Growth Prediction of Alicyclobacillus acidoterrestris in Orange Juice Based on Near-infrared Spectroscopy

Abstract

Alicyclobacillus acidoterrestris is the dominant spoilage bacteria resulting the deterioration of orange juice. To simulate the growth of Alicyclobacillus acidoterrestris in orange juice, near-infrared (NIR) spectroscopy technique was used to predict the content of Alicyclobacillus acidoterrestri in orange juice. Different spectral pre-processing methods, including autoscale, multiplicative scatter correction (MSC), standard normal variate (SNV) and detrend, coupled with chemometric regression were used to build the prediction model of Alicyclobacillus acidoterrestris in orange juice by NIR spectroscopy. Based on that, the NIR predicted colony data of Alicyclobacillus acidoterrestris was used to develop the growth model of Alicyclobacillus acidoterrestris in orange juice by one-step approach. Results showed that, PLS model established by spectral pretreatment after Autoscale had relatively good prediction effect on the content of Alicyclobacillus acidoterrestri in orange juice, with the prediction determination coefficient (Rp2), root mean square error of prediction (RMSEP) and relative percent deviation (RPD) of 0.733, 0.242 lg CFU/mL and 1.919, respectively. Four different growth simulation models gave satisfactory predictions, with MSE values from 0.0046 to 0.0300 lg CFU/mL, RMSE values from 0.068 to 0.173 lg CFU/mL, AIC values from -66.383 to -53.944, respectively. Correlation analysis was performed between the four developed growth models based on the NIR prediction of colony number and the growth model constructed by plate counting method, and all of their correlation coefficients (r) were higher than 0.900. Particularly, the Huang-full model had the best ability to describe the growth of Alicyclobacillus acidoterrestris in orange juice and showed the best fitting results. Besides, the good reliability of all developed models was verified by accuracy factor (\begin{document}$ {A}_{f} $\end{document}) and bias factor (\begin{document}$ {B}_{f} $\end{document}). Accordingly, this study indicated the potential to use NIR spectroscopy combined with advanced chemometrics to describe the growth prediction of Alicyclobacillus acidoterrestris in orange juice.

Keywords

• alicyclobacillus acidoterrestris
• near-infrared spectroscopy
• growth model
• one-step approach
• food predictive microbiology