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

Wang, Jie; Wang, Sugui; Ge, Xiaolan; Zhang, Mengjuan

doi:10.1007/s00217-021-03816-9

Cited by 7 publications

(5 citation statements)

References 43 publications

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“…Linear discriminant analysis (LDA) is a classical supervised data dimension reduction method, which can be utilized to identify perceptible olfactory differences between different sources, narrowing the differences between similar sources and widening the differences between distinct sources, with more considerable distances between groups indicating more significant variability ( Wang et al, 2021a ). As shown in Figure 2B , LDA clustered different samples with good differentiation according to the fermentation strain: CJ is concentrated at the top of the figure and LAFCJ and LPFCJ are at the bottom.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Resultsmentioning

confidence: 99%

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

et al. 2023

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“…LDA is a statistical method that uses supervised features to maximize the ratio of between‐class variance to within‐class conflict 36 . As shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…LDA is a statistical method that uses supervised features to maximize the ratio of between-class variance to within-class conflict. 36 As shown in Fig. 4(B), the identification index (DI) was 98.5%, indicating that the volatile profiles of the different treatment groups were significantly different.…”

Section: Viable Count Of Labsmentioning

confidence: 91%

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

Wang,

Wei,

Zhai

et al. 2023

J Sci Food Agric

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BACKGROUNDLactic 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.RESULTSThis 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.CONCLUSIONThis 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.

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“…There are many common methods for the origin tracing of traditional Chinese medicines, including stable isotope techniques [ 12 , 13 ], high-performance liquid chromatography (HPLC) analysis [ 14 ], DNA barcoding techniques [ 15 ], near-infrared (NIR) spectroscopy [ 16 , 17 ], and metal element analysis [ 18 , 19 ]. Meng et al determined the stable isotope of volatile compounds in wolfberry from Gansu, Ningxia and Qinghai by gas chromatography isotope ratio mass spectrometry (GC-IRMS), and combined this with one-way analysis of variance (ANOVA) for origin tracing, and reached a final accuracy 89.16%, 87.77%, and 85.87%, respectively [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

Molecules

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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.

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

Cited by 7 publications

References 43 publications

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

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

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

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

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