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Impacts of extrusion processing on food nutritional components

Author

Listed:
  • Qian Wang

    (Zibo Vocational Institute)

  • Kandhasamy Sivakumar

    (Karpaga Vinayaga College of Engineering and Technology)

  • Sugumar Mohanasundaram

    (Sri Sankara Arts and Science College (Autonomous))

Abstract

The modern society is dealing with the nutritional diseases whose major cause is the unreasonable diet of people and their changing living standards. The objective of this study is to understand the alterations in physical or chemical properties of food nutrients during the extrusion process in the context of Industry 4.0. This article takes cassava leaf as the research object, and evaluates the cassava leaf puffed food through the changes of physical and chemical properties before and after extrusion during supply chain process. The experimental results show that the starch changes from 46.371 g/100 g to 40.315 g/100 g before and after extrusion, the crude fat changes from 4.763 g/100 g to 2.897 g/100 g and the crude fiber changes from 2.555 g/100 g to 2.133 g/100 g. On the other hand, the protein changes from 8.56 g/100 g to 8.58 g/100 g and similarly, β-carotene changes from 758.9 g/100 g to 397.9 g/100 g. Generally, during the process of extrusion, nutrient content of starch and crude fat in the cassava leaf puffed food is reduced. This scenario reduces the crude fiber, and the content of soluble dietary fiber is increased, which improves the digestibility of the product. There is basically no change in the composition, except that the content of lysine is reduced, resulting in a decrease in nutritional value. This work provides the suitable evidences that for the Industry 4.0 context only the content of total flavonoids has been reduced in the process, and processing parameters of the extruder can be adjusted to reduce total flavonoids as much as possible.

Suggested Citation

  • Qian Wang & Kandhasamy Sivakumar & Sugumar Mohanasundaram, 2022. "Impacts of extrusion processing on food nutritional components," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 364-374, March.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01422-2
    DOI: 10.1007/s13198-021-01422-2
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    References listed on IDEAS

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    1. Manik Rakhra & Ramandeep Singh & Tarun Kumar Lohani & Mohammad Shabaz, 2021. "Metaheuristic and Machine Learning-Based Smart Engine for Renting and Sharing of Agriculture Equipment," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-13, February.
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