Detecting total acid content quickly and accurately by combining hyperspectral imaging and an optimized algorithm method. (4th September 2021)

• Record Type: Journal Article
• Authors: Jiang, Xinna; Hu, Xinjun; Huang, Haoping; Tian, Jianping; Bu, Youhua; Huang, Dan; Luo, Huibo
• Is Part Of: Journal of food process engineering. Volume 44:Number 11(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-04
• Subjects: Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; 664.005
• DOI: 10.1111/jfpe.13844
• Languages: English
• ISSNs: 0145-8876

Abstract

Abstract: The total acid content of Daqu during fermentation directly influences the quality of the Daqu. Hyperspectral imaging (HSI) was used to rapidly and accurately detect the total acid content of Daqu. The performances of two spectral ranges obtained by two hyperspectral cameras for Daqu total acid content were compared. Different pretreatment methods were used to build the partial least squares regression (PLSR) model, and the optimal pretreatment for the corresponding spectra was determined. A combination of principal component analysis (PCA) and successive projection algorithm (SPA) was used to select the feature wavelengths. The PCA algorithm optimized by SPA was more accurate than the PCA algorithm alone when extracting the feature wavelengths. PLSR, backpropagation neural network (BP), and the backpropagation‐genetic algorithm (BP‐GA) model were developed to predict the total acid content of the Daqu samples by using the full wavelengths and feature wavelengths, respectively. The predictive performance of each model was compared and analyzed. The optimal model was the MSC + PCA‐SPA+BP‐GA model ( R c 2 = 0.8832, RMSEC = 0.1163, R p 2 = 0.9724, RMSEP = 0.0593, RPD = 4.2860, AB_RMSE = 0.0570). In addition, the distribution of total acid content within the region of interest (ROI) of Daqu samples was visualized at different fermentation stages using the optimized model. These results show that HSI technology can rapidly and precisely detect the total acid content of Daqu and visualize the content distribution, which provides important technical support for upgrading and transforming the liquor. Practical Applications: Daqu is the saccharifying agent, leavening agent, and aroma‐generating agent of liquor brewing. During the fermentation process, the total acid content is an important indicator for the quality evaluation of Daqu. Therefore, it is highly significant to detect the total acid content in Daqu quickly and accurately. The HSI technique is widely used to detect the contents of various substances in food. In this study, the HSI technique combining the PCA‐SPA and BP‐GA algorithms was established to detect the total acid content of Daqu, and a satisfactory result was obtained, showing that HSI technology combined with an optimized algorithm could be used to realize rapid and accurate detection of the total acid content of Daqu. In addition, the predictive model proposed in this study is not only applicable for detecting other food substances but also this method has great potential for real‐time indicators detection in winery for future work. Abstract :