Facile synthesis of iron nanoparticles from Camellia Sinensis leaves catalysed for biodiesel synthesis from Azolla filiculoides.

Recent years have seen an increase in research on biodiesel, an environmentally benign and renewable fuel alternative for traditional fossil fuels. Biodiesel might become more cost-effective and competitive with diesel if a solid heterogeneous catalyst is used in its production. One way to make biodiesel more affordable and competitive with diesel is to employ a solid heterogeneous catalyst in its manufacturing. Based on X-ray diffraction (XRD) and Fourier Transform infrared spectroscopy (FTIR), the researchers in this study proved their hypothesis that iron oxide core-shell nanoparticles were generated during the green synthesis of iron-based nanoparticles (FeNPs) from Camellia Sinensis leaves. The fabrication of spherical iron nanoparticles was successfully confirmed using scanning electron microscopy (SEM). As a heterogeneous catalyst, the synthesised catalyst has shown potential in facilitating the conversion of algae oil into biodiesel. With the optimal parameters (0.5 weight percent catalytic load, 1:6 oil-methanol ratio, 60 °C reaction temperature, and 1 h and 30 min reaction duration), a 93.33% yield was attained. This may be due to its acid-base property, chemical stability, stronger metal support interaction. Furthermore, the catalyst was employed for transesterification reactions five times after regeneration with n-hexane washing followed by calcination at 650 °C for 3 h.

Association of the electrical parameters and photosynthetic characteristics of the tea tree manifests its response to simulated karst drought.

Tea plantations in Karst regions suffer from the serious effects of frequent temporary karst droughts, leading to a decline in tea production and quality in the region. The close relationship between growth and electrical parameters of plants, including physiological capacitance, resistance and impedance, can be used to accurately monitor their plant water status online, quickly, accurately, timely and nondestructively. In this study, three tea tree cultivars of Zhonghuang No.2 (ZH), Wuniuzao (WNZ), and Longjing 43 (LJ) with different levels of drought resistance were selected as experimental materials, and experiments were carried out under controlled conditions according to control (soil water content of 40-45%, D0), (keeping D0 no watering to 5 days, D5), (keeping D0 no watering to 10 days, D10), (the first day after D10 is rehydrated to D0 is regarded as R1) and (the fifth day after D10 rehydration to D0 is regarded as R5), to determine intracellular water metabolism and nutrient translocation characteristics based on intrinsic electrical parameters. The photosynthetic characteristics and chlorophyll fluorescence parameters were also determined to investigate the response of water metabolism to simulated karst drought in the three tea tree cultivars. The results indicated that the water metabolism patterns responded to environmental water changes with a medium water-holding capacity, medium water transport rate, and low water-use efficiency, and the nutrient patterns in those tea tree varieties demonstrated with a high nutrient flux per unit area, low nutrient transfer rate, and high nutrient transport capacity. After rehydration, only the electrical characteristics of WNZ returned to the D0 levels, but the net photosynthetic rate of all varieties returned to or even exceeded the D0 levels. The chlorophyll fluorescence parameters could not be used to characterize the recoverability of metabolism in tea trees. The electrical characteristics quickly reflected the response of the water metabolism in plants to environmental changes, and the fusion of electrical characteristics and photosynthetic characteristics was able to more quickly, accurately, and comprehensively reflect the response of water metabolism to temporary karst drought.

Soil organic matter and total nitrogen as key driving factors promoting the assessment of acid-base buffering characteristics in a tea (Camellia sinensis) plantation habitat.

The issue of soil acidification in tea plantations has become a critical concern due to its potential impact on tea quality and plant health. Understanding the factors contributing to soil acidification is essential for implementing effective soil management strategies in tea-growing regions. In this study, a field study was conducted to investigate the effects of tea plantations on soil acidification and the associated acid-base buffering capacity (pHBC). We assessed acidification, pHBC, nutrient concentrations, and cation contents in the top 0-20 cm layer of soil across forty tea gardens of varying stand ages (0-5, 5-10, 10-20, and 20-40 years old) in Anji County, Zhejiang Province, China. The results revealed evident soil acidification due to tea plantation activities, with the lowest soil pH observed in tea gardens aged 10-20 and 20-40 years. Higher levels of soil organic matter (SOM), total nitrogen (TN), Olsen phosphorus (Olsen-P), available iron (Fe), and exchangeable hydrogen (H+) were notably recorded in 10-20 and 20-40 years old tea garden soils, suggesting an increased risk of soil acidification with prolonged tea cultivation. Furthermore, prolonged tea cultivation correlated with increased pHBC, which amplified with tea stand ages. The investigation of the relationship between soil pHBC and various parameters highlighted significant influences from soil pH, SOM, cation exchange capacity, TN, available potassium, Olsen-P, exchangeable acids (including H+ and aluminum), available Fe, and available zinc. Consequently, these findings underscore a substantial risk of soil acidification in tea gardens within the monitored region, with SOM and TN content being key driving factors influencing pHBC.

Dynamic changes and the effects of key procedures on the characteristic aroma compounds of Lu'an Guapian green tea during the manufacturing process.

As a kind of green tea with unique multiple baking processes, the flavor code of Lu'an Guapian (LAGP) has recently been revealed. To improve and stabilize the quality of LAGP, further insight into the dynamic changes in odorants during the whole processing is required. In this study, 50 odorants were identified in processing tea leaves, 14 of which were selected for absolute quantification to profile the effect of processes. The results showed that spreading is crucial for key aroma generation and accumulation, while these odorants undergo significant changes at the deep baking stage. By adjusting the conditions of the spreading and deep baking, it was found that low-temperature (4 °C) spreading for 6 h and low-temperature with long-time baking (final leaf temperature: 102 °C, 45 min) could improve the overall aroma quality. These results provide a new direction for enhancing the quality of LAGP green tea.

Theanine Capture of Reactive Carbonyl Species in Humans after Consuming Theanine Capsules or Green Tea.

Acrolein (ACR), methylglyoxal (MGO), and glyoxal (GO) are a class of reactive carbonyl species (RCS), which play a crucial role in the pathogenesis of chronic and age-related diseases. Here, we explored a new RCS inhibitor (theanine, THE) and investigated its capture capacity on RCS in vivo by human experiments. After proving that theanine could efficiently capture ACR instead of MGO/GO by forming adducts under simulated physiological conditions, we further detected the ACR/MGO/GO adducts of theanine in the human urine samples after consumption of theanine capsules (200 and 400 mg) or green tea (4 cups, containing 200 mg of theanine) by using ultraperformance liquid chromatography-time-of-flight-high-resolution mass spectrometry. Quantitative assays revealed that THE-ACR, THE-2ACR-1, THE-MGO, and THE-GO were formed in a dose-dependent manner in the theanine capsule groups; the maximum value of the adducts of theanine was also tested. Furthermore, besides the RCS adducts of theanine, the RCS adducts of catechins could also be detected in the drinking tea group. Whereas, metabolite profile analysis showed that theanine could better capture RCS produced in the renal metabolic pathway than catechins. Our findings indicated that theanine could reduce RCS in the body in two ways: as a pure component or contained in tea leaves.

Efficacy of green tea ( Camellia sinensis Linn) 3% extract cream on improvement of striae distensae.

Background: Striae distensae (SD) is a skin condition that frequently causes dermatological consultations and although asymptomatic, it may can cause itch and burning sensation. Green tea extract contains polyphenol, including flavanol, flavandiol, flavonoid, phenolic acid, amino acids and minerals which play a role in the repair of stretch marks through anti-inflammatory mechanism, increase collagen production, fibroblast proliferation, and skin hydration. Objective: To determine the efficacy of green tea extract cream on striae distensae. Methods: This is a pre-experimental clinical trial with a pretest-posttest design on 36 subjects with striae distensae. Diagnosis establishes through history taking and clinical evaluation. Imam Nelva Alviera (INA) score was used as SD severity before and after the application of the 3% green tea extract cream carried out at weeks 0, 2, 4, 6, and 8. Side effects and subjects' satisfaction were also recorded. Cochran test was carried out to see the difference before and after treatment, with a p-value <0.05 considered significant. Results: Majority of study subjects were 18-25 years (77.8%), had history of pregnancy (75%), had a history of menarche at the age of 12 years (27.8%) and all subjects had striae alba. There was significant decrement in INA score for striae distensae (p<0.001) after eight weeks administration of 3% green tea extract cream. Clinical improvement and no side effects were also noted. All subjects were satisfied. Conclusions: The use of 3% green tea extract cream can improve the appearance of SD.

Automated detection of selected tea leaf diseases in Bangladesh with convolutional neural network.

Globally, tea production and its quality fundamentally depend on tea leaves, which are susceptible to invasion by pathogenic organisms. Precise and early-stage identification of plant foliage diseases is a key element in preventing and controlling the spreading of diseases that hinder yield and quality. Image processing techniques are a sophisticated tool that is rapidly gaining traction in the agricultural sector for the detection of a wide range of diseases with excellent accuracy. This study focuses on a pragmatic approach for automatically detecting selected tea foliage diseases based on convolutional neural network (CNN). A large dataset of 3330 images has been created by collecting samples from different regions of Sylhet division, the tea capital of Bangladesh. The proposed CNN model is developed based on tea leaves affected by red rust, brown blight, grey blight, and healthy leaves. Afterward, the model's prediction was validated with laboratory tests that included microbial culture media and microscopic analysis. The accuracy of this model was found to be 96.65%. Chiefly, the proposed model was developed in the context of the Bangladesh tea industry.

Pesticide application behavior in green tea cultivation and risk assessment of tea products: a case study of Rizhao green tea.

Previous research on pesticides in green tea mainly focused on detection technology but lacked insights into pesticide use during cultivation. To address this gap, a survey was conducted among Rizhao green tea farmers. The survey results showed that most tea farmers were approximately 60 years old and managed small, scattered tea gardens (< 0.067 ha). Notably, tea farmers who had received agricultural training executed more standardized pesticide application practices. Matrine and thiazinone are the most used pesticides. A total of 16 types of pesticides were detected in the tested green tea samples, with 65% of the samples containing residues of at least one pesticide. Notably, higher levels of residues were observed for bifenthrin, cyfluthrin, and acetamiprid. The presence of pesticide residues varied significantly between seasons and regions. The risk assessment results indicated that the hazard quotient (HQ) values for all 16 pesticides detected in green tea were < 1, suggesting that these residue levels do not pose a significant public health concern.

Investigation of heat stress responses and adaptation mechanisms by integrative metabolome and transcriptome analysis in tea plants (Camellia sinensis).

Extreme high temperature has deleterious impact on the yield and quality of tea production, which has aroused the attention of growers and breeders. However, the mechanisms by which tea plant varieties respond to extreme environmental heat is not clear. In this study, we analyzed physiological indices, metabolites and transcriptome differences in three different heat-tolerant tea plant F1 hybrid progenies. Results showed that the antioxidant enzyme activity, proline, and malondialdehyde were significantly decreased in heat-sensitive 'FWS' variety, and the accumulation of reactive oxygen molecules such as H2O2 and O2- was remarkably increased during heat stress. Metabolomic analysis was used to investigate the metabolite accumulation pattern of different varieties in response to heat stress. The result showed that a total of 810 metabolites were identified and more than 300 metabolites were differentially accumulated. Transcriptional profiling of three tea varieties found that such genes encoding proteins with chaperon domains were preferentially expressed in heat-tolerant varieties under heat stress, including universal stress protein (USP32, USP-like), chaperonin-like protein 2 (CLP2), small heat shock protein (HSP18.1), and late embryogenesis abundant protein (LEA5). Combining metabolomic with transcriptomic analyses discovered that the flavonoids biosynthesis pathway was affected by heat stress and most flavonols were up-regulated in heat-tolerant varieties, which owe to the preferential expression of key FLS genes controlling flavonol biosynthesis. Take together, molecular chaperons, or chaperon-like proteins, flavonols accumulation collaboratively contributed to the heat stress adaptation in tea plant. The present study elucidated the differences in metabolite accumulation and gene expression patterns among three different heat-tolerant tea varieties under extreme ambient high temperatures, which helps to reveal the regulatory mechanisms of tea plant adaptation to heat stress, and provides a reference for the breeding of heat-tolerant tea plant varieties.

Skin- and Eco-Friendly Hand Sanitizer: A Novel Composition of Natural Extracts to Prevent the Spread of Respiratory Viruses.

Respiratory diseases caused by viruses are a serious global health threat. Although the use of hand sanitizers containing alcohol and synthetic antiseptic agents is recognized as an effective, simple, and low-cost measure to combat viral transmission, they can harm human health and the environment. Thus, this work aimed to study the efficacy of combining Camellia sinensis and Chamomilla recutita extracts in a skin- and eco-friendly leave-on hand sanitizer to prevent the spread of respiratory viruses. An oil-in-water emulsion containing C. recutita oily extract (5.0%), C. recutita glycolic extract (0.2%) and C. sinensis glycolic extract (5.0%) showed virucidal activity against HAdV-2 (respiratory virus) and two surrogate viruses of SARS-CoV-2 (HSV-1 and MVH-3), showing great potential to prevent the spread of respiratory viruses. These natural extracts combined are also promising to combat a broad spectrum of other viruses, in the form of antiseptic mouthwashes or throat sprays, surface disinfectants, and veterinary products, among others. Complementally, the developed hand sanitizer demonstrated efficacy against bacteria and fungus.

YOLOv8-RMDA: Lightweight YOLOv8 Network for Early Detection of Small Target Diseases in Tea.

In order to efficiently identify early tea diseases, an improved YOLOv8 lesion detection method is proposed to address the challenges posed by the complex background of tea diseases, difficulty in detecting small lesions, and low recognition rate of similar phenotypic symptoms. This method focuses on detecting tea leaf blight, tea white spot, tea sooty leaf disease, and tea ring spot as the research objects. This paper presents an enhancement to the YOLOv8 network framework by introducing the Receptive Field Concentration-Based Attention Module (RFCBAM) into the backbone network to replace C2f, thereby improving feature extraction capabilities. Additionally, a mixed pooling module (Mixed Pooling SPPF, MixSPPF) is proposed to enhance information blending between features at different levels. In the neck network, the RepGFPN module replaces the C2f module to further enhance feature extraction. The Dynamic Head module is embedded in the detection head part, applying multiple attention mechanisms to improve multi-scale spatial location and multi-task perception capabilities. The inner-IoU loss function is used to replace the original CIoU, improving learning ability for small lesion samples. Furthermore, the AKConv block replaces the traditional convolution Conv block to allow for the arbitrary sampling of targets of various sizes, reducing model parameters and enhancing disease detection. the experimental results using a self-built dataset demonstrate that the enhanced YOLOv8-RMDA exhibits superior detection capabilities in detecting small target disease areas, achieving an average accuracy of 93.04% in identifying early tea lesions. When compared to Faster R-CNN, MobileNetV2, and SSD, the average precision rates of YOLOv5, YOLOv7, and YOLOv8 have shown improvements of 20.41%, 17.92%, 12.18%, 12.18%, 10.85%, 7.32%, and 5.97%, respectively. Additionally, the recall rate (R) has increased by 15.25% compared to the lowest-performing Faster R-CNN model and by 8.15% compared to the top-performing YOLOv8 model. With an FPS of 132, YOLOv8-RMDA meets the requirements for real-time detection, enabling the swift and accurate identification of early tea diseases. This advancement presents a valuable approach for enhancing the ecological tea industry in Yunnan, ensuring its healthy development.

High-density genetic map construction and QTL mapping of a zigzag-shaped stem trait in tea plant (Camellia sinensis).

The highly unique zigzag-shaped stem phenotype in tea plants boasts significant ornamental value and is exceptionally rare. To investigate the genetic mechanism behind this trait, we developed BC1 artificial hybrid populations. Our genetic analysis revealed the zigzag-shaped trait as a qualitative trait. Utilizing whole-genome resequencing, we constructed a high-density genetic map from the BC1 population, incorporating 5,250 SNP markers across 15 linkage groups, covering 3,328.51 cM with an average marker interval distance of 0.68 cM. A quantitative trait locus (QTL) for the zigzag-shaped trait was identified on chromosome 4, within a 61.2 to 97.2 Mb range, accounting for a phenotypic variation explained (PVE) value of 13.62%. Within this QTL, six candidate genes were pinpointed. To better understand their roles, we analyzed gene expression in various tissues and individuals with erect and zigzag-shaped stems. The results implicated CsXTH (CSS0035625) and CsCIPK14 (CSS0044366) as potential key contributors to the zigzag-shaped stem formation. These discoveries lay a robust foundation for future functional genetic mapping and tea plant genetic enhancement.

Changes in amino acids, catechins and alkaloids during the storage of oolong tea and their relationship with antibacterial effect.

The storage process has a significant impact on tea quality. Few is known about effect of storage on quality of oolong tea. This study aimed to assess the effect of different storage times on the key chemical components of oolong tea by measuring changes in catechin, free amino acid, and alkaloid content. Variation in the main substances was determined by principal component analysis and heat map analysis. The results revealed notable effects of the storage process on the levels of theanine, epigallocatechin gallate (EGCG), and glutamine. These findings suggest that these compounds could serve as indicators for monitoring changes in oolong tea quality during storage. Additionally, the study observed an increase in the antibacterial ability of tea over time. Correlation analysis indicated that the antibacterial ability against Micrococcus tetragenus and Escherichia coli was influenced by metabolites such as aspartic acid, threonine, serine, gamma-aminobutyric acid, ornithine, alanine, arginine, and EGCG. Overall, this study presents an approach for identifying key metabolites to monitor tea quality effectively with relatively limited data.

Identification and quality evaluation of Lushan Yunwu tea from different geographical origins based on metabolomics.

The relationship between the chemical composition and quality of Lushan Yunwu tea (LYT) from different geographical origins is not clear. Sensory evaluation, metabolomics analyses combined with chemometrics were conducted on LYT from 8 different geographical origins, and altitude was identified as the main factor responsible for the differences among LYT. A total of 32 non-volatile and 27 volatile compounds were identified as marker metabolites to distinguish the origins of high altitudes from those of low altitudes. LYT samples from higher altitude areas contained more free amino acids, sugars, and organic acids, and less catechins, which may contribute to the reduction of bitterness and astringency and the enhancement of umami. The contents of geranylacetone, ethyl hexanoate, ethyl caprylate, 3-carene, d-cadinene, linalool, nerol, and nerolidol in high altitude areas were higher than those in low altitude areas, indicating that LYT from high altitude had strong floral and fruity aroma. The altitudes were positively correlated with pH value, total flavonoids, soluble protein, total free amino acids, and the antioxidant capacities of the LYT. This study provided a theoretical basis for the study of the effect of altitude on tea quality.

Uptake, accumulation, translocation and transformation of seneciphylline (Sp) and seneciphylline-N-oxide (SpNO) by Camellia sinensis L.

Pyrrolizidine alkaloids (PAs) and their N-oxide (PANOs), as emerging environmental pollutants and chemical hazards in food, have become the focus of global attention. PAs/PANOs enter crops from soil and reach edible parts, but knowledge about their uptake and transport behavior in crops is currently limited. In this study, we chose tea (Camellia sinensis L.) as a representative crop and Sp/SpNO as typical PAs/PANOs to analyze their root uptake and transport mechanism. Tea roots efficiently absorbed Sp/SpNO, utilizing both passive and active transmembrane pathways. Sp predominantly concentrated in roots and SpNO efficiently translocated to above-ground parts. The prevalence of SpNO in cell-soluble fractions facilitated its translocation from roots to stems and leaves. In soil experiment, tea plants exhibited weaker capabilities for the uptake and transport of Sp/SpNO compared to hydroponic conditions, likely due to the swift degradation of these compounds in the soil. Moreover, a noteworthy interconversion between Sp and SpNO in tea plants indicated a preference for reducing SpNO to Sp. These findings represent a significant stride in understanding the accumulation and movement mechanisms of Sp/SpNO in tea plants. The insights garnered from this study are pivotal for evaluating the associated risks of PAs/PANOs and formulating effective control strategies.

The fluoride exporter (CsFEX) regulates fluoride uptake/accumulation in Camellia sinensis under different pH.

Fluoride (F) can be absorbed from the environment and hyperaccumulate in leaves of Camellia sinensis without exhibiting any toxic symptoms. Fluoride exporter in C. sinensis (CsFEX) could transport F to extracellular environment to alleviate F accumulation and F toxicity, but its functional mechanism remains unclear. Here, combining with pH condition of C. sinensis growth, the characteristics of CsFEX and mechanism of F detoxification were further explored. The results showed that F accumulation was influenced by various pH, and pH 4.5 and 6.5 had a greater impact on the F accumulation of C. sinensis. Through Non-invasive Micro-test Technology (NMT) detection, it was found that F uptake/accumulation of C. sinensis and Arabidopsis thaliana might be affected by pH through changing the transmembrane electrochemical proton gradient of roots. Furthermore, diverse expression patterns of CsFEX were induced by F treatment under different pH, which was basically up-regulated in response to high F accumulation, indicating that CsFEX was likely to participate in the process of F accumulation in C. sinensis and this process might be regulated by pH. Additionally, CsFEX functioned in the mitigation of F sensitivity and accumulation strengthened by lower pH in Escherichia coli and A. thaliana. Moreover, the changes of H+ flux and potential gradient caused by F were relieved as well in transgenic lines, also suggesting that CsFEX might play an important role in the process of F accumulation. Above all, F uptake/accumulation were alleviated in E. coli and A. thaliana by CsFEX through exporting F-, especially at lower pH, implying that CsFEX might regulate F accumulation in C. sinensis.

Quality characteristics and cooking-induced changes on phenolic compounds of dried green tea noodles.

Incorporating green tea powder (GTP) into wheat flour-based noodles can significantly improve nutritional value. So, this study investigated the effects of GTP (0%, 0.5%, 1%, 1.5%, and 2.0%) on the quality properties of dried green tea noodles (DGTN) and cooking-induced changes to phenolic compounds. Mixolab analysis of wheat flour with GTP showed more water absorption of dough, and the developed dough had a firmer structure. GTP markedly increased the toughness of the noodle sheet. DGTN fortified with GTP showed more stable textural properties during cooking and storage, representing higher hardness and tensile strength. The viscosity and thermal properties of DGTN showed that GTP affected the gelatinization and retrogradation behavior of starch, which were closely related to the textural properties. Overall, DGTN prepared with 1.5% GTP showed better quality properties. However, ultra-performance liquid chromatography-time (UPLC/Q-TOF-mass spectrometry [MS]/MS) analysis showed that cooking by boiling significantly decreased phenolic content in 1.5% DGTN; further analysis revealed that the thermal degradation is a key factor in the loss of polyphenols. Therefore, further studies are necessary to focus on the mechanism of cooking-induced polyphenol loss, which is of great significance for improving the nutritional value of cooked DGTN.

Production of Disinfective Coating Layer to Facial Masks Supplemented with Camellia sinensis Extract.

Although usefulness of masks for protection against respiratory pathogens, accumulation of pathogens on their surface represents a source of infection spread. Here we prepared a plant extract-based disinfecting layer to be used in coating masks thus inhibiting their capacity to transmit airborne pathogens. To reach this, a polypropylene membrane base was coated with a layer of polyvinyledine difluoride polymer containing 500 µg/ml of Camellia sinensis (Black tea) methanolic extract. Direct inhibitory effects of C. sinensis were initially demonstrated against Staphylococcus aureus (respiratory bacteria), influenza A virus (enveloped virus) and adenovirus 1 (non-enveloped virus) which were directly proportional to both extract concentration and incubation time with the pathogen. This was later confirmed by the capacity of the supplemented membrane with the plant extract to block infectivity of the above mentioned pathogens, recorded % inhibition values were 61, 72 and 50 for S. aureus, influenza and adenovirus, respectively. In addition to the disinfecting capacity of the membrane its hydrophobic nature and pore size (154 nm) prevented penetration of dust particles or water droplets carrying respiratory pathogens. In summary, introducing this layer could protect users from infection and decrease infection risk upon handling contaminated masks surfaces.

Antidiabetic Potential of Tea and Its Active Compounds: From Molecular Mechanism to Clinical Evidence.

Diabetes mellitus (DM) is a chronic endocrine disorder that poses a long-term risk to human health accompanied by serious complications. Common antidiabetic drugs are usually accompanied by side effects such as hepatotoxicity and nephrotoxicity. There is an urgent need for natural dietary alternatives for diabetic treatment. Tea (Camellia sinensis) consumption has been widely investigated to lower the risk of diabetes and its complications through restoring glucose metabolism homeostasis, safeguarding pancreatic ß-cells, ameliorating insulin resistance, ameliorating oxidative stresses, inhibiting inflammatory response, and regulating intestinal microbiota. It is indispensable to develop effective strategies to improve the absorption of tea active compounds and exert combinational effects with other natural compounds to broaden its hypoglycemic potential. The advances in clinical trials and population-based investigations are also discussed. This review primarily delves into the antidiabetic potential and underlying mechanisms of tea active compounds, providing a theoretical basis for the practical application of tea and its active compounds against diabetes.

Classification and identification of tea diseases based on improved YOLOv7 model of MobileNeXt.

To address the issues of low accuracy and slow response speed in tea disease classification and identification, an improved YOLOv7 lightweight model was proposed in this study. The lightweight MobileNeXt was used as the backbone network to reduce computational load and enhance efficiency. Additionally, a dual-layer routing attention mechanism was introduced to enhance the model's ability to capture crucial details and textures in disease images, thereby improving accuracy. The SIoU loss function was employed to mitigate missed and erroneous judgments, resulting in improved recognition amidst complex image backgrounds.The revised model achieved precision, recall, and average precision of 93.5%, 89.9%, and 92.1%, respectively, representing increases of 4.5%, 1.9%, and 2.6% over the original model. Furthermore, the model's volum was reduced by 24.69M, the total param was reduced by 12.88M, while detection speed was increased by 24.41 frames per second. This enhanced model efficiently and accurately identifies tea disease types, offering the benefits of lower parameter count and faster detection, thereby establishing a robust foundation for tea disease monitoring and prevention efforts.