Search Results (74)

Precise quality screening of tea tree seeds is crucial for the development of the tea industry. This study proposes a high-precision quality classification method for tea tree seeds by integrating mid-infrared (MIR) spectroscopy with an improved deep learning model. Four types of tea tree seeds in different states were prepared, and their spectral data were collected and preprocessed using Savitzky–Golay (SG) filtering and wavelet transform. Aiming at the deficiencies of DenseNet121 in one-dimensional spectral processing, such as insufficient generalization ability and weak feature extraction, the ECA-DenseNet model was proposed. Based on DenseNet121, the Batch Channel Normalization (BCN) module was introduced to reduce the dimensionality via 1 × 1 convolution while preserving the feature extraction capabilities, the Attention–Convolution Mix (ACMix) module was integrated to combine convolution and self-attention, and the Efficient Channel Attention (ECA) mechanism was utilized to enhance the feature discriminability. Experiments show that ECA-DenseNet achieves 99% accuracy, recall, and F1-score for classifying the four seed quality types, outperforming the original DenseNet121, machine learning models, and deep learning models. This study provides an efficient solution for tea tree seeds detection and screening, and its modular design can serve as a reference for the spectral classification of other crops. Full article

In response to issues such as low resolution, severe occlusion, and insufficient fine-grained feature extraction in tea plantation disease detection, this study proposes an improved YOLOv10 network based on low-altitude unmanned aerial vehicle remote sensing for the detection of diseases in Yunnan large-leaf tea trees. Through the use of a Shape-IoU optimized loss function, a Wavelet Transform Convolution to enhance the network’s Backbone, and a Histogram Transformer to optimize the network’s Neck, the detection accuracy and localization precision of disease targets were significantly improved. Through testing of common diseases, the research results indicate that, for the improved YOLOv10 network, the Box Loss, Cls Loss, and DFL Loss were reduced by 15.94%, 13.16%, and 8.82%, respectively, in the One-to-Many Head, and by 14.58%, 17.72%, and 8.89%, respectively, in the One-to-One Head. Compared to the original YOLOv10 network, precision, recall, and F1 increased by 3.4%, 10.05%, and 6.75%, respectively. The improved YOLOv10 network not only effectively addresses phenomena such as blurry images, complex backgrounds, strong illumination, and occlusion in disease detection, but also demonstrates high levels of precision and recall, thereby providing robust technological support for precision agriculture and decision-making, and to a certain extent promoting the development of agricultural modernization. Full article

Distinguishing vegetation types from satellite images has long been a goal of remote sensing, and the combination of multi-source and multi-temporal remote sensing images for vegetation classification is currently a hot topic in the field. In species-rich mountainous environments, this study selected four remote sensing images from different seasons (two aerial images, one WorldView-2 image, and one UAV image) and proposed a vegetation classification method integrating hierarchical extraction and object-oriented approaches for 11 vegetation types. This method innovatively combines the Random Forest algorithm with a decision tree model, constructing a hierarchical strategy based on multi-temporal feature combinations to progressively address the challenge of distinguishing vegetation types with similar spectral characteristics. Compared to traditional single-temporal classification methods, our approach significantly enhances classification accuracy through multi-temporal feature fusion and comparative experimental validation, offering a novel technical framework for fine-grained vegetation classification under complex land cover conditions. To validate the effectiveness of multi-temporal features, we additionally performed Random Forest classifications on the four individual remote sensing images. The results indicate that (1) for single-temporal images classification, the best classification performance was achieved with autumn images, reaching an overall classification accuracy of 72.36%, while spring images had the worst performance, with an accuracy of only 58.79%; (2) the overall classification accuracy based on multi-temporal features reached 89.10%, which is an improvement of 16.74% compared to the best single-temporal classification (autumn). Notably, the producer accuracy for species such as Quercus acutissima Carr., Tea plantations, Camellia sinensis (L.) Kuntze, Pinus taeda L., Phyllostachys spectabilis C.D.Chu et C.S.Chao, Pinus thunbergii Parl., and Castanea mollissima Blume all exceeded 90%, indicating a relatively ideal classification outcome. Full article

Pre- and post-milking teat antisepsis is one of the most effective methods for reducing the incidence of mastitis. Plant extracts have proven effective in reducing microorganisms, providing a natural alternative for antisepsis, along with additional benefits for teat health. This study aimed to evaluate the antimicrobial and antiseptic effects of two newly formulated products, used as pre-dipping and post-dipping agents, respectively, based on plant extracts from papain (Carica papaya), aloe vera (Aloe barbadensis), andiroba (Carapa guianensis), copaiba (Copaifera officinalis), tea tree (Melaleuca alternifolia), and barbatimão (Stryphnodendron barbatiman). Minimum inhibitory concentration tests were performed in vitro, along with microbiological analyses of different bacterial groups and in vivo compliance assessments to evaluate the antimicrobial activity of the formulations, as well as the molecular identification of Staphylococcus aureus. The results demonstrated that the products were effective in vitro against the main pathogens that cause mastitis, including Staphylococcus aureus, Streptococcus agalactiae, and Escherichia coli. In the in vivo assays, similar performance was observed between the tested products and the control products, indicating that the plant-extract-based formulations, applied as pre-dipping and post-dipping agents, effectively reduced the microbial load on the teats. The effects were equivalent to those of hydrogen-peroxide- and iodine-based products, being able to reduce the total microbial load by more than 80%. Full article

The primary objective of this research was to develop an efficient method for accurately identifying and localizing weeds in ecological tea garden environments, aiming to enhance the quality and yield of tea production. Weed competition poses a significant challenge to tea production, particularly due to the small size of weed plants, their color similarity to tea trees, and the complexity of their growth environment. A dataset comprising 5366 high-definition images of weeds in tea gardens has been compiled to address this challenge. An enhanced U-Net model, incorporating a Double Attention Mechanism and an Atrous Spatial Pyramid Pooling module, is proposed for weed recognition. The results of the ablation experiments show that the model significantly improves the recognition accuracy and the Mean Intersection over Union (MIoU), which are enhanced by 4.08% and 5.22%, respectively. In addition, to meet the demand for precise weed management, a method for determining the center of weed plants by integrating the center of mass and skeleton structure has been developed. The skeleton was extracted through a preprocessing step and a refinement algorithm, and the relative positional relationship between the intersection point of the skeleton and the center of mass was cleverly utilized to achieve up to 82% localization accuracy. These results provide technical support for the research and development of intelligent weeding equipment for tea gardens, which helps to maintain the ecology of tea gardens and improve production efficiency and also provides a reference for weed management in other natural ecological environments. Full article

Aeromonas spp. is a major pathogen in aquaculture with a great negative economic impact. Essential oils (EOs) are compounds of the secondary metabolism of plants known for their antibacterial and antibiofilm activities. In this study, in vitro antibacterial activity of eight EOs: tea tree (extracted from Melaleuca alternifolia), eucalyptus (extracted from Eucalyptus globulus LABILL.), knee timber (extracted from Pini mungo L.), peppermint (extracted from Mentha piperita L.), oregano (extracted from Origanum vulgare L.), rosemary (extracted from Rosmarinus officinalis L.), thyme (extracted from Thymus vulgaris L.) and pine EO (extracted from Pinus silvestris L.), obtained from Calendula a.s., was evaluated. Their antibacterial activity was demonstrated against Aeromonas spp. isolates. Oregano and thyme EOs showed the strongest activity against all tested isolates at low concentrations, followed by tea tree and peppermint EOs. The MIC value ranged from 0.06 µL/mL to 1.0 µL/mL. The tested EOs showed a significant antibiofilm activity against biofilm-forming isolates with MBIC₅₀ ranging from 0.015 µL/mL to 0.25 µL/mL. All tested isolates were obtained from rainbow trout free of clinical signs of infection. Twelve isolates of Aeromonas salmonicida subsp. masoucida, four Aeromonas hydrophila, and four isolates of Aeromonas veronii were identified. The results of the in vitro study showed a significant effect of EOs against Aeromonas spp., which confirmed their potential for use in aquaculture as a prevention against bacterial diseases and a way of reducing the use of antibiotics. Full article

Bacterial cellulose (BC) is a biodegradable polymer resembling paper after being dried. It finds a growing number of applications in many branches of industry and in medicine. In the present study, BC was produced after Gluconacetobacter hansenii ATCC 23769 strain culture and used as a matrix for plant extracts (tulsi, brahmi, lemon, blackberry, nettle root, and nettle leave) and essential oils (cinnamon, sage, clove, mint, thyme, lemongrass, rosemary, lemon, anise, tea tree, lime, grapefruit, and tangerine), and the antimicrobial properties of these biomaterials was determined. The growth-inhibiting effects of plant extracts and essential oils combined with BC were analyzed against five Cronobacter species isolated from food matrix and two reference strains from the ATCC (513229 and 29544). Additional analyses were conducted for BC water activity and for its capability to absorb biologically active plant compounds. The cellulose matrix with a 50% extract from brahmi was found to effectively inhibit the growth of the selected Cronobacter strains. The other plant water extracts did not show any antimicrobial activity against the tested strains. It was demonstrated that BC soaked with thyme essential oil was characterized with the strongest antimicrobial activity in comparison to the other tested EOs. These study results indicate the feasibility of deploying BC impregnated with natural plant components as an active and environmentally-friendly packaging material. Full article

Due to the complex shape of the tea tree canopy and the large undulation of a tea garden terrain, the quality of fresh tea leaves harvested by existing tea harvesting machines is poor. This study proposed a tea canopy surface profiling method based on 2D LiDAR perception and investigated the extraction and fitting methods of canopy point clouds. Meanwhile, a tea profiling harvester prototype was developed and field tests were conducted. The tea profiling harvesting device adopted a scheme of sectional arrangement of multiple groups of profiling tea harvesting units, and each unit sensed the height information of its own bottom canopy area through 2D LiDAR. A cross-platform communication network was established, enabling point cloud fitting of tea plant surfaces and accurate estimation of cutter profiling height through the RANSAC algorithm. Additionally, a sensing control system with multiple execution units was developed using rapid control prototype technology. The results of field tests showed that the bud leaf integrity rate was 84.64%, the impurity rate was 5.94%, the missing collection rate was 0.30%, and the missing harvesting rate was 0.68%. Furthermore, 89.57% of the harvested tea could be processed into commercial tea, with 88.34% consisting of young tea shoots with one bud and three leaves or fewer. All of these results demonstrated that the proposed device effectively meets the technical standards for machine-harvested tea and the requirements of standard tea processing techniques. Moreover, compared to other commercial tea harvesters, the proposed tea profiling harvesting device demonstrated improved performance in harvesting fresh tea leaves. Full article

The use of chemical pesticides in agriculture contributes to soil, water and air pollution, biodiversity loss, and injury to non-target species. The European Commission has already established a Harmonized Risk Indicator to quantify the progress in reducing the risks linked to pesticides. Therefore, there is an increasing need to promote biopesticides, or so-called low-risk pesticides (LRP). Tea tree oil (TTO) is known for its antiseptic, antimicrobial, antiviral, antifungal, and anti-inflammatory properties. TTO has been extensively studied in pest management as well as in the pharmaceutical and cosmetic industry; there are already products based on its active substances on the market. This review focuses on the overall evaluation of TTO in terms of effectiveness and safety as a biopesticide for the first time. The collected data can be an added value for further evaluation of TTO in terms of the authorization extension as a fungicide in 2026. Full article

The biodeterioration of wooden cultural heritage is a severe problem worldwide and fungi are the main deteriorating agents. The identification of effective natural products, safer for humans and the environment, is a current challenge. Ten deteriorated archaeological objects (a wooden statue of a seated man, an anthropoid wooden coffin with a cartonnage mummy of Nespathettawi, and a wooden box of Padimen’s son), stored at the Egyptian museum in Cairo, were considered here. The wood species of the three most deteriorated objects were previously identified as Acacia nilotica, Ficus sycomorus, and Tamarix gennessarensis. Twenty-six fungal species were isolated and identified from the wooden objects and the four most frequent species belonged to the genus Aspergillus. Fourteen fungal species among those isolated showed the greatest biodeterioration activity on the experimental wood blocks of the archaeological objects. The antifungal activities of several eco-friendly plant essential oils (from cinnamon, eucalyptus, frankincense, geranium, lavender, lemongrass, menthe, rosemary, tea tree, and thyme) and plant extracts (from basil, eucalyptus, henna, melia, and teak) were tested against the fungal species with the greatest biodeterioration activity. The essential oils (Eos) were more effective than the plant extracts. Thyme EO, followed by geranium and cinnamon ones, was the most active (minimum inhibitory concentrations: 0.25–1 µL/mL). These EO; also showed inhibitory effects on the enzymatic activities (cellulase, amylase, and protease) of the four most dominant fungal species. Thymol and p-cymene were the two main components of thyme oil, while geraniol and beta-citronellol were those of geranium oil; eugenol and caryophyllene were those of the cinnamon EO. Thyme oil applied to the most deteriorated experimental aged A. nilotica wooden cubes inoculated with the four highly frequent fungal species was effective in wood preservation. Moreover, no significant interference was observed in the wood before and after thyme treatment. Thyme oil seems to be a promising eco-friendly antifungal agent for the preservation of archaeological wooden artefacts. Full article

The Cupressaceae family includes species considered to be medicinal. Their essential oil is used for headaches, colds, cough, and bronchitis. Cedar trees like Chamaecyparis lawsoniana (C. lawsoniana) are commonly found in urban areas. We investigated whether C. lawsoniana exerts some of its effects by modifying airway smooth muscle (ASM) contractility. The leaves of C. lawsoniana (363 g) were pulverized mechanically, and extracts were obtained by successive maceration 1:10 (w:w) with methanol/CHCl₃. Guinea pig tracheal rings were contracted with KCl, tetraethylammonium (TEA), histamine (HIS), or carbachol (Cch) in organ baths. In the Cch experiments, tissues were pre-incubated with D-600, an antagonist of L-type voltage-dependent Ca²⁺ channels (L-VDCC) before the addition of C. lawsoniana. Interestingly, at different concentrations, C. lawsoniana diminished the tracheal contractions induced by KCl, TEA, HIS, and Cch. In ASM cells, C. lawsoniana significantly diminished L-type Ca²⁺ currents. ASM cells stimulated with Cch produced a transient Ca²⁺ peak followed by a sustained plateau maintained by L-VDCC and store-operated Ca²⁺ channels (SOCC). C. lawsoniana almost abolished this last response. These results show that C. lawsoniana, and its active metabolite quercetin, relax the ASM by inhibiting the L-VDCC and SOCC; further studies must be performed to obtain the complete set of metabolites of the extract and study at length their pharmacological properties. Full article

Double-layered textile sweat-absorbing underarm pads with a natural antimicrobial treatment can be used to solve the problem of the wetness sensation in the case of increased physical activity or hyperhidrosis. In addition, changeable antimicrobial active underarm pads help to decrease the number of clothing washings, i.e., reducing water consumption and pollution. Another aspect of sustainability is that the underarm pads can be produced from clothing production waste. The moisture absorption capability of six hydrophilic cellulose-based knitted fabrics and two hydrophobic synthetic woven fabrics was investigated. It was found that the best result for next-to-skin moisture absorption and next-to-clothing protection against moisture penetration was achieved by using a double-layered underarm pad composed of a cotton-based fleece knitted structure in the next-to-skin layer and a very thin and tight 100% PA woven fabric in the outer layer. Four samples of impregnated liquid with herbal extracts and essential oils were prepared, and antimicrobial activity was evaluated using the discus method. Textile impregnated with tea tree essential oil, nutmeg, and birch extracts had the highest antimicrobial activity against Gram-positive bacteria—Staphylococcus aureus, Staphylococcus epidermidis, and Bacillus cereus. Full article

Ningnanmycin is a widely used antibiotic in agricultural production that effectively controls fungal and viral diseases in tea trees and chrysanthemums. The polarity characteristic of ningnanmycin has posed limitations on the development of robust detection methods, thereby hindering effective monitoring and control measures. By combining cation exchange solid phase extraction (SPE) with hydrophilic interaction chromatography tandem mass spectrometry (HILIC-MS/MS), we have effectively tackled the issue pertaining to the separation and retention of ningnanmycin. The average recoveries of ningnanmycin in green tea, black tea, and chrysanthemum were 77.3–82.0%, 80.1–81.5%, and 74.0–80.0%, respectively. The intraday and interday relative standard deviations (RSDs) were below and equal to 7.7%. Good linearity was observed in the concentration range of 1–1000 μg/L (R2 > 0.998). The limits of detection (LODs) ranged from 1.1 μg/kg to 7.1 μg/kg, and the limits of quantification (LOQs) ranged from 3.6 μg/kg to 23.7 μg/kg for ningnanmycin. These results indicate the good accuracy, repeatability, reproducibility, and sensitivity of the method. It is suitable for detecting ningnanmycin in tea and chrysanthemum. Full article

In this study, the influence of the incorporation of eucalyptus (EO), tea tree (TT) and rosemary (RO) essential oils and Chiriyuyo extract (CE) on the structure and properties of thermoplastic starch (TPS) obtained from potato starch, glycerin and water was evaluated. All oils and the extract were used at a concentration of 0.5 g/100 g of TPS, while for TT, the effect of the concentration was also studied. The mixtures obtained were processed by extrusion and thermocompression molding. The sheets were characterized by XRD, FTIR, TGA, SEM and analyses of their mechanical properties, antimicrobial characteristics and biodegradability. The results show that the use of small concentrations of the oils in 70TPS does not induce changes in the TPS structure according to the results of XRD, FTIR and TGA, with each essential oil and CE affecting the mechanical properties unevenly, although in all cases, antimicrobial activity was obtained, and the biodegradability of TPS in soil was not modified. An increase in the concentration of TT in 60TPS causes marked changes in the crystallinity of TPS, providing a greater modulus with a higher concentration of TT. Regardless of the amount of TT, all sheets maintain antimicrobial characteristics, and their biodegradation in soil is delayed with a higher oil content. Full article

Alzheimer’s disease manifests as a complex pathological condition, with neuroinflammation, oxidative stress and cholinergic dysfunction being a few of the many pathological changes. Due to the complexity of the disease, current therapeutic strategies aim at a multitargeted approach, often relying on a combination of substances with versatile and complementary effects. In the present study, a unique combination of α-lipoic acid, citicoline, extracts of leaves from olive tree and green tea, vitamin D3, selenium and an immune-supporting complex was tested in scopolamine-induced dementia in rats. Using behavioral and biochemical methods, we assessed the effects of the combination on learning and memory, and elucidated the mechanisms of these effects. Our results showed that, compared to its components, the experimental combination was most efficient in improving short- and long-term memory as assessed by the step-through method as well as spatial memory as assessed by T-maze and Barnes maze underlined by decreases in AChE activity (p < 0.05) and LPO (p < 0.001), increases in SOD activity in the cortex (p < 0.05) and increases in catalase (p < 0.05) and GPx (p < 0.01) activities and BDNF (p < 0.001) and pCREB (p < 0.05) levels in the hippocampus. No significant histopathological changes or blood parameter changes were detected, making the experimental combination an effective and safe candidate in a multitargeted treatment of AD. Full article