Yuwei Liu

Bio: Yuwei Liu is an academic researcher from South China University of Technology. The author has contributed to research in topics: Fermentation & Gas chromatography. The author has an hindex of 3, co-authored 3 publications receiving 283 citations. Previous affiliations of Yuwei Liu include Guangzhou Higher Education Mega Center.

Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications

Abstract: Background The quality of products depends on their processing. Effective way of monitoring and controlling these processes will ensure the quality and safety of products. Since traditional measurement methods cannot achieve on-line monitoring, imaging spectroscopy, as a fast, accurate and non-destructive detection tool, has been widely used to evaluate quality and safety attributes of foods undergoing various processes. Scope and Approach In the current review, detailed applications of hyperspectral imaging (HSI) system in various food processes are outlined, including cooking, drying, chilling, freezing and storage, and salt curing. The study emphasized the ability of HSI technique to detect internal and external quality parameters in different food processes. Also, the advantages and disadvantages of HSI applications on these food processes are discussed. Key Findings and Conclusions The literature presented in this review clearly demonstrate that HSI has the ability to inspect and monitor different food manufacturing processes and has the potential to control the quality and safety of the processed foods. Although still with some barriers, it can be expected the HSI systems will find more useful and valuable applications in the future evaluation of food processes.

Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Abstract: K value is an important freshness indicator of meat. This study investigated the integration of spectral and textural data for enhancing the hyperspectral prediction ability of K value in pork meat. In this study, six feature wavebands (407, 481, 555, 578, 633, and 973 nm) were identified by successive projections algorithm (SPA). Meanwhile, the texture data of the grayscale images at the feature wavebands were extracted by gray level co-occurrence matrix (GLCM). The spectral and textural data were integrated by feature level fusion and the partial least square regression (PLSR) model built based on data fusion yielded excellent results, an improvement of at least 17.5% was obtained in model performance compared to those when either spectral data or textural data were used alone, indicating that data fusion is an effective way to enhance hyperspectral imaging ability for the determination of K values for freshness evaluation in pork meat.

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

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.

Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications

Abstract: Background The quality of products depends on their processing. Effective way of monitoring and controlling these processes will ensure the quality and safety of products. Since traditional measurement methods cannot achieve on-line monitoring, imaging spectroscopy, as a fast, accurate and non-destructive detection tool, has been widely used to evaluate quality and safety attributes of foods undergoing various processes. Scope and Approach In the current review, detailed applications of hyperspectral imaging (HSI) system in various food processes are outlined, including cooking, drying, chilling, freezing and storage, and salt curing. The study emphasized the ability of HSI technique to detect internal and external quality parameters in different food processes. Also, the advantages and disadvantages of HSI applications on these food processes are discussed. Key Findings and Conclusions The literature presented in this review clearly demonstrate that HSI has the ability to inspect and monitor different food manufacturing processes and has the potential to control the quality and safety of the processed foods. Although still with some barriers, it can be expected the HSI systems will find more useful and valuable applications in the future evaluation of food processes.

Novel techniques for evaluating freshness quality attributes of fish: A review of recent developments

Abstract: Background Fishery plays an important role in providing abundant nutrition for consumers as well as in international trade and foreign exchange earner. Due to the abundant endogenous enzymes and psychrophilic bacteria in fish bodies and the fragile organization of fish, fish and fish products are easily perishable and are affected by pre-harvest and postmortem factors, thus decreasing their value. It is thus significant to evaluate fish freshness in an effective and timely manner. Scope and approach In the current review, the principles and applications of novel techniques including enzyme biosensor, electrochemical biosensor, electronic nose, colorimetric sensor, electronic tongue, computer vision techniques, Vis/NIR spectroscopy, HSI spectroscopy and fluorescence spectroscopy as reliable and rapid evaluation tools complementing traditional time-consuming, expensive and cumbersome techniques are highlighted and the advantages and disadvantages of these methods are discussed. Moreover, challenges and future research trends are also proposed. Key findings and conclusions Although recent development of novel technologies has demonstrated their superiority for time-saving, rapid, economic, and even nondestructive and on-line detection of fish freshness, some challenges still remain in optimizing and simplifying bionics techniques, developing algorithms and chemometrics in spectroscopic technologies and improving selectivity and sensitivity in biosensor methods. Further studies are still needed to facilitate the applications of these new evaluation technologies in the fish industry.