same author

The kinase MST4 limits inflammatory responses through direct phosphorylation of the adaptor TRAF6.

Nature immunology·2015

Related Experiment Video

Updated: Apr 7, 2026

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

7.1K

Non-Destructive Determination of Moisture Content in Husk-On Fresh Corn Using Multichannel Visible-Near-Infrared

Min Xu1, Xin Zhao1, Yanping Chen2

  • 1Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, China.

Applied Spectroscopy
|April 6, 2026
PubMed
Summary

Accurate moisture content (MC) detection in husk-on fresh corn is challenging due to husk interference. A multichannel Vis-NIR system with deep learning fusion significantly improved MC prediction accuracy, offering a practical solution.

Keywords:
Husk-on fresh cornVis-NIRZea maize L. sinensis Kuleshdeep learningdetection modelmoisture contentmultichannel visible–near-infrared spectroscopy

More Related Videos

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

11.3K
Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

10.0K

Related Experiment Videos

Last Updated: Apr 7, 2026

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

7.1K
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

11.3K
Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

10.0K

Area of Science:

  • Agricultural Engineering
  • Spectroscopy
  • Machine Learning

Background:

  • Accurate, non-destructive determination of moisture content (MC) in husk-on fresh corn is vital for quality control and harvesting optimization.
  • Corn husks significantly interfere with spectroscopic analysis, reducing the accuracy of MC detection in kernels.
  • Existing methods struggle to overcome husk-induced spectral noise, necessitating advanced approaches.

Purpose of the Study:

  • To develop a multichannel visible and near-infrared (Vis-NIR) spectral acquisition system for accurate MC determination in husk-on fresh corn.
  • To mitigate husk interference using spatially resolved diffuse reflectance technology and multichannel data collection.
  • To compare deep learning-based fusion strategies (feature-level, data-level, decision-level) for MC prediction.

Main Methods:

  • Development of a multichannel Vis-NIR spectral acquisition system utilizing spatially resolved diffuse reflectance.
  • Collection of spectral data from multiple detection positions to minimize husk interference.
  • Application and comparison of three deep learning fusion models: feature-level, data-level, and decision-level fusion.
  • Utilized standard normal variate (SNV) preprocessing for model optimization.

Main Results:

  • The decision-level fusion model, combined with SNV preprocessing, achieved the highest prediction accuracy (R²p = 0.897, RMSEP = 4.13%).
  • Multichannel data acquisition demonstrably enhanced model performance, with a four-channel combination yielding optimal results.
  • Deep learning frameworks effectively integrated spectral information from multiple channels.

Conclusions:

  • Deep learning and multichannel spectral data fusion offer a robust and practical solution for non-destructive MC measurement in fresh corn.
  • The developed system successfully overcomes husk interference, paving the way for improved quality assessment in agriculture.
  • This approach holds significant potential for optimizing fresh corn management from harvest to storage.