Accurate tea leaf disease classification in real-world scenarios is hindered by complex backgrounds and the loss of fine-grained lesion details during CNN down sampling.To address this,we propose ResNet50-Dual-Fusion....Accurate tea leaf disease classification in real-world scenarios is hindered by complex backgrounds and the loss of fine-grained lesion details during CNN down sampling.To address this,we propose ResNet50-Dual-Fusion.It integrates a Cross-Attention Feature Fusion module(CAmodule)to adaptively reconstruct tiny lesion edges via cross-spatial interaction between shallow and deep features.Furthermore,a Magnitude-Aware Linear Attention(MALA)module with 2D Rotary Position Embedding(RoPE)is introduced to rectify magnitude neglect,effectively suppressing background noise.Evaluated on a 5,276-image dataset,our model achieves 85.96%accuracy(+3.00%over the baseline),outperforming architectures like ViT and Swin-Tiny.Grad-CAM visualizations confirm its superior lesion localization,providing a robust paradigm for automated crop disease diagnosis.展开更多
[Objective] The aim was to understand the change of fermentation pro- cess of Chang-sheng-chuan green brick tea and analyze the changes in the con- tents of structure components of tea leaves before and after fermenta...[Objective] The aim was to understand the change of fermentation pro- cess of Chang-sheng-chuan green brick tea and analyze the changes in the con- tents of structure components of tea leaves before and after fermentation. [Method] Ten tea leaves before and after fermentation were chosen. The tea leaves sections were made using paraffin microtomy, PAS staining, and observed under light mi- croscopy. Through image analysis for the tea leaves, we compared the changes on the areas of the cellulose and colloid in cell before and after pile-fermentation. At the same time, the tea leaves were observed under transmission electron micro- scope. [Result] The results showed that the pile-fermentation process caused the tea leaves tissue to become loose, and expanded the cell space. Besides, the cell wall of tea leaves was obviously thinning, and even breaking which composed of cellulose. Image analysis showed that the leaf fiber composition reduced significant- ly, with a corresponding increase of yellow colloid in cell. Under observation of transmission electron microscope, there were large amounts of fungi located in the space between the colloid and the cell wall of the tea leaves after pile-fermentation. [Conclusion] The fermentation of Green brick tea is the process of microbial bio- transformation of tea, which is dominated by microbe and consumed the cellulose components of tea leaves.展开更多
The purpose of this study was to characterize mulberry leaf instant tea(MLIT)powder prepared from the'Longsang No.1'(Morus abla L.cv.Longsang 1)mulberry leaves in Heilongjiang Province(China)and assess its obe...The purpose of this study was to characterize mulberry leaf instant tea(MLIT)powder prepared from the'Longsang No.1'(Morus abla L.cv.Longsang 1)mulberry leaves in Heilongjiang Province(China)and assess its obesity-preventing/relieving effects.A total of 174 compounds including quercetin,chlorogenic acid,1-deoxyecomycin(1-DNJ)related to antihyperlipidemia effects were identified from the MLIT powder.MLIT treatment reversed the Lee's index,fat coefficient,and serum biochemical parameters in both the obesity relieving and obesity preventing mice fed with high-fat diet.In the obesity relieving experiment,the relative abundance of Desulfovibrio in mouse feces decreased after both 0.5%and 1%MLIT treatments.In obesity preventing experiments,mouse with different amount of MLIT treatments showed increased relative abundance of Akkermansia,Bifidobacterium and Lactobacillus,while Deferribacteres,Desulfobacterota decreased.The beneficial bacteria in the intestinal tract of mice treated with MLIT increased.This study proved that MLIT had antihyperlipidemia potential via modulating intestinal microbiota in mice.展开更多
Numerous studies indicated that aluminum, the most abundant metallic element within the lithosphere, was considered to be related to some human diseases especially the Alzheimer’s disease. Tea, economically an import...Numerous studies indicated that aluminum, the most abundant metallic element within the lithosphere, was considered to be related to some human diseases especially the Alzheimer’s disease. Tea, economically an important beverage in the world, has been found to contain higher concentration of aluminum than many other drinks and foods. Therefore, tea would be a potentially important source of dietary aluminum. In order to understand the sources of aluminum in tea leaves and factors related with aluminum content of tea leaves, an experiment was designed to investigate the relationships of aluminum in tea leaves with leaf age, soil properties and forms of aluminum in soils. The results showed that there were great distinctions in the concentration of aluminum in tea leaves with different leaf age (Alold leaf> Almature leaf> Alyoung leaf). Moreover, soil pH was the major factor controlling the uptake of aluminum from soil into tea leaves. Furthermore, the content of aluminum in tea leaves was better predicated by the soluble aluminum extracted by 0.02mol/L CaCl2.展开更多
Tea plant cultivation plays a significant role in the Indian economy.The Tea board of India supports tea farmers to increase tea production by preventing various diseases in Tea Plant.Various climatic factors and othe...Tea plant cultivation plays a significant role in the Indian economy.The Tea board of India supports tea farmers to increase tea production by preventing various diseases in Tea Plant.Various climatic factors and other parameters cause these diseases.In this paper,the image retrieval model is developed to identify whether the given input tea leaf image has a disease or is healthy.Automation in image retrieval is a hot topic in the industry as it doesn’t require any form of metadata related to the images for storing or retrieval.Deep Hashing with Integrated Autoencoders is our proposed method for image retrieval in Tea Leaf images.It is an efficient andflexible way of retrieving Tea Leaf images.It has an integrated autoencoder which makes it better than the state-of-the-art methods giving better results for the MAP(mean average precision)scores,which is used as a parameter to judge the efficiency of the model.The autoencoders used with skip connections increase the weightage of the prominent features present in the previous tensor.This constitutes a hybrid model for hashing and retrieving images from a tea leaf data set.The proposed model will examine the input tea leaf image and identify the type of tea leaf disease.The relevant image will be retrieved based on the resulting type of disease.This model is only trained on scarce data as a real-life scenario,making it practical for many applications.展开更多
In recent years, the effects of reactive oxygen species（ROS） generated in the course of biological metabolism, such as superoxide（O2 ）, hydrogen peroxide（H202）, hydroxyl radical（HO） and singlet oxygen（102） o...In recent years, the effects of reactive oxygen species（ROS） generated in the course of biological metabolism, such as superoxide（O2 ）, hydrogen peroxide（H202）, hydroxyl radical（HO） and singlet oxygen（102） on the human health have received more attention due to their vital roles in physiological functions. Normally, antioxidant molecules, superoxide dismutase and catalase in biological organism can scavenge excessive free radicals by a series of chemical reactions to keep the cells in a state of redox homeostasis. Once the homeostasis has been broken,展开更多
文摘Accurate tea leaf disease classification in real-world scenarios is hindered by complex backgrounds and the loss of fine-grained lesion details during CNN down sampling.To address this,we propose ResNet50-Dual-Fusion.It integrates a Cross-Attention Feature Fusion module(CAmodule)to adaptively reconstruct tiny lesion edges via cross-spatial interaction between shallow and deep features.Furthermore,a Magnitude-Aware Linear Attention(MALA)module with 2D Rotary Position Embedding(RoPE)is introduced to rectify magnitude neglect,effectively suppressing background noise.Evaluated on a 5,276-image dataset,our model achieves 85.96%accuracy(+3.00%over the baseline),outperforming architectures like ViT and Swin-Tiny.Grad-CAM visualizations confirm its superior lesion localization,providing a robust paradigm for automated crop disease diagnosis.
基金Supported by Higher Education Institutions' Young Teacher In-Depth Business Project of Hubei Provincial Department of Education(XD2014056)~~
文摘[Objective] The aim was to understand the change of fermentation pro- cess of Chang-sheng-chuan green brick tea and analyze the changes in the con- tents of structure components of tea leaves before and after fermentation. [Method] Ten tea leaves before and after fermentation were chosen. The tea leaves sections were made using paraffin microtomy, PAS staining, and observed under light mi- croscopy. Through image analysis for the tea leaves, we compared the changes on the areas of the cellulose and colloid in cell before and after pile-fermentation. At the same time, the tea leaves were observed under transmission electron micro- scope. [Result] The results showed that the pile-fermentation process caused the tea leaves tissue to become loose, and expanded the cell space. Besides, the cell wall of tea leaves was obviously thinning, and even breaking which composed of cellulose. Image analysis showed that the leaf fiber composition reduced significant- ly, with a corresponding increase of yellow colloid in cell. Under observation of transmission electron microscope, there were large amounts of fungi located in the space between the colloid and the cell wall of the tea leaves after pile-fermentation. [Conclusion] The fermentation of Green brick tea is the process of microbial bio- transformation of tea, which is dominated by microbe and consumed the cellulose components of tea leaves.
基金supported by the Natural Science Foundation of Heilongjiang Province(LH2021C075)Key Laboratory of Functional Inorganic Material Chemistry(Heilongjiang University),Ministry of Education。
文摘The purpose of this study was to characterize mulberry leaf instant tea(MLIT)powder prepared from the'Longsang No.1'(Morus abla L.cv.Longsang 1)mulberry leaves in Heilongjiang Province(China)and assess its obesity-preventing/relieving effects.A total of 174 compounds including quercetin,chlorogenic acid,1-deoxyecomycin(1-DNJ)related to antihyperlipidemia effects were identified from the MLIT powder.MLIT treatment reversed the Lee's index,fat coefficient,and serum biochemical parameters in both the obesity relieving and obesity preventing mice fed with high-fat diet.In the obesity relieving experiment,the relative abundance of Desulfovibrio in mouse feces decreased after both 0.5%and 1%MLIT treatments.In obesity preventing experiments,mouse with different amount of MLIT treatments showed increased relative abundance of Akkermansia,Bifidobacterium and Lactobacillus,while Deferribacteres,Desulfobacterota decreased.The beneficial bacteria in the intestinal tract of mice treated with MLIT increased.This study proved that MLIT had antihyperlipidemia potential via modulating intestinal microbiota in mice.
文摘Numerous studies indicated that aluminum, the most abundant metallic element within the lithosphere, was considered to be related to some human diseases especially the Alzheimer’s disease. Tea, economically an important beverage in the world, has been found to contain higher concentration of aluminum than many other drinks and foods. Therefore, tea would be a potentially important source of dietary aluminum. In order to understand the sources of aluminum in tea leaves and factors related with aluminum content of tea leaves, an experiment was designed to investigate the relationships of aluminum in tea leaves with leaf age, soil properties and forms of aluminum in soils. The results showed that there were great distinctions in the concentration of aluminum in tea leaves with different leaf age (Alold leaf> Almature leaf> Alyoung leaf). Moreover, soil pH was the major factor controlling the uptake of aluminum from soil into tea leaves. Furthermore, the content of aluminum in tea leaves was better predicated by the soluble aluminum extracted by 0.02mol/L CaCl2.
文摘Tea plant cultivation plays a significant role in the Indian economy.The Tea board of India supports tea farmers to increase tea production by preventing various diseases in Tea Plant.Various climatic factors and other parameters cause these diseases.In this paper,the image retrieval model is developed to identify whether the given input tea leaf image has a disease or is healthy.Automation in image retrieval is a hot topic in the industry as it doesn’t require any form of metadata related to the images for storing or retrieval.Deep Hashing with Integrated Autoencoders is our proposed method for image retrieval in Tea Leaf images.It is an efficient andflexible way of retrieving Tea Leaf images.It has an integrated autoencoder which makes it better than the state-of-the-art methods giving better results for the MAP(mean average precision)scores,which is used as a parameter to judge the efficiency of the model.The autoencoders used with skip connections increase the weightage of the prominent features present in the previous tensor.This constitutes a hybrid model for hashing and retrieving images from a tea leaf data set.The proposed model will examine the input tea leaf image and identify the type of tea leaf disease.The relevant image will be retrieved based on the resulting type of disease.This model is only trained on scarce data as a real-life scenario,making it practical for many applications.
基金Supported by the Natural Science Foundation of Shandong Province,China(No.Y2006B31)
文摘In recent years, the effects of reactive oxygen species（ROS） generated in the course of biological metabolism, such as superoxide（O2 ）, hydrogen peroxide（H202）, hydroxyl radical（HO） and singlet oxygen（102） on the human health have received more attention due to their vital roles in physiological functions. Normally, antioxidant molecules, superoxide dismutase and catalase in biological organism can scavenge excessive free radicals by a series of chemical reactions to keep the cells in a state of redox homeostasis. Once the homeostasis has been broken,
