Analysis of the juice and water losses in salted and unsalted pork samples heated in water bath. Consequences for the prediction of weight loss by transfer models

An evaluation of biochemical, structural and volatile changes of dry-cured pork using a combined ion mobility spectrometry, hyperspectral and confocal imaging approach

BACKGROUND

Food processing induces various modifications that affect the structure, physical and chemical properties of food products and hence the acceptance of the product by the consumer. In this work, the evolution of volatile components, 2-thiobarbituric acid reactive substances (TBARS), moisture content (MC) and microstructural changes of pork was investigated by hyperspectral (HSI) and confocal imaging (CLSM) techniques in synergy with gas chromatography-ion mobility spectrometry (GC-IMS). Models based on partial least squares regression (PLSR) were developed using the full HSI spectrum variables as well as optimum variables selected through a competitive adaptive reweighted sampling algorithm.

RESULTS

Prediction results for MC and TBARS using multiplicative scatter correction pre-processed spectra models demonstrated greater efficiency and predictability with determination coefficient of prediction of 0.928, 0.930 and root mean square error of prediction of 0.114, 1.002, respectively. Major structural changes were also observed during CLSM imaging, which were greatly pronounced in pork samples oven cooked for 15 and 20 h. These structural changes could be related to the denaturation of the major meat components, which could explain the loss of moisture and the formation of TBARS visualized from the HSI chemical distribution maps. GC-IMS identified 35 volatile components, including hexanal and pentanal, which are also known to have a higher lipid oxidation specificity.

CONCLUSION

The synergistic application of HSI, CLSM and GC-IMS enhanced data mining and interpretation and provided a convenient way for analyzing the chemical, structural and volatile changes occurring in meat during processing. © 2021 Society of Chemical Industry.

Monitoring microstructural changes and moisture distribution of dry-cured pork: a combined confocal laser scanning microscopy and hyperspectral imaging study

BACKGROUND

Various spectral profiles, including reflectance, absorbance, and Kubelka-Munk spectra, have been derived from hyperspectral images and used to develop multivariate models to evaluate changes in the quality of meat and meat products as a function of processing. However, none of these has the capacity to produce images of the structural changes often associated with processing. This study explored the feasibility of combining hyperspectral imaging (HSI) with confocal laser scanning microscopy (CLSM) to examine the impact of processing on microstructural changes and the evolution of moisture. Reflectance spectra features were obtained and transformed into absorbance and Kubelka-Munk spectra and their ability to predict moisture content using models established on partial least-squares regression were evaluated.

RESULTS

The partial least-squares regression model (full-band wavelength) dubbed Rs-MSC yielded the best result, with R c 2 = 0.967 , RMSEC = 0.127, R cv 2 = 0.949 , RMSECV = 0.418, R p 2 = 0.937 , RMSEP = 0.824. Next, a total of 16 optimum wavelengths were selected using the competitive adaptive reweighted sampling algorithm. These wavelengths also yielded good results for Rs-MSC, with R c 2 = 0.958 , RMSEC = 0.840, R cv 2 = 0.931 , RMSECV = 0.118, R p 2 = 0.926 , RMSEP = 0.121. Regarding moisture distribution and microstructure analysis, HSI and CLSM were able to reveal moisture content distribution and conformational differences in microstructure in the test samples.

CONCLUSION

Using HSI in synergy with CLSM may offer a reliable means for assessing both the chemical and structural changes that occur in other congener food products during processing. © 2020 Society of Chemical Industry.

Nondestructive Detection Method for Beef Water-Holding Capacity Using Modified Test Paper

Water-holding capacity (WHC) is a critical indicator of beef quality. Several conventional test methods have high cost or spend more time. In this study, a rapid detection method was developed to measure WHC by modified test paper. The test paper was modified by cobalt chloride for its color turned from blue to red after contacting with water. When the test paper was attached to the surface of meat sample, its color would change. The time of color changing was related to WHC. A prediction model was built. The prediction accuracy was 90 % and the detection time was less than 1 min. The results of scanning electron microscope (SEM) analysis showed that the three-dimensional network structures of the test paper were more compact and homogeneous. Accordingly, the modified test paper exhibits a more stable property and can be used for other meat products.