Search Results (148)

The impact of seasonality on the aroma quality of tea has been documented in various tea types, but not specifically in oolong tea. This study is the first to explore the complex relationships between seasonality, volatile compounds, and aroma quality in oolong tea. Using Headspace Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC-MS)-based untargeted metabolomics, we analyzed 266 samples of Tieguanyin oolong tea. The data identified linalool, linalool oxides (trans-linalool oxide (furanoid) and trans-linalool oxide (pyranoid)), and their metabolites (diendiol I; hotrienol) as key seasonal discriminants. Four out of the top ten key differential compounds for distinguishing aroma scores were metabolites from fatty acid degradation, namely trans-3-hexenyl butyrate, trans-2-hexenyl hexanoate, hexyl hexanoate, and hexyl 2-methyl butyrate. Approximately one-fifth of the seasonal discriminant volatile compounds were significant in influencing aroma quality. Overall, the impact of seasonality on the aroma quality of finished Tieguanyin oolong tea is marginal. These findings enhance our understanding of the interplay between seasonal variations, volatile composition, and aroma quality in oolong tea. Full article

Concerns about mycotoxin contamination by Alternaria spp. in tomato-based products emphasize the need for understanding the effect of the environment on their production. In the current study, we focused on three species frequently associated with tomato (A. alternata, A. solani, and A. tenuissima) by evaluating the effects of different temperatures (5 to 40 °C) and substrata (PDA and V8) on mycelial growth and the production of mycotoxins (alternariol, alternariol monomethyl ether, and tenuazonic acid). Both biological processes were supported between 5 and 35 °C, with optimal temperatures between 20 and 30 °C, depending on the species. Temperature and its interaction with species significantly (p < 0.05) affected both processes. However, the species factor alone was not significant (p > 0.05), indicating that environmental conditions affect Alternaria spp. growth and mycotoxin production more than the species itself does. Mathematical equations were developed to describe the effect of temperature on mycelial growth, as well as on the production of AOH, AME, and TeA, for each Alternaria species. High concordance (CCC ≥ 0.807) between observed and predicted data and low levels of residual error (RMSE ≤ 0.147) indicated the high goodness of fit of the developed equations, which may be used for the development of models to predict Alternaria contamination both in field and during post-harvest storage. Full article

The simplex strategies of fertilizer management and problems caused by simultaneous precipitation and high-temperature (SPH) climate were the main factors that led to yield loss and quality decline in the continuous cropping of tea chrysanthemum (Dendranthema morifolium ‘Jinsi Huang’). In this study, with sustainable biofertilizers being proposed as a potential solution. However, their effects under such constraints are underexplored. In this study, we compared different proportions of a sustainable dark tea biofertilizer, made with two commonly used fertilizers, by their contributions to the morphological, photosynthetic, and flowering traits of D. morifolium ‘Jinsi Huang’. The results showed that increasing the dark tea biofertilizer application to 4.5 kg·m⁻² significantly enhanced the soil alkali hydrolyzed nitrogen (596.53% increase), available phosphorus (64.11%), and rapidly available potassium (75.56%) compared to the levels in yellow soil. This nutrient enrichment in soil caused D. morifolium ‘Jinsi Huang’ to produce more leaves (272.84% increase) and flower buds (1041.67%), along with a strengthened photosynthetic capacity (higher Fv/Fm values and light saturation point). These improvements alleviated the photoinhibition caused by SPH climate conditions, ultimately leading to significantly higher contents of chlorogenic acid (38.23% increase) and total flavonoids (80.28%) in the harvested flowers compared to the control group. Thus, dark tea biofertilizer is a cost-effective and efficient additive for growing tea chrysanthemum in SPH regions due to improving soil quality and causing nutritional and functional components to accumulate in harvest flowers, which greatly promotes the commercial value of rural revitalization industries centered around tea chrysanthemum. Full article

Integrating organic soil amendments such as vermicompost (VC) and vermicompost tea (VCT) in agriculture has received increasing attention as a sustainable strategy to improve soil fertility, enhance plant growth, and suppress pest infestations. This study aimed to evaluate the effects of varying concentrations of VCT (10%, 20%, and 40%), alone and in combination with VC (2.47 ton/ha), on the development and yield of corn (Zea mays), and suppression of fall armyworm (FAW, Spodoptera frugiperda) infestation. The experiment was conducted in seven raised beds with seven treatments: V0 (control), VCT10, VCT20, VCT40, VC1 + VCT10, VC1 + VCT20, and VC1 + VCT40. Six weekly applications of VCT were applied starting at the V2 stage, and soil and plant nutrient contents were determined post-harvest. Additionally, relative chlorophyll content, height, cob yield, dry biomass, and FAW infestations were assessed. Results show that both VC and VCT significantly enhanced soil nutrient content compared to the control treatment (V0). VCT20 and VC1 + VCT10 improved plant N, K, and micronutrient uptake. Corn treated with VCT10 and VC1 + VCT10 had the highest biomass (6.52 and 6.57 tons/ha, respectively), while VCT20 produced the highest cob yield (6.0 tons/ha), which was more than eight times that of V0. SPAD values and corn height were significantly high across all treatments, with VCT20 achieving the highest SPAD readings while the control achieved the lowest. For FAW infestation, the control treatment experienced moderate infestation. At the same time, there was complete suppression in VCT20 and VCT40 treatments and a reduction in VC + VCT treatments, likely due to the bioactive compounds and beneficial microbes in VC and VCT that strengthened plant immunity. The results suggest that VCT20 is a cost-effective, eco-friendly amendment for improving corn performance and FAW resistance. This study contributes to sustainable agriculture by demonstrating how organic amendments can enhance crop resilience while supporting environmentally friendly farming practices. Full article

Ilex vomitoria Ait. is a star substitute for “tea” in recent years. At present, research on I. vomitoria mainly focuses on its breeding and cultivation, and there are few reports on the seasonal changes of important components such as leaf nutrients. This study focuses on the leaves of the topmost annual branches of I. vomitoria. Leaves were harvested at different stages, and the nutrient elements, antioxidant substances, antioxidant capacity, and aroma components in the leaves were measured and analyzed. The results showed that the content of mineral elements, soluble sugars, vitamin C, amino acids, flavonoids, polyphenols, saponins, caffeine, and catechins, as well as the DPPH free radical scavenging ability, ABTS cation free radical scavenging ability, and FRAP iron ion reduction ability in the leaves of I. vomitoria showed significant differences with seasonal changes. The mineral element content in spring leaves is relatively high. Flavonoids and polyphenols are the main antioxidant substances in the leaves of I. vomitoria, indicating that the antioxidant capacity of spring leaves is the strongest. The content of aroma components in the leaves of I. vomitoria in spring is the highest, with alcohols ranging from 54.93% to 66.08%, followed by ketones from 17.63% to 48.07%, and aldehydes from 21.27% to 38.51%. Overall, spring leaves are more suitable for harvesting, development, and utilization. Full article

The globe artichoke (Cynara cardunculus L. var. scolymus) is a Mediterranean crop valued for its edible capitula and bioactive compounds. Post-harvest residual leaves are among the main by-products of artichoke cultivation and remain largely underutilized. This study reports a comprehensive characterization of the residual leaves of Carciofo di Malegno, an Alpine artichoke landrace. Comparative analysis was conducted against leaves from two commercial cultivars and a commercial herbal tea product. HPLC analysis revealed that Carciofo di Malegno exhibited the lowest levels of secondary metabolites. Cynaropicrin content was 0.52 ± 0.03 mg/g, lower than in the commercial samples, while the phenolic compounds were below the quantification limit. Proximate analysis indicated a distinctive nutritional profile, with significantly higher ash (8.01 ± 0.04%) and crude fiber (35.75 ± 0.29%) contents compared to all reference samples. These findings highlight the potential of Carciofo di Malegno residual leaves as a sustainable source of nutrients for functional food and nutraceutical applications. Their low content of bitter sesquiterpene lactones may enhance palatability, supporting their valorisation within circular economy frameworks. Moreover, their use may contribute to the in situ conservation of this landrace, reinforcing the link between agrobiodiversity preservation and the sustainable exploitation of agricultural by-products. Full article

Sea buckthorn (Hippophae rhamnoides) is a valuable plant rich in biologically active compounds, mainly found in its berries and leaves. The harvesting process, which includes pruning, freezing, and shaking, leaves behind large amounts of biomass and juice-pressing residues, typically composted. The aim of this study is to expand knowledge of the valorization of sea buckthorn secondary raw materials by applying an innovative pressure cyclic solid–liquid (PCSL) extraction method and to develop value-added functional food products. Extraction was performed in 20 and 60 cycles, each lasting from 2 to 10 min. The highest concentrations of proanthocyanidins (5.51 g_CE/L) and total phenolics (12.42 g_GAE/L) were obtained under prolonged conditions, but the L-4 extract (20 cycles × 2 min) was selected for kombucha production due to its favorable balance between efficiency and sustainability. Microbial safety evaluation showed that kombucha with sea buckthorn leaf extract exhibited significantly stronger antimicrobial activity against tested pathogens compared to green tea kombucha. Additionally, sensory analysis revealed higher consumer acceptability of beverages enriched with sea buckthorn extracts. Shotgun metagenomic analysis identified high microbial diversity in the M. gisevii MI-2 starter culture and fermented kombucha products (227 bacteria and 44 eukaryotes), most of which (92.5% bacteria, 77.8% eukaryotes) remain viable and contribute to fermentation dynamics. New biotechnological strategies and genetic modifications raise concerns about the safe use of microorganisms in food production. To address these issues, these findings provide a foundation for future strategies aimed at the safe application of beneficial microorganisms in food biotechnology and support the long-term goals of the European Green Deal by promoting sustainable biomass valorization and circular economy advancement in the food sector. Full article

Native to South Africa, Bush tea is a plant that thrives in various climates. Cultural practices such as mineral nutrition, fertigation, pruning, and harvesting have been shown to influence bush tea’s quality, growth, and yield. This study set out to determine the effects of mulching and deficit irrigation on the growth, yield, and quality of bush tea. Three deficit irrigation treatments (0%, 30%, and 100% Crop evapotranspiration (ETc) on field capacity) and three mulch treatments (sawdust, black plastic mulch, and no mulch) were included in a two-factor experiment, which was set up in a randomized complete block design (RCBD) with three replications. Physiological and growth parameters were taken every two weeks. The number of branches was counted, and measurements of chlorophyll content and the proportion of radiation intercepted by the canopy were recorded. Yield and secondary metabolites such as sugar residuals, fatty acids, and phenols of bush tea were determined after harvest. Growing bush tea under various water regimes showed that a 30% water regime significantly enhanced plant growth characteristics, including the proportion of intercepted radiation, plant height, and both fresh and dry weight. Furthermore, under different water regimes, sawdust improved plant growth in bush tea grown in the field. Black plastic mulch and a 0% water regime produced more compounds beneficial to health than tea treated with half or full irrigation. The extraction of data for Proton Nuclear Magnetic Resonance (NMR) and Mass Spectrometry analyses was conducted for quality components. Our study did not show any distinct structural differences in the tea under different water regimes or mulching. Flavones, phenols, diterpenes, and gardoside were some of the most abundant compounds found in bush tea using mass spectrometry. Principal Component Analysis was performed on the NMR spectral data across 27 samples of bush tea. Full article

Matcha, a finely powdered green tea, has been cherished in Japan for centuries, used in the traditional tea ceremony and nowadays also valued for its health-promoting properties. Cultivated under shaded conditions to enhance chlorophyll production, which gives the typical vibrant green color, matcha is rich in important bioactive compounds, including caffeine, catechins, and theanine. This study analyzes three matcha grades—ceremonial grade 1 (G1), grade 4 (G4), and food grade (FG)—to assess variations in their metabolite profiles. The Bligh–Dyer method was employed to extract polar and non-polar metabolites from organic and hydroalcoholic phases. High-performance thin-layer chromatography (HPTLC) was used for qualitative metabolite analysis, while nuclear magnetic resonance (NMR) spectroscopy was employed for both qualitative and quantitative analyses. Results reveal a decreasing gradient of amino acids and caffeine from grade 1 to food grade, while other metabolites, such as polyphenols, display an increasing trend. These findings suggest that factors such as harvesting time and leaf maturity significantly influence matcha’s chemical composition, providing a scientific basis for its quality differentiation and potential nutraceutical uses. Full article

The flavor profile of white tea emerges from the natural biochemical composition of its tender leaves, a delicate balance profoundly shaped by seasonal growing conditions and tea cultivars. However, the effects of harvest seasons on biochemical and volatile compounds in white teas in southwestern China have not been fully analyzed at present. This study investigated the sensory characteristics, biochemical components, and volatile compounds of ‘Sanhua1951’ spring white tea (SH-S), ‘Sanhua1951’ autumn white tea (SH-A), ‘Fudingdabai’ spring white tea (FD-S), and ‘Fudingdabai’ autumn white tea (FD-A). The results showed that the sensory quality (appearance, taste, and aroma) scores of spring tea were higher than those of autumn tea. Spring teas exhibited significantly higher epigallocatechin, soluble sugar, and amino acid levels than autumn teas (p < 0.05), whereas autumn teas contained greater contents of epicatechin gallate, catechin, caffeine, and polyphenols (p < 0.05), which were responsible for the differences in taste quality observed between samples with different harvest seasons. A total of 90 volatile compounds in four groups were identified through HS-SPME–GC–MS analysis, and spring white teas contained higher contents of and variability in volatile compounds than autumn white teas. According to the OPLS-DA model, 52 and 57 differential volatile compounds (VIP > 1, p < 0.05, and fold change ≥ 2 or ≤0.5) were identified in SH-S vs. SH-A and FD-S vs. FD-A, including (Z)-linalool oxide, (E)-linalool oxide, styrene, phenylethyl alcohol, (Z)-citral, etc. The odor active value (OAV) results indicated that 30 key differential volatile compounds (OAV > 1) were determined in four groups, among which β-ionone, 5,6-epoxy-β-ionone, linalool, and (E)-linalool oxide exhibited particularly high OAVs and contributed more pekoe aroma and floral sensory characteristics. Notably, (E)-linalool oxide, (Z)-jasmone, and δ-cadinene were identified in each cultivar. These findings suggest their potential as seasonal markers, paving the way for the development of white tea ’Sanhua1951’ and ’Fudingdabai’. Full article

Accurate detection of tea shoots in field conditions is a challenging task for production management and harvesting in tea plantations. Deep learning is well-suited for performing complex tasks due to its robust feature extraction capabilities. However, low-complexity models often suffer from poor detection performance, while high-complexity models are hindered by large size and high computational cost, making them unsuitable for deployment on resource-limited mobile devices. To address this issue, a lightweight and high-performance model was developed based on YOLOv5 for detecting tea shoots in field conditions. Initially, a dataset was constructed based on 1862 images of the tea canopy shoots acquired in field conditions, and the “one bud and one leaf” region in the images was labeled. Then, YOLOv5 was modified with a parallel-branch fusion downsampling block and a lightweight feature extraction block. The modified model was then further compressed using model pruning and knowledge distillation, which led to additional improvements in detection performance. Ultimately, the proposed lightweight and high-performance model for tea shoot detection achieved precision, recall, and average precision of 81.5%, 81.3%, and 87.8%, respectively, which were 0.4%, 0.6%, and 2.0% higher than the original YOLOv5. Additionally, the model size, number of parameters, and FLOPs were reduced to 8.9 MB, 4.2 M, and 15.8 G, representing decreases of 90.6%, 90.9%, and 85.3% compared to YOLOv5. Compared to other state-of-the-art detection models, the proposed model outperforms YOLOv3-SPP, YOLOv7, YOLOv8-X, and YOLOv9-E in detection performance while maintaining minimal dependency on computational and storage resources. The proposed model demonstrates the best performance in detecting tea shoots under field conditions, offering a key technology for intelligent tea production management. Full article

Applying a top dressing of nitrogen fertilizer before harvesting spring tea is vital for producing high-quality spring tea. However, the interaction between the sprouting phenological characteristics of various cultivars and the timing of top dressing remains unclear. A field trial was conducted to investigate such interaction. Urea enriched with ¹⁵N was applied to soil of the early-sprouting cultivar Jia-ming-1 (JM1) and the late-sprouting cultivar Tie-guan-yin (TGY) on 29 January (early application, EApp) or 10 March (late application, LApp), respectively. The bud density and yield of young spring shoots were significantly decreased in LApp compared to EApp. Such differences were more remarkable in the early-sprouting cultivar (JM1) than in the late-sprouting cultivar (TGY). The N_dff (N derived from ¹⁵N-enriched urea) in mature leaves and young spring shoots as well as the amount of ¹⁵N in young spring shoots were all higher in EApp than in LApp. N_dff in both mature leaves (R² = 0.99, p < 0.001) and young spring shoots (R² = 0.61–0.89, p < 0.01) could be well predicted by the growing degree days of the duration between the N fertilization and sampling. N_dff and ¹⁵N concentrations in mature leaves were significantly correlated with the content of nitrate and the ratio of ammonium to total inorganic nitrogen. Partial least squares path modeling revealed that thermal condition directly affected soil N supply and soil pH and thereby affected N_dff in mature leaves and young spring shoots. Our findings highlight the importance of early pre-spring topdressing of N fertilizer to improve the yield and N use efficiency of spring tea in both early- and late-sprouting tea cultivars. The work identified a synergistic effect of N uptake by tea plants, N transformation, and soil pH related to the thermo-conditions of early and late N topdressing. Full article

During the harvesting and preparation of tea, it is common for tea to become mixed with some impurities. Eliminating these impurities is essential to improve the quality of famous green tea. At present, this sorting procedure heavily depends on manual efforts, which include high labor intensity, low sorting efficiency, and high sorting costs. In addition, the hardware performance is poor in actual production, and the model is not suitable for deployment. To solve this technical problem in the industry, this article proposes a lightweight algorithm for detecting and sorting impurities in premium green tea in order to improve sorting efficiency and reduce labor intensity. A custom dataset containing four categories of impurities was created. This dataset was employed to evaluate various YOLOv8 models, ultimately leading to the selection of YOLOv8n as the base model. Initially, four loss functions were compared in the experiment, and Focaler_mpdiou was chosen as the final loss function. Subsequently, this loss function was applied to other YOLOv8 models, leading to the selection of YOLOv8m-Focaler_mpdiou as the teacher model. The model was then pruned to achieve a lightweight model at the expense of detection accuracy. Finally, knowledge distillation was applied to enhance its detection performance. Compared to the base model, it showed advancements in P, R, mAP, and FPS by margins of 0.0051, 0.0120, and 0.0094 and an increase of 72.2 FPS, respectively. Simultaneously, it achieved a reduction in computational complexity with GFLOPs decreasing by 2.3 and parameters shrinking by 860350 B. Afterwards, we further demonstrated the model’s generalization ability in black tea samples. This research contributes to the technological foundation for sophisticated impurity classification in tea. Full article

Tea leaf diseases are among the most critical factors affecting the yield and quality of tea harvests. Due to climate change and widespread pesticide use in tea cultivation, these diseases have become more prevalent. As the demand for high-quality tea continues to rise, tea has assumed an increasingly prominent role in the global economy, thereby rendering the continuous monitoring of leaf diseases essential for maintaining crop quality and ensuring sustainable production. In this context, developing innovative and sustainable agricultural policies is vital. Integrating artificial intelligence (AI)-based techniques with sustainable agricultural practices presents promising solutions. Ensuring that the outputs of these techniques are interpretable would also provide significant value for decision-makers, enhancing their applicability in sustainable agricultural practices. In this study, advanced deep learning architectures such as ResNet50, MobileNet, EfficientNetB0, and DenseNet121 were utilized to classify tea leaf diseases. Since low-resolution images and complex backgrounds caused significant challenges, an ensemble learning approach was proposed to combine the strengths of these models. The generalization performance of the ensemble model was comprehensively evaluated through statistical cross-validation. Additionally, Grad-CAM visualizations demonstrated a clear correspondence between diseased regions and disease types on the tea leaves. Thus, the models could detect diseases under varying conditions, highlighting their robustness. The ensemble model achieved high predictive performance, with precision, recall, and F1-score values of 95%, 94%, and 94% across folds. The overall classification accuracy reached 96%, with a maximum standard deviation of 2% across all dataset folds. Additionally, Grad-CAM visualizations demonstrated a clear correspondence between diseased regions and specific disease types on tea leaves, confirming the ability of models to detect diseases under varying conditions accurately and highlighting their robustness. Full article

Selecting and breeding tea plant varieties with low nitrogen tolerance is crucial for reducing the application of nitrogen fertilizer in tea gardens and promoting the green and sustainable production of tea. Thus, a split-plot designed field experiment was conducted in a subtropical tea garden in China, where ten distinct cultivars were planted and exposed to two different levels of nitrogen (N) supply. This study aimed to assess the response of these cultivars to normal (450 kg ha⁻¹) and low (150 kg ha⁻¹) N fertilization treatments and to evaluate their tolerance to low N conditions. The results revealed notable differences in both the growth and biomass responses of the tea cultivars to N supply levels. Under low N supply, tea tree height, pruned litter biomass, and its nitrogen accumulation were all significantly lower than those under the normal N level. There was also a significant interaction effect between the cultivar and N level in the one-hundred-bud weight, new shoot yield, and its nitrogen content, respectively. The amount of total N uptake by harvested new shoots was relatively low, whereas a considerable amount of N was returned to the garden through pruned biomass. The aboveground biomass and its nitrogen accumulation could be considered as critical indicators for identifying nitrogen-tolerant cultivars with a variation coefficient by 20% and 20.57%, respectively. Additionally, cluster analysis showed that BY1 and LJ43 were strong low N-tolerant cultivars, while HJY was the most N-sensitive cultivar, closely followed by the ZN117 tea plants. In conclusion, significant disparities were observed in the adaptability of different tea cultivars to low N fertilization under the ambient field conditions. This study provided valuable theoretical insights and practical references for selecting N-tolerant tea varieties and reducing N fertilizer consumption in tea gardens. Full article