CURRENT CHALLENGES, AND FUTURE OPPORTUNITIES FOR FERMENTED TEA LEAF SEGMENTATION, CLASSIFICATION, AND OPTIMIZATION DOI

C.M. Sulaikha,

Aditya Somasundaram

ShodhKosh Journal of Visual and Performing Arts, Journal Year: 2024, Volume and Issue: 5(1)

Published: June 30, 2024

Fermented tea leaves emerged as a significant agricultural commodity on the global scene. This type of product experiences segmentation, classification, and optimization due to different textures, stages fermentation, environmental influences. The article reviews progresses limitations made by automatic systems in realm image-based analysis fermented leaves, machine learning algorithms, methods. challenges high segmentation accuracy heterogeneous samples, robust classification among diverse varieties, scaling strategies for quality enhancement are some key challenges. Apart from hybrid algorithms designed interpret gap, future areas opportunities that utilize deep multimodal fusion. Highlights hyperspectral imaging approaches AI-driven models providing quick solutions with cost-effectiveness.

Language: Английский

Effects of Different Kinds of Fruit Juice on Flavor Quality and Hypoglycemic Activity of Black Tea DOI Creative Commons

Hongchun Cui,

Yuxiao Mao,

Yun Zhao

et al.

Foods, Journal Year: 2025, Volume and Issue: 14(4), P. 588 - 588

Published: Feb. 10, 2025

At present, the heavy bitter taste, poor flavor quality and low functional activity of summer autumn tea are bottleneck problems restricting utilization rate resources. The research development new products fruit-flavored black is conducive to expanding Different kinds fruit juice were added during fermentation processing classic tea, such as bananas, apples, fragrant pear Sydney pear, in this study. effects on amylase inhibitory fruity researched. sensory quality, chemicals α-amylase evaluated. results showed that evaluation scores treated with significantly higher than those without juice, especially crown juice. inhibition was control (p < 0.05). scores, polyphenol oxidase activity, water extract content, soluble sugar free amino acid theaflavin thearubigin content apple banana juices 0.05), Tea lower 0.05) had a redder broth, more pronounced sweet aroma, mellow taste reduced astringency. Therefore, preferred. hopes provide theoretical basis for resources technology.

Language: Английский

Citations

0
Comprehensive analysis of the flavor and color characteristics of light-fermented sour tea mediated by aspergillus Niger RAF106 DOI

Minyu Cai,

Zhiye Peng,

Peidong Xu

et al.

Food Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 143866 - 143866

Published: March 1, 2025

Language: Английский

Citations

0
Enhanced bioactivity of honeysuckle-Cassia seeds extracts through Lactobacillus acidophilus and Bacillus subtilis co-fermentation: Impact on alcoholic liver disease and gut microbiota DOI

Mengtian Zhou,

Yingao Zhang,

Ze-Yi Song

et al.

Food Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 144463 - 144463

Published: April 1, 2025

Language: Английский

Citations

0
EDITORIAL: Microbial Diversity, Microbial Resources and the Quality/Safety of Fermented Beverages DOI
Vittorio Capozzi, Baoru Yang, Wenjia He

et al.

Food Bioscience, Journal Year: 2024, Volume and Issue: unknown, P. 105793 - 105793

Published: Dec. 1, 2024

Language: Английский

Citations

0
CURRENT CHALLENGES, AND FUTURE OPPORTUNITIES FOR FERMENTED TEA LEAF SEGMENTATION, CLASSIFICATION, AND OPTIMIZATION DOI

C.M. Sulaikha,

Aditya Somasundaram

ShodhKosh Journal of Visual and Performing Arts, Journal Year: 2024, Volume and Issue: 5(1)

Published: June 30, 2024

Fermented tea leaves emerged as a significant agricultural commodity on the global scene. This type of product experiences segmentation, classification, and optimization due to different textures, stages fermentation, environmental influences. The article reviews progresses limitations made by automatic systems in realm image-based analysis fermented leaves, machine learning algorithms, methods. challenges high segmentation accuracy heterogeneous samples, robust classification among diverse varieties, scaling strategies for quality enhancement are some key challenges. Apart from hybrid algorithms designed interpret gap, future areas opportunities that utilize deep multimodal fusion. Highlights hyperspectral imaging approaches AI-driven models providing quick solutions with cost-effectiveness.

Language: Английский

Citations

0