Discrimination of Chinese Baijiu grades based on colorimetric sensor arrays

Hao, Lin; Kang, Wencui; Jin, Hong-juan; Man, Zhong-xiu; Chen, Quansheng

doi:10.1007/s10068-020-00757-z

Cited by 15 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As one of the extremely important flavoring substances in Huangjiu [ 68 ] and Baijiu [ 69 , 70 ], hexanoic acid ethyl ester (ethyl hexanoate) is also the representative of the characteristic flavor component in Baijiu, the content of which directly determines the quality of strong-flavor Baijiu. Esters produced during the fermentation process are mainly synthesized by the following two pathways based on present research: one is that microorganisms synthesize esters under the action of their own intracellular enzymes [ 71 – 73 ]; while the more frequent method is the catalysis by the extracellular enzymes (microbial lipases) secreted by microorganisms when organic acids react with alcohols in outside surrounding environment for synthesis [ 74 , 75 ].…”

Section: Resultsmentioning

confidence: 99%

The changes of microbial diversity and flavor compounds during the fermentation of millet Huangjiu, a traditional Chinese beverage

et al. 2022

View full text Add to dashboard Cite

Huangjiu is a national alcoholic beverage in China. Millet has congenital advantages in development and utilization of nutrient. Brewing Huangjiu with millet can increase the value of millet. Microbial community plays crucial roles in millet Huangjiu fermentation. Flavor compounds reflect the quality and health function of Huangjiu. The flavor compounds of Huangjiu are complex and their formation is closely associated with microorganisms, but the relationship between them during fermentation has been unknown. In this research, this relationship during millet Huangjiu fermentation were deeply investigated. Totally 86 volatile compounds were detected. Bacillus, Weissella, Paenibacillus, Klebsiella, Prevotella was investigated as the dominant microbes through high-throughput sequencing. 537 correlations between major flavor compounds and microbes were established to reflect the dynamic change during millet Huangjiu fermentation. The top five dominant genus of flavor producing microbes were Chryseobacterium, Sporolactobacillus, Psychrobacter, Sphingobium and Anoxybacillus. The content of malic acid and citric acid was gradually improved all through the millet Huangjiu fermentation. Malic acid and citric acid generated from millet Huangjiu fermentation shows healthy properties as liver protection and eliminating fatigue. Our research provides essential information on microbial community succession and the flavor formation during millet Huangjiu fermentation, and beneficial for development of Huangjiu products.

show abstract

Section: Resultsmentioning

confidence: 99%

The changes of microbial diversity and flavor compounds during the fermentation of millet Huangjiu, a traditional Chinese beverage

et al. 2022

View full text Add to dashboard Cite

show abstract

“…For the last few years, various brands, grades and vintage Baijiu were widely distributed in the market. In general, the common counterfeit method is the substitution of a shorter aging years Baijiu for another aging properly or adulteration with water or other inexpensive additives ( Lin, Kang, Jin, Man, & Chen, 2020 ). Considering the above situation, the discrimination of Baijiu with different aging years is a significant portion of the protection of product quality and market supervision.…”

Section: Discrimination Of Baijiu Vintagementioning

confidence: 99%

Synergy of physicochemical reactions occurred during aging for harmonizing and improving flavor

Jia

et al. 2023

Food Chemistry: X

View full text Add to dashboard Cite

“…e new semantic image identification through sensor array is computed for error detection during similarity analysis, preventing uneven patterns. e semantic feature recognition that ensures distribution and analysis based on irregular semantics and uneven patterns in colour distribution is retained using semantic analysis time as in equation (7). erefore, the detection error is identified in the sensor array representation with similarity identification through max-pooling.…”

Section: Analysis Timementioning

confidence: 99%

“…e colorimetric sensor array is used in the image segmentation process that provides an appropriate set of data for the segmentation process. Colorimetric sensor arrays are used to identify the complex components presented in an image [7]. Various methods and techniques are used for the segmentation process.…”

Section: Introductionmentioning

confidence: 99%

Image Semantic Recognition and Segmentation Algorithm of Colorimetric Sensor Array Based on Deep Convolutional Neural Network

Tang

Wang

Huang

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Semantic feature recognition in colour images is required for identifying uneven patterns in object detection and classification. The semantic features are identified by segmenting the colorimetric sensor array features through machine learning paradigms. Semantic segmentation is a method for identifying distinct elements in an image. This can be considered a task involving image classification at the pixel level. This article introduces a semantic feature-dependent array segmentation method (SFASM) to improve recognition accuracy due to irregular semantics. The proposed method incorporates a deep convolutional neural network for detecting the semantic and un-semantic features based on sensor array representations. The colour distributions per array are identified for horizontal and vertical semantics analysis. In this analysis, deep learning classifies the uneven patterns based on colour distribution, i.e. the consecutive and scattered colour distribution pixels in an array are correlated for their similarity. This similarity identification is maximized through max-pooling and recurrent iterations, preventing detection errors. The proposed method classifies the semantic features for further correlation sections, improving the accuracy. The proposed method’s performance is thus validated using the metrics precision, analysis time and F1-Score.

show abstract

Discrimination of Chinese Baijiu grades based on colorimetric sensor arrays

Cited by 15 publications

References 24 publications

The changes of microbial diversity and flavor compounds during the fermentation of millet Huangjiu, a traditional Chinese beverage

The changes of microbial diversity and flavor compounds during the fermentation of millet Huangjiu, a traditional Chinese beverage

Synergy of physicochemical reactions occurred during aging for harmonizing and improving flavor

Image Semantic Recognition and Segmentation Algorithm of Colorimetric Sensor Array Based on Deep Convolutional Neural Network

Contact Info

Product

Resources

About