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Food Analytical Methods

, Volume 11, Issue 9, pp 2472–2484 | Cite as

Hyperspectral Imaging Sensing of Changes in Moisture Content and Color of Beef During Microwave Heating Process

  • Yuwei Liu
  • Da-Wen Sun
  • Jun-Hu Cheng
  • Zhong Han
Article

Abstract

Moisture content (MC) and color are two important quality parameters of beef during microwave heating process. This study examined the effects of microwave heating time (0–75 s) on MC, color, and myoglobins of beef samples. The results showed that heating time significantly influenced the MC, color (L*, a*), and percentage of related myoglobins. The suitability of hyperspectral imaging (HSI) (400–1000 nm) was investigated to correlate the mean spectra of beef samples and the color and MC values during microwave treatment. After the use of pre-processing methods and optimum wavelengths selection, the SG-SPA-LS-SVM prediction model for MC (R2P = 0.869, RMSEP = 1.304, and RPD = 2.724) and the SG-RC-MLR model for a* (R2P = 0.890, RMSEP = 0.735, and RPD = 2.733) were established. The models were then used to develop the distribution maps of MC and a* values, respectively, showing that both MC and a* at the center of the meat slices were higher than those at the edge, corresponding to the temperature distribution during microwave heating. The results demonstrated the ability of HSI system for monitoring the changes of some quality parameters during microwave heating.

Keywords

Hyperspectral imaging Beef Microwave heating Moisture content Color Myoglobin 

Notes

Acknowledgements

The authors wish to acknowledge the contribution of undergraduate student Zhibin Liang for his assistance in the experiment.

Funding Information

The authors are grateful to the National Key R&D Program of China (2017YFD0400404) for its support. This research was also supported by the Natural Science Foundation of Guangdong Province (2017A030310558), the S&T Project of Guangzhou (201804010469), the China Postdoctoral Science Foundation (2017M612672), the Agricultural Development and Rural Work of Guangdong Province (2017LM4173), the S&T Project of Guangdong Province (2017B020207002), the Pearl River S&T Nova Program of Guangzhou (201610010104), the International and Hong Kong – Macau - Taiwan Collaborative Innovation Platform of Guangdong Province on Intelligent Food Quality Control and Process Technology & Equipment (2015KGJHZ001), the Guangdong Provincial R & D Centre for the Modern Agricultural Industry on Non-destructive Detection and Intensive Processing of Agricultural Products, the Common Technical Innovation Team of Guangdong Province on Preservation and Logistics of Agricultural Products (2016LM2154) and the Innovation Centre of Guangdong Province for Modern Agricultural Science and Technology on Intelligent Sensing and Precision Control of Agricultural Product Qualities.

Compliance with Ethical Standards

Conflict of Interest

Yuwei Liu declares that she has no conflict of interest. Da-Wen Sun declares that he has no conflict of interest. Jun-Hu Cheng declares that he has no conflict of interest. Zhong Han declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

Informed Consent

Not applicable.

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Authors and Affiliations

  1. 1.School of Food Science and EngineeringSouth China University of TechnologyGuangzhouChina
  2. 2.Academy of Contemporary Food Engineering, Guangzhou Higher Education Mega CenterSouth China University of TechnologyGuangzhouChina
  3. 3.Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain FoodsGuangzhou Higher Education Mega CenterGuangzhouChina
  4. 4.Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science CentreUniversity College Dublin, National University of IrelandDublin 4Ireland

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