Poonam Singha

Employment

• National Institute of Technology Rourkela Assistant Professor
  2020 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (53)

• Characterization of structural, functional, and rheological modifications in the hyacinth bean (Lablab purpureus) protein induced by multipin cold plasma treatment
  Journal of Food Measurement and Characterization 2026 DOI: 10.1007/s11694-025-03969-1
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• Automated Millet Classification Using Transfer Learning and Computer Vision
  Journal of Food Process Engineering 2026 DOI: 10.1111/jfpe.70554
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• Machine learning-assisted Fourier transform infrared spectroscopy to predict adulteration in coriander powder
  Food Chemistry 2025 DOI: 10.1016/j.foodchem.2025.143502
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• Deccan hemp (Hibiscus cannabinus) seed as a sustainable protein source: Impact of ultrasound coupled alkaline extraction on structural, functional, nutritional, and rheological properties
  Food Chemistry Advances 2025 DOI: 10.1016/j.focha.2025.100911
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• Sustainable valorization of jojoba oilcake: Pressing method-dependent protein stability and functionality for food applications
  Biomass and Bioenergy 2025 DOI: 10.1016/j.biombioe.2025.107660
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• Advanced machine learning techniques for hyacinth bean identification using infrared spectroscopy and computer vision
  Sustainable Food Technology 2025 DOI: 10.1039/D5FB00011D
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• Effect of pH and biopolymer ratio on phase behavior, rheology, and structural characteristics of pea protein isolate-locust bean gum coacervates
  JSFA reports 2024 DOI: 10.1002/jsf2.187
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• Viscoelastic behavior, gelation properties and structural characterization of Deccan hemp seed (Hibiscus cannabinus) protein: Influence of protein and ionic concentrations, pH, and temperature
  International Journal of Biological Macromolecules 2024 DOI: 10.1016/j.ijbiomac.2024.130120
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• Sustainable food processing technologies
  Future Crops and Processing Technologies for Sustainability and Nutritional Security 2024 DOI: 10.1201/9781003280170-2
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• Spectroscopic food adulteration detection using machine learning: Current challenges and future prospects
  Trends in Food Science and Technology 2024 DOI: 10.1016/j.tifs.2024.104377
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