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Non-destructive Tests for Concrete Strength01:12

Non-destructive Tests for Concrete Strength

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The rebound hammer test, also known as the Schmidt hammer test, is a non-destructive technique for evaluating the hardness of concrete and, indirectly, the strength of concrete. It operates on the principle that the rebound of a spring-driven mass from a concrete surface correlates to the surface's hardness. The device comprises a mass within a tubular housing, a spring mechanism, and a plunger that strikes the concrete. Upon release, the energy imparted to the mass by the spring causes it...
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Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
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Advances in Emerging Non-Destructive Technologies for Detecting Raw Egg Freshness: A Comprehensive Review.

Elsayed M Atwa1,2,3, Shaomin Xu1, Ahmed K Rashwan4

  • 1College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.

Foods (Basel, Switzerland)
|November 27, 2024
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Summary

Detecting raw egg freshness is crucial for the food industry. Modern non-destructive technologies like near-infrared spectroscopy and computer vision offer rapid, accurate, and objective freshness assessments, surpassing traditional methods.

Keywords:
NIR spectroscopycomputer visioneggfreshnesshyperspectral imagingnon-destructive technologies

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Area of Science:

  • Food Science
  • Analytical Chemistry
  • Agricultural Technology

Background:

  • Eggs are nutrient-rich but susceptible to microbial spoilage, impacting usability.
  • Traditional egg freshness assessment is subjective and time-consuming.
  • Need for objective, rapid methods to ensure egg quality and safety.

Purpose of the Study:

  • To review and discuss recent advances in non-destructive technologies for raw egg freshness detection.
  • To highlight the advantages of modern techniques over traditional methods.
  • To provide an overview of state-of-the-art technologies for the food industry.

Main Methods:

  • Review of near-infrared (NIR) spectroscopy.
  • Analysis of computer vision (color imaging) techniques.
  • Evaluation of hyperspectral imaging, Raman spectroscopy, fluorescence spectroscopy, electronic noses, and nuclear magnetic resonance.

Main Results:

  • Non-destructive technologies provide objective and rapid results.
  • NIR spectroscopy, computer vision, and hyperspectral imaging achieve >96% accuracy.
  • These methods overcome limitations of traditional, subjective assessments.

Conclusions:

  • Non-destructive technologies represent a significant advancement in raw egg freshness detection.
  • These technologies offer high accuracy and efficiency for the food industry.
  • The review contributes to emerging technologies in food quality assessment and safety.