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Related Concept Videos

Photoluminescence: Applications01:14

Photoluminescence: Applications

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Photoluminescence offers a wide range of applications due to its inherent sensitivity and selectivity. This technique allows for both direct and indirect analyses of the analyte. Direct quantitative analysis is possible when the analyte exhibits a favorable quantum yield for fluorescence or phosphorescence. However, an indirect analysis may be feasible if the analyte is not fluorescent or phosphorescent, or if the quantum yield is unfavorable. Indirect methods include reacting the analyte with...
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An effective detection method for wheat mold based on ultra weak luminescence.

Gong Yue-Hong1,2,3, Yang Tie-Jun4,5,6, Liang Yi-Tao3

  • 1Key Laboratory of Grain Information Processing and Control, Henan University of Technology, Ministry of Education, Zhengzhou, China.

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Detecting mold in stored wheat is crucial for food safety. This study introduces a novel, eco-friendly method using ultra-weak luminescence and machine learning, achieving 93.1% accuracy in identifying moldy wheat.

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Area of Science:

  • Agricultural Science
  • Food Science
  • Biotechnology

Background:

  • Mold contamination in stored wheat reduces kernel quality and produces harmful mycotoxins.
  • Mycotoxins pose significant health risks to humans and animals.
  • Accurate and efficient detection of wheat mold is vital for quality assessment and safety.

Purpose of the Study:

  • To develop an eco-friendly and nondestructive method for detecting mold in stored wheat.
  • To overcome limitations of traditional biochemical detection methods.

Main Methods:

  • Utilizing ultra-weak luminescence (UWL) signals measured by a photon analyzer.
  • Employing approximate entropy and multiscale approximate entropy as classification features.
  • Establishing a support vector machine (SVM) model for moldy and healthy wheat classification.

Main Results:

  • The proposed UWL-based detection model achieved a maximum classification accuracy of 93.1%.
  • The receiver operating characteristic (ROC) curve demonstrated the model's effectiveness.

Conclusions:

  • The developed ultra-weak luminescence method offers a feasible and promising approach for nondestructive wheat mold detection.
  • This technique can aid in evaluating wheat storage quality and processing suitability.