Authentication of American ginseng (Panax quinquefolius L.) from different origins by linear discriminant analysis of multi-elements

Non-volatile and volatile compound changes in blueberry juice inoculated with different lactic acid bacteria strains

BACKGROUND

Lactic acid bacteria (LABs) are widely present in foods and affect the flavour of fermented cultures. This study investigates the effects of fermentation with Lactobacillus acidophilus JYLA-16 (La), Lactobacillus plantarum JYLP-375 (Lp), and Lactobacillus rhamnosus JYLR-005 (Lr) on the flavour profile of blueberry juice.

RESULTS

This study showed that all LABs strains preferentially used glucose rather than fructose as the carbon source during fermentation. Lactic acid was the main fermentation product, reaching 7.76 g L-1 in La-fermented blueberry juice, 5.86 g L-1 in Lp-fermented blueberry juice, and 6.41 g L-1 in Lr-fermented blueberry juice. These strains extensively metabolized quinic acid, whereas oxalic acid metabolism was almost unaffected. Sixty-four volatile compounds were identified using gas chromatography-ion mobility spectrometry (GC-IMS). All fermented blueberry juices exhibited decreased aldehyde levels. Furthermore, fermentation with La was dominated by alcohols, Lp was dominated by esters, and Lr was dominated by ketones. Linear discriminant analysis of the electronic nose and principal component analysis of the GC-IMS data effectively differentiated between unfermented and fermented blueberry juices.

CONCLUSION

This study informs LABs selection for producing desirable flavours in fermented blueberry juice and provides a theoretical framework for flavour detection. © 2023 Society of Chemical Industry.

Geographical origin discriminatory analysis of onions: Chemometrics methods applied to ICP-OES and ICP-MS analysis

Geographical origin is an important determinant of agricultural product quality and safety. Herein, inductively coupled plasma (ICP) analysis was applied to determine the inorganic elemental content of onions and identify their geographical origin (Korean or Chinese). Chemometric, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to the ICP results. OPLS-DA distinguished each group, and 17 elements with variable importance in projection (VIP) values of ≥ 1 were selected. The receiver operating characteristic (ROC) curve had an area under the curve (AUC) of 1, indicating excellent discriminatory power. Differences in elemental content between groups were visually observed in a heatmap, and the country of origin was determined with 100% accuracy using canonical discriminant analysis (CDA). This method accurately distinguishes between Korean and Chinese onions and is expected to be beneficial for identifying agricultural products.

Protected Geographical Indication Discrimination of Zhejiang and Non-Zhejiang Ophiopogonis japonicus by Near-Infrared (NIR) Spectroscopy Combined with Chemometrics: The Influence of Different Stoichiometric and Spectrogram Pretreatment Methods

This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657 Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas ('non-Zhejiang'). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R² reaching 0.9979, while that of the second derivative was the lowest with an R² of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.

Aroma profiles of sweet cherry juice fermented by different lactic acid bacteria determined through integrated analysis of electronic nose and gas chromatography-ion mobility spectrometry

Sweet cherries are popular among consumers, with a recent explosion in sweet cherry production in China. However, the fragility of these fruits poses a challenge for expanding production and transport. With the aim of expanding the product categories of sweet cherries that can bypass these challenges, in this study, we prepared sweet cherry juice fermented by three different lactic acid bacteria (LAB; Lactobacillus acidophilus, Lactobacillus plantarum, and Lactobacillus rhamnosus GG), and evaluated the growth, physiochemical, and aroma characteristics. All three strains exhibited excellent growth potential in the sweet cherry juice; however, Lactobacillus acidophilus and Lactobacillus plantarum demonstrated more robust acid production capacity and higher microbial viability than Lactobacillus rhamnosus GG. Lactic acid was the primary fermentation product, and malic acid was significantly metabolized by LAB, indicating a transition in microbial metabolism from using carbohydrates to organic acids. The aroma profile was identified through integrated analysis of electronic nose (E-nose) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) data. A total of 50 volatile compounds characterized the aromatic profiles of the fermented juices by HS-GC-IMS. The flavor of sweet cherry juice changed after LAB fermentation and the fruity odor decreased overall. Lactobacillus acidophilus and Lactobacillus plantarum significantly increased 2-heptanone, ethyl acetate, and acetone contents, bringing about a creamy and rummy-like favor, whereas Lactobacillus rhamnosus GG significantly increased 2-heptanone, 3-hydroxybutan-2-one, and 2-pentanone contents, generating cheesy and buttery-like odors. Principal component analysis of GC-IMS data and linear discriminant analysis of E-nose results could effectively differentiate non-fermented sweet cherry juice and the sweet cherry juice separately inoculated with different LAB strains. Furthermore, there was a high correlation between the E-nose and GC-IMS results, providing a theoretical basis to identify different sweet cherry juice formulations and appropriate starter culture selection for fermentation. This study enables more extensive utilization of sweet cherry in the food industry and helps to improve the flavor of sweet cherry products.