•Se-enriched fermented P. eryngii were produced by different Se addition methods.•The taste and aroma profiles of fermented P. eryngii were investigated.•Se-enrichment rates in fermented P. eryngii ...were all more than 50%.•Se increased the TPC and DPPH radical scavenging activity of fermented P. eryngii.•Se-enriched L. plantarum inoculation can produce high-quality fermented P. eryngii.
The effects of selenium (Se) addition methods on antioxidant activity and flavor properties of fermented Pleurotus eryngii (P. eryngii) using Lactobacillus plantarum (L. plantarum) inoculated and natural fermentation were investigated. After fermentation, the Se-enrichment rates in fruiting bodies of Se-added fermented P. eryngii were all more than 50%. Se addition, especially in the form of Se-enriched L. plantarum inoculation, had a significantly positive effect on total phenolic content and DPPH radical scavenging activity. Non-volatiles analysis revealed that the highest ration of lactic acid to acetic acid and the highest umami intensity were observed in P. eryngii fermented by inoculating Se-enriched L. plantarum (Lp-Se). Principal components analysis and cluster analysis of volatiles clearly separated Se-treated and plain experiments, which mainly due to dissimilarities in alcohols, aldehydes and ketones. Additionally, Lp-Se obtained the highest alcohols, especially 1-octen-3-ol with mushroom flavor. In short, Se-enriched L. plantarum inoculation could produce high-quality fermented P. eryngii.
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•Inorganic and organic nitrogen significantly affected the volatile compounds of cider.•Addition of 60 mg N/L DAP significantly increased the content of ethyl esters.•150 mg N/L amino ...acids mixture increased higher alcohols and acetate esters content.•Medium-chain fatty acid ethyl esters contributed the most to tropical fruity aroma.
To investigate the impact of inorganic and organic nitrogen on volatile compounds of cider, various levels (60, 150 and 240 mg N/L) of diammonium hydrogen phosphate (DAP) and amino acids mixture were added to apple juice before fermentation, respectively. The qualitative and quantitative of volatile substances were carried out by GC–MS. Further, sensory and electronic nose analysis was performed to analyze the aroma profile of cider. Both DAP and amino acids mixture promoted fermentation, significantly affected volatile compositions and increased perceived aromas of cider. Adding 60 mg N/L DAP significantly increased volatile compounds content, especially medium-chain fatty acid ethyl esters (MCFAEEs) and fatty acids (FAs), whereas higher alcohols and acetate esters concentrations were remarkably increased with 150 mg N/L amino acids supplementation. Partial least-squares (PLS) regression analysis suggested that MCFAEEs contributed the most to tropical fruity aroma. The study provides a theoretical foundation for high-quality cider brewing.
Acid-resistant bacteria are more and more widely used in industrial production due to their unique acid-resistant properties. In order to survive in various acidic environments, acid-resistant ...bacteria have developed diverse protective mechanisms such as sensing acid stress and signal transduction, maintaining intracellular pH homeostasis by controlling the flow of H
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, protecting and repairing biological macromolecules, metabolic modification, and cross-protection. Acid-resistant bacteria have broad biotechnological application prospects in the food field. The production of fermented foods with high acidity and acidophilic enzymes are the main applications of this kind of bacteria in the food industry. Their acid resistance modules can also be used to construct acid-resistant recombinant engineering strains for special purposes. However, they can also cause negative effects on foods, such as spoilage and toxicity. Herein, the aim of this paper is to summarize the research progress of molecular mechanisms against acid stress of acid-resistant bacteria. Moreover, their effects on the food industry were also discussed. It is useful to lay a foundation for broadening our understanding of the physiological metabolism of acid-resistant bacteria and better serving the food industry.
β-glucosidase is widely used in food industry for its glycosidic hydrolysis properties. In this paper, performance of a novel β-glucosidase BGL0224 from Oenococcus oeni for aroma enhancement of ...Cabernet Sauvignon wines was explored for the first time. The main projects included electronic nose, gas chromatography-mass spectrometry and sensory analysis. Principal component analysis indicated that electronic nose had the ability to discriminate different treatments by responding specifically to volatile compounds. Adding BGL0224 before alcoholic fermentation significantly increased the “aromatic index” of Cabernet Sauvignon wines. Compared with the control group, adding BGL0224 increased more than 15 volatile aroma compounds of Cabernet Sauvignon wines. Furthermore, with the addition of BGL0224 before alcoholic fermentation, the concentrations of medium-chain fatty acid ethyl esters, long-chain fatty acid ethyl esters and terpenes in wines were 3004.19 ± 36.14 μg/L, 4090.37 ± 94.07 μg/L and 210.21 ± 8.98 μg/L respectively, which were all significantly higher than other treatments. Sensory analysis showed that BGL0224 increased “tropical fruity”, “sweet fruity” and “floral notes” characteristics while inhibited “citrus” characteristics of Cabernet Sauvignon wines. Overall, this study provided support for industrial application of BGL0224 by evaluating its performance for aroma enhancement of Cabernet Sauvignon wines.
•BGL0224 remarkably increased the “aromatic index” and “terpene index” of wines.•BGL0224 increased types and concentrations of aroma compounds in wines.•Adding BGL0224 before malolactic fermentation decreased total alcohol concentration.•Long/medium-chain fatty acid ethyl esters promoted the “tropical fruity” of wines.•Terpenes promoted the “floral notes” of wines.
Few-shot class-incremental learning (FSCIL) struggles to incrementally recognize novel classes from few examples without catastrophic forgetting of old classes or overfitting to new classes. We ...propose TLCE, which ensembles multiple pre-trained models to improve separation of novel and old classes. Specifically, we use episodic training to map images from old classes to quasi-orthogonal prototypes, which minimizes interference between old and new classes. Then, we incorporate the use of ensembling diverse pre-trained models to further tackle the challenge of data imbalance and enhance adaptation to novel classes. Extensive experiments on various datasets demonstrate that our transfer learning ensemble approach outperforms state-of-the-art FSCIL methods.
Nearest-Neighbor (NN) classification has been proven as a simple and effective approach for few-shot learning. The query data can be classified efficiently by finding the nearest support class based ...on features extracted by pre-trained deep models. However, NN-based methods are sensitive to the data distribution and may produce false prediction if the samples in the support set happen to lie around the distribution boundary of different classes. To solve this issue, we present P3DC-shot, an improved nearest-neighbor based few-shot classification method empowered by prior-driven data calibration. Inspired by the distribution calibration technique which utilizes the distribution or statistics of the base classes to calibrate the data for few-shot tasks, we propose a novel discrete data calibration operation which is more suitable for NN-based few-shot classification. Specifically, we treat the prototypes representing each base class as priors and calibrate each support data based on its similarity to different base prototypes. Then, we perform NN classification using these discretely calibrated support data. Results from extensive experiments on various datasets show our efficient non-learning based method can outperform or at least comparable to SOTA methods which need additional learning steps.
•We propose a prior-driven discrete data calibration method for NN based few-shot classification.•Our method can efficiently utilize similar base prototypes to calibrate each support sample.•Our non-learning based method can outperform or at least comparable to SOTA methods.
Regional facial image synthesis conditioned on a semantic mask has achieved great attention in the field of computational visual media. However, the appearances of different regions may be ...inconsistent with each other after performing regional editing. In this paper, we focus on harmonized regional style transfer for facial images. A multi-scale encoder is proposed for accurate style code extraction. The key part of our work is a multi-region style attention module. It adapts multiple regional style embeddings from a reference image to a target image, to generate a harmonious result. We also propose style mapping networks for multi-modal style synthesis. We further employ an invertible flow model which can serve as mapping network to fine-tune the style code by inverting the code to latent space. Experiments on three widely used face datasets were used to evaluate our model by transferring regional facial appearance between datasets. The results show that our model can reliably perform style transfer and multi-modal manipulation, generating output comparable to the state of the art.
With the rapid development of new technologies and global trade and increasing collaboration among countries worldwide, public health has become a global issue. Global health, as a new discipline, ...has been drawing more attention from both academia and governments. The Belt and Road Initiative (BRI), proposed by China in 2013, aimed to promote trade and resource exchange, including education, research, and health issues, with over 60 countries in Asia, Africa, and Europe. The BRI provides good opportunities for involved countries to address health problems jointly as well. In response to the BRI and to promote international collaboration on global health issues, “The 2017 Belt and Road Initiative Global Health International Congress & 2017 Chinese Preventive Medicine Association-Chinese Society on Global Health Annual Meeting” was held on September 24-27, 2017 in Xi’an, China. Thus far, this is the largest high-quality international conference held in China that focused on the BRI global health issues. This article summarized the background, key sessions and topics covered during the congress, and important events, and highlights different perspectives of the BRI and global health by invited experts from China and abroad. The conference included 14 sessions (three keynote speech forums and ten scientific sessions and a research poster session) and about 100 speakers, around 40 of which were leading experts outside of China. All the major sessions were held in English. More than 40 leaders and experts of health sectors from 13 countries presented their work in the congress. Approximately 400 delegates from 29 countries attended the congress. Delegates had extensive discussions about global health related issues, future cooperation and development in global health. The congress fostered international exchange and collaboration.
Few-shot class-incremental learning (FSCIL) struggles to incrementally recognize novel classes from few examples without catastrophic forgetting of old classes or overfitting to new classes. We ...propose TLCE, which ensembles multiple pre-trained models to improve separation of novel and old classes. TLCE minimizes interference between old and new classes by mapping old class images to quasi-orthogonal prototypes using episodic training. It then ensembles diverse pre-trained models to better adapt to novel classes despite data imbalance. Extensive experiments on various datasets demonstrate that our transfer learning ensemble approach outperforms state-of-the-art FSCIL methods.
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