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

You might also read

Related Articles

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

Sort by
Same author

Enriched environment inhibits melanoma by reshaping gut microbiota and enriching Parabacteroides distasonis.

Cellular oncology (Dordrecht, Netherlands)·2026
Same author

Genomic characterization of <i>bla</i><sub>IMP</sub>-harboring plasmids in <i>Klebsiella</i> spp.

Microbiology spectrum·2026
Same author

Non-invasive evaluation of muscle invasion and survival prognosis in bladder cancer using enhanced CT-based deep learning radiomics: a multi-center real-world cohort study.

Military Medical Research·2026
Same author

Construction and external validation of radiomics models to detect primary prostate cancer with machine learning: a multicenter study based on <sup>68</sup>Ga-PSMA PET/CT.

Journal of the National Cancer Center·2026
Same author

Deep learning-based spatiotemporal estimation of lesion changes for patient-level assessment of breast cancer lung metastases on longitudinal CT.

NPJ precision oncology·2026
Same author

Lutein-fortified infant formula for newborn health: a comprehensive patent review and a systematic review of clinical trials.

Critical reviews in food science and nutrition·2026
Same journal

Refinement and application of 12S <i>rRNA</i> meta-barcoding primers for seafood identification in multispecies product.

Current research in food science·2026
Same journal

Advancing sensory metrology: establishing a standardized protocol for measuring the concentration-dependent sweetness potency of sweeteners utilizing gLMS.

Current research in food science·2026
Same journal

Humidity management modulates aroma deterioration in postharvest strawberry through volatile remodeling and membrane lipid metabolism.

Current research in food science·2026
Same journal

Application and evaluation of digital PCR platforms for same-day detection of <i>Vibrio parahaemolyticus</i> in mussel samples.

Current research in food science·2026
Same journal

Precision prebiotics: Engineering food-derived polysaccharides to target specific SCFA-producing taxa for neuroprotection via the microbiota-gut-brain axis.

Current research in food science·2026
Same journal

Effects of high-speed shear and esterification modification on physicochemical and structural properties of cassava starch and microencapsulation for olive oils.

Current research in food science·2026
See all related articles

Related Experiment Video

Updated: Aug 16, 2025

Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography
06:21

Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography

Published on: October 9, 2018

8.9K

Microwave imaging for watermelon maturity determination.

Joe Garvin1, Feras Abushakra1, Zachary Choffin1

  • 1Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL, 35487, USA.

Current Research in Food Science
|December 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a new microwave imaging system to assess watermelon ripeness. The technology shows distinct image differences correlating with maturity, offering a novel quality control method for the food industry.

Keywords:
Food qualityMaturityMicrowave imagingRipenessVivaldi antennaWatermelon

More Related Videos

A Contrast of Three Inoculation Techniques used to Determine the Race of Unknown Fusarium oxysporum f.sp. niveum Isolates
11:48

A Contrast of Three Inoculation Techniques used to Determine the Race of Unknown Fusarium oxysporum f.sp. niveum Isolates

Published on: October 28, 2021

3.3K
An Efficient Clearing Protocol for the Study of Seed Development in Tomato Solanum lycopersicum L.
06:26

An Efficient Clearing Protocol for the Study of Seed Development in Tomato Solanum lycopersicum L.

Published on: September 7, 2022

4.3K

Related Experiment Videos

Last Updated: Aug 16, 2025

Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography
06:21

Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography

Published on: October 9, 2018

8.9K
A Contrast of Three Inoculation Techniques used to Determine the Race of Unknown Fusarium oxysporum f.sp. niveum Isolates
11:48

A Contrast of Three Inoculation Techniques used to Determine the Race of Unknown Fusarium oxysporum f.sp. niveum Isolates

Published on: October 28, 2021

3.3K
An Efficient Clearing Protocol for the Study of Seed Development in Tomato Solanum lycopersicum L.
06:26

An Efficient Clearing Protocol for the Study of Seed Development in Tomato Solanum lycopersicum L.

Published on: September 7, 2022

4.3K

Area of Science:

  • Electromagnetics and Applied Physics
  • Food Science and Technology
  • Non-invasive Sensing Technologies

Background:

  • Microwave imaging is valuable for medical diagnosis and food quality assessment.
  • Fruit ripeness is a critical quality indicator for consumers.
  • Non-destructive methods are needed to evaluate fruit maturity.

Purpose of the Study:

  • To propose and demonstrate a novel microwave imaging system for determining watermelon ripeness.
  • To validate the system's effectiveness using various watermelon samples.
  • To establish a proof of concept for microwave imaging in fruit quality assessment.

Main Methods:

  • A microwave imaging system utilizing a circular array of 10 Coplanar Vivaldi antennas was designed.
  • Automated channel switching was employed for rapid S-parameter data acquisition.
  • Eight watermelon samples of varying ripeness and characteristics were scanned.
  • Image data was compared with physical cross-sections and sugar concentration measurements.

Main Results:

  • Distinct differences in microwave images were observed corresponding to watermelon maturity levels.
  • The imaging technique successfully differentiated between unripe and ripe watermelons.
  • Sugar concentration measurements validated the imaging-based ripeness assessment.

Conclusions:

  • The proposed microwave imaging system is a viable non-destructive tool for assessing watermelon ripeness.
  • This technology offers potential for enhanced food safety and quality control in the fruit industry.
  • Further development could extend this technique to other fruits and food products.