Rapid non-destructive monitoring and quality assessment of the fumigation process of Shanxi aged vinegar based on Vis-NIR hyperspectral imaging combined with multiple chemometric algorithms.

The quality of the grains during the fumigation process can significantly affect the flavour and nutritional value of Shanxi aged vinegar (SAV). Hyperspectral imaging (HSI) was used to monitor the extent of fumigated grains, and it was combined with chemometrics to quantitatively predict three key physicochemical constituents: moisture content (MC), total acid (TA) and amino acid nitrogen (AAN). The noise reduction effects of five spectral preprocessing methods were compared, followed by the screening of optimal wavelengths using competitive adaptive reweighted sampling. Support vector machine classification was employed to establish a model for discriminating fumigated grains, and the best recognition accuracy reached 100%. Furthermore, the results of partial least squares regression slightly outperformed support vector machine regression, with correlation coefficient for prediction (Rp) of 0.9697, 0.9716, and 0.9098 for MC, TA, and AAN, respectively. The study demonstrates that HSI can be employed for rapid non-destructive monitoring and quality assessment of the fumigation process in SAV.

Fast monitoring the dynamic change of total acids during apple vinegar fermentation process using a colorimetric IDA sensor array.

In this work, a colorimetric sensor array (CSA) for quantitative determination of total acids in apple vinegar during fermentation was constructed. The sensor array was properly designed based on indicators displacement assay (IDA) using three metal ions (Cu2+, Zn2+ and Ni2+) as receptors to organic acids. The time stability results showed that the prepared CSA had good operational stability. Three quantitative models, including one linear (partial least square, PLS) and two nonlinear (support vector regression, SVR and back propagation artificial neural network, BP-ANN) models were used to estimate the content of total acids in fermentation broth of apple vinegar through image analysis. The correlation coefficient (RP), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) of the better SVR model were 0.8708, 0.0545 and 10.91, respectively. The results implied that the CSA had an excellent potential for quantitative monitoring of total acids in apple vinegar during fermentation.

Nondestructive monitoring, kinetics and antimicrobial properties of ultrasound technology applied for surface decontamination of bacterial foodborne pathogen in pork.

In this study, electronic nose (E-nose) and Hyperspectral Imaging (HSI) was employed for nondestructive monitoring of ultrasound efficiency (20KHZ) in the inactivation of Salmonella Typhimurium, and Escherichia coli in inoculated pork samples treated for 10, 20 and 30 min. Weibull, and Log-linear model fitted well (R2 ≥ 0.9) for both Salmonella Typhimurium, and Escherichia coli inactivation kinetics. The study also revealed that ultrasound has antimicrobial effects on the pathogens. For qualitative analysis, unsupervised (PCA) and supervised (LDA) chemometric algorithms were applied. PCA was used for successful sample clustering and LDA approach was used to construct statistical models for the classification of ultrasound treated and untreated samples. LDA showed classification accuracies of 99.26%,99.63%,99.70%, 99.43% for E-nose - S. Typhimurium, E-nose -E. coli, HSI - S. Typhimurium and HSI -E. coli respectively. PLSR quantitative models showed robust models for S. Typhimurium- (E-nose Rp2 = 0.9375, RMSEP = 0.2107 log CFU/g and RPD = 9.7240 and (HSI Rp2 = 0.9687 RMSEP = 0.1985 log CFU/g and RPD = 10.3217) and E. coli -(E-nose -Rp2 = 0.9531, RMSEP = 0.2057 log CFU/g and RPD = 9.9604) and (HIS- Rp2 = 0.9687, RMSEP = 0.2014 log CFU/g and RPD = 10.1731). This novel study shows the overall effectiveness of applying E-nose and HSI for in-situ and nondestructive detection, discrimination and quantification of bacterial foodborne pathogens during the application of food processing technologies like ultrasound for pathogen inactivation.