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The nondestructive characterization of citrus varieties (Egyptian sweet orange, Lane Late navel orange, Australian orange, and Blood orange) was developed based on near-infrared diffuse reflectance spectroscopy (NIRDRS) together with principal component analysis (PCA) and Fisher linear discriminant analysis (FLDA). An experiment for the penetration of NIRDRS into the peel was designed and the effects of different spectral acquisition points were investigated. Pretreatments were used to eliminate the spectral interferences. As an unsupervised pattern recognition method, PCA was used to establish the characterization models. Furthermore, supervised pattern recognition based on PCA and FLDA was employed to enhance the accuracy. The results of the penetration experiments show that near-infrared light enters the citrus peel and is able to characterize the internal composition. Even with the optimized spectral pretreatment, accurate characterization of citrus varieties was not achieved by PCA. However, the accurate characterization of citrus varieties was provided by PCA-FLDA. The accuracies of four spectral acquisition points are 95%, while the characterization accuracies of six spectral acquisition points are 100% combined with optimized spectral pretreatment. Therefore, NIRDRS with PCA-FLDA is suitable for the rapid and nondestructive characterization of citrus varieties. [ABSTRACT FROM AUTHOR]

In this paper, a novel strategy of "pick the best of the best" was proposed for the nondestructive identification of different‐origin and adulterated Poria cocos with near‐infrared spectroscopy. First, various preprocessing methods were divided into three classes: baseline correction, scattering and trend correction, and scaling. The single preprocessing methods with the best predictions in each class were selected. Then, the selected preprocessing methods were combined in pairs according to three classes. The pair combination preprocessing methods with the best predictions and also better predictions than single methods were selected. Finally, the selected pair combination preprocessing method was combined with the methods in the unselected class. The three combination preprocessing methods with the best predictions and also better predictions than pair combination methods were selected as the final prediction. With this strategy, the optimized preprocessing combination can be obtained quickly, and the identification accuracy with principal component analysis method can be greatly improved. 0% identification accuracy of adulterated samples and 12.5% identification accuracy of different‐origin samples were obtained with the raw data. However, 100% accuracy of adulterated samples, 93.8% accuracy of calibration dataset, and 75% accuracy of validation dataset can be obtained with the novel strategy. The developed technology can be regarded as a simple, rapid, and accurate nondestructive identification method for different‐origin and adulterated samples, and has a broad application prospect in the future. [ABSTRACT FROM AUTHOR]

The quality of Citri Reticulatae Pericarpium (CRP) is closely correlated with the aging time. However, CRPs in different storage ages are similar in appearance, and the young CRP may be labeled as the aged one to obtain the excess profit by some unscrupulous traders. Most traditional analysis methods are laborious and time‐consuming, and they can hardly realize the nondestructive classification. In this paper, a novel method based on near‐infrared diffuse reflectance spectroscopy (NIRDRS) and data combination technique for the nondestructive classification of different‐age CRPs was proposed. The CRPs in different storage ages (5, 10, 15, 20, and 25 years) were measured. The near‐infrared spectra of outer skin and inner capsule were obtained. Principal component analysis (PCA), soft independent modeling of class analogy (SIMCA), and Fisher's linear discriminant analysis (FLD), with different data pretreatment methods, were used for the classification analysis. Data combination of the outer skin and inner capsule spectra was discussed for further improving the classification results. The results show that multiple sensors provide more useful and complementary information than a single sensor does for improving the prediction accuracy. With the help of data combination strategy, 100% prediction accuracy can be obtained with both second‐order derivative–FLD and continuous wavelet transform–multiplicative scatter correction–FLD methods. [ABSTRACT FROM AUTHOR]

Intensive study of the metabolome during the Douchi fermentation can provide new knowledge for optimizing the fermentation process. In this work, the metabolic characterization throughout the fermentation of Mucor racemosus Douchi was investigated using gas chromatography with time‐of‐flight mass spectrometry. A total of 511 peaks were found, and 114 metabolites were identified. The fermentation process was clearly distinguished into two main phases by principal components analysis and orthogonal partial least squares‐discriminant analysis. All the samples in the score plots were within the 95% Hotelling T2 ellipse. Two separated clusters can be seen clearly in the score plot, which represents the two stages of fermentation: koji‐making (within 48 hr) and postfermentation (after 48 hr). Besides, clear separation and discrimination by both methods were found among different fermentation time within 15 days, while the discrimination cannot be found with more than 15 days of fermentation, indicating that the fermentation of Douchi was finished in 15 days. Due to the synergistic effect of protease and hydrolase accumulated in the early stage, proteins and other big molecular substances are rapidly hydrolyzed into a large number of small molecule components. However, the activity of enzymes decreased with the further fermentation, and some free amino acids were consumed in Maillard reaction. Therefore, there was no significant change in the content of small molecular substances after 15 days of fermentation. Furthermore, the levels of some metabolites such as alanine and lysine involved in the fermentation varied significantly throughout the processes. This study provides new insights for the metabolomics characteristics of Douchi fermentation. [ABSTRACT FROM AUTHOR]

Citri Reticulatae Pericarpium (CRP), has been used in China for hundreds of years as a functional food and medicine. However, some short-age CRPs are disguised as long-age CRPs by unscrupulous businessmen in order to obtain higher profits. In this paper, a rapid and nondestructive method for the classification of different-age CRPs was established using portable near infrared spectroscopy (NIRS) in diffuse reflectance mode combination with appropriate chemometric methods. The spectra of outer skin and inner capsule of CRPs at different storage ages were obtained directly without destroying the samples. Principal component analysis (PCA) with single and combined spectral pretreatment methods was used for the classification of different-age CRPs. Furthermore, the data were pretreated with the PCA method, and Fisher linear discriminant analysis (FLD) with optimized pretreatment methods was discussed for improving the accuracy of classification. Data pretreatment methods can be used to eliminate the noise and background interference. The classification accuracy of inner capsule is better than that of outer skin data. Furthermore, the best results with 100% prediction accuracy can be obtained with FLD method, even without pretreatment. [ABSTRACT FROM AUTHOR]

This study optimized the headspace solid phase microextraction (HS-SPME) conditions for the analysis of the volatile flavor compounds of Chinese south stinky tofu brine by gas chromatography-mass spectrometry (GC-MS). The optimum HS-SPME conditions established were as follows: polar column CD-WAX, white 85 μm polyella extractor, extraction temperature 60 °C, equilibrium time 20 min, extraction time 40 min. Under these conditions, a total of 63 volatile flavor compounds in five stinky tofu brines were identified. The offensive odor of the stinky tofu may be derived from some of the volatile flavor compounds such as phenol, p-cresol, 3-methylindole, indole, acetic acid, propionic acid, isobutyric acid, n-butyric acid and 3-methylbutanoic acid. The volatile flavor substances data was examined by principal component analysis (PCA) to visualize the response patterns in the feature space of principal components (PC). PCA analysis results revealed that the Chengshifu brine (STB1) and Baise jingdian brine (STB4) are similar in PC 1, 2, and 3, and the two brines have a similar flavor. Results also indicate that the Huogongdian brine (STB2) and Wangcheng brine (STB3) can be grouped in the same class as they are similar in PC 3. However, PC 1, 2, and 3 of the Luojia brine (STB5) and other brands of brine are different as is the flavor. [ABSTRACT FROM AUTHOR]