Tea Planting Research Articles

Effect of long-term land use on the nosZI- and nosZII-containing microbial communities

Nitrous oxide (N2O) reduction plays a crucial role in mitigating N2O emissions from terrestrial ecosystems, but the function and distribution pattern of nosZI- and nosZII-containing N2O reducers in different land use remains largely unexplored. Here, soil samples were collected from a long-term land use experiment, including conventional agriculture (CA), tea planting (TP), natural forest (NF), and pine forest (PF). Soil potential N2O-reducing ability, and the abundance and community composition of nosZI and nosZII genes were determined. Both the N2O reducing capacity and the abundance of nosZI and nosZII genes followed the order of CA > TP > NF > PF, and the nosZII abundance was significantly higher than that of nosZI in all samples. Although different land use induced significant shifts in the community structure of both nosZI and nosZII-containing N2O reducers, their response strategies were different. Approximately 37 %–61 % of the total nosZI OTUs were shared by all land use types, and these common OTUs contributed over 90 % of the total relative abundance. In contrast, the proportion of the common nosZII OTUs varied widely from 7 % (CA) to 51 % (PF), and the corresponding relative abundance shifted from 37 % (CA) to 94 % (NF). In conclusion, agricultural practices significantly increased the abundance and capacity of N2O reducers. The nosZI-containing community was relatively stable, while that of nosZII was more sensitive to different land use.

Effects of tea planting age on soil microbial biomass C:N:P stoichiometry and microbial quotient

Effects of tea planting age on soil microbial biomass C:N:P stoichiometry and microbial quotient

Soil resistance to flowing water erosion as affected by tea planting age in Three Gorges Reservoir Area of China

Soil erosion resistance is influenced by intrinsic soil properties and multiple external factors. This study investigated the effect of tea planting age on soil resistance to flowing water erosion (reflected by rill erodibility (Kr) and critical shear stress (τc)) in Three Gorges Reservoir Area. One slope farmland (as the control) and five tea plantations cultivated for 3 to 34 years were selected for sampling sites. The results indicated that bulk density (BD), soil cohesion (Coh), water stable aggregate (WSA), mean weight diameter (MWD), soil organic carbon (SOC), litter density (LD), and root mass density (RMD) increased generally with tea planting age. Compared to the control, Kr of tea plantations reduced by 71.1%–85.3%. The temporal variation in soil erosion resistance was controlled greatly by the variations in most near-surface characteristics. Kr decreased with WSA, Coh, LD, RMD, and SOC following a power function (P < 0.01); τc increased with MWD, LD, RMD, and SOC as an exponential function, with BD a power function, and Coh a logarithmic function (P < 0.01). In this study, Kr could be simulated well by WSA and LD with a power function, and τc could be simulated well by MWD and RMD with an exponential function.

Evaluation on real-time self-organization algorithm of forest cultivation, tea planting and tea processing for sustainable ecosystem management of agricultural water resources

Abstract Agricultural water resources are water resources that can be used for agricultural production, including surface water, groundwater and soil water. The sustainable use of water resources is of great significance to agriculture and rural economy. In the context of climate change and the increasing crisis of water resources, how to effectively use forest resources and other natural resources to achieve sustainable management of agricultural water ecosystems has become an increasingly urgent issue. Therefore, this paper proposed a real-time self-organization algorithm for forest cultivation, tea planting and tea processing for sustainable ecosystem management of agricultural water resources. This paper first described the sustainable ecosystem of agricultural water resources, carried out optimization analysis on tea planting and processing technology, using the genetic optimization algorithm based on decision tree and then carried out an experimental analysis on a tea garden. It can be seen from the data that the average monthly temperature of the tea garden cultivated by the algorithm in this paper was between 13.4 and 20.5 °C and the average annual temperature was 16.16 °C. However, the average monthly temperature of the traditional cultivation method was between 11.5 and 16.8 °C and the average annual temperature was 13.64 °C.

Determination of nitrogen sources and losses in surface runoff from different lands at a watershed scale.

Nitrogen (N) loss by surface runoff inevitably results in severe N pollution and eutrophication of aquatic ecosystems. In this study, surface runoff from different land uses in the East Tiaoxi River watershed was collected, and the N concentrations, sources and losses were measured using the dual isotope (δ15N-NO3- and δ18O-NO3-), a Bayesian isotopic mixing (SIAR) model and Soil Conservation Service Curve Number (SCS-CN) method. The results showed that the N concentrations in surface runoff from agricultural lands were higher than those from urban areas and forestlands, and nitrate (NO3-), particulate nitrogen (PN) and dissolved organic nitrogen (DON) were the major forms of N in surface runoff in the East Tiaoxi River watershed. The total loss rate of total nitrogen (TN) from surface runoff in the East Tiaoxi River watershed was 5.38kg·ha-1·a-1, with NO3--N (46%) contributing the most to TN loss. The TN, and NO3--N loss rates in surface runoff from tea planting lands (21.08kg·ha-1·a-1, 11.98kg·ha-1·a-1) and croplands (16.93kg·ha-1·a-1, 10.96kg·ha-1·a-1) were high, those from vegetable lands and urban areas were medium, and those from economic and natural forestlands were low in the East Tiaoxi River watershed. The NO3--N contributions of chemical fertiliser (CF), soil N (SN), sewage/manure (SM), and atmospheric deposition (AD) in surface runoff in the East Tiaoxi River watershed were 124.32 × 103, 104.84 × 103, 82.25 × 103 and 58.69 × 103kg·a-1, respectively. The N pollutant losses in surface runoff from agricultural lands (croplands with rice growing, vegetable lands and tea planting lands) were responsible for most of the N pollutants being transported into the East Tiaoxi River systems.

Comparison of machine learning and deep learning models for evaluating suitable areas for premium teas in Yunnan, China.

Tea is an important economic crop in Yunnan, and the market price of premium teas such as Lao Banzhang is significantly higher than ordinary teas. For planting lands to promote, the tea industry to develop and minority lands' economies to prosper, it is vital to evaluate and analyze suitable areas for premium tea cultivation. Climate, terrain, soil, and green cropping system in the premium tea planting areas were used as evaluation variables. The suitability of six machine learning models for predicting suitable areas of premium teas were evaluated. FA+ResNet demonstrated the best performance with an accuracy score of 0.94 and a macro-F1 score of 0.93. The suitable areas of premium teas were mainly located in the southern catchment of LancangJiang River, south-central part of Dehong, a few areas in the mid-west of Lincang, central scattered areas of Pu'er, most of the southern western part of Xishuangbanna and the southern edge of Honghe. Annual mean temperature, annual mean precipitation, mist belt, annual mean relative humidity, soil type and elevation were the key components in evaluating the suitable areas of premium teas in Yunnan.

Transcriptome-based variations effectively untangling the intraspecific relationships and selection signals in Xinyang Maojian tea population.

As one of the world's top three popular non-alcoholic beverages, tea is economically and culturally valuable. Xinyang Maojian, this elegant green tea, is one of the top ten famous tea in China and has gained prominence for thousands of years. However, the cultivation history of Xinyang Maojian tea population and selection signals of differentiation from the other major variety Camellia sinensis var. assamica (CSA) remain unclear. We newly generated 94 Camellia sinensis (C. sinensis) transcriptomes including 59 samples in the Xinyang area and 35 samples collected from 13 other major tea planting provinces in China. Comparing the very low resolution of phylogeny inferred from 1785 low-copy nuclear genes with 94C. sinensis samples, we successfully resolved the phylogeny of C. sinensis samples by 99,115 high-quality SNPs from the coding region. The sources of tea planted in the Xinyang area were extensive and complex. Specifically, Shihe District and Gushi County were the two earliest tea planting areas in Xinyang, reflecting a long history of tea planting. Furthermore, we identified numerous selection sweeps during the differentiation of CSA and CSS and these positive selection genes are involved in many aspects such as regulation of secondary metabolites synthesis, amino acid metabolism, photosynthesis, etc. Numerous specific selective sweeps of modern cultivars were annotated with functions in various different aspects, indicating the CSS and CSA populations possibly underwent independent specific domestication processes. Our study indicated that transcriptome-based SNP-calling is an efficient and cost-effective method in untangling intraspecific phylogenetic relationships. This study provides a significant understanding of the cultivation history of the famous Chinese tea Xinyang Maojian and unravels the genetic basis of physiological and ecological differences between the two major tea subspecies.

Behavior, Characteristics and Sources of Microplastics in Tea

Microplastics have become a widespread environmental concern because they are found in most tested places, including the air we breathe and the food and beverages we consume. To explore the current status of microplastic pollution and future research trends in tea, we reviewed the distribution, abundance, shape, size and sources of microplastics in tea. Microplastics are plastic particles that are 5 mm in diameter or less. Those found in tea and tea gardens originate from agricultural plastic films, plastic packaging of products and tools used in tea production, organic fertilizers, even atmospheric deposition. The microplastics in tea gardens are typically fragments and fibers, mainly composed of polyethylene, polypropylene and polyethylene terephthalate. The prevention and control of microplastics in tea planting, tea processing and packaging should be strengthened, and reduce the input of products containing microplastics. Future research on microplastic detection methods in tea and determination of safety thresholds should be prioritized to provide a reference for microplastic contamination risk, control, and management in tea.

Risk Assessment and Application of Tea Frost Hazard in Hangzhou City Based on the Random Forest Algorithm

Using traditional tea frost hazard risk assessment results as sample data, the four indicators of minimum temperature, altitude, tea planting area, and tea yield were selected to consider the risk of hazard-causing factors, the exposure of hazard-bearing bodies, and the vulnerability of hazard-bearing bodies. The random forest algorithm was used to construct the frost hazard risk assessment model of Hangzhou tea, and hazard risk assessment was carried out on tea with different cold resistances in Hangzhou. The model’s accuracy reached 93% after training, and the interpretation reached more than 0.937. According to the risk assessment results of tea with different cold resistance, the high-risk areas of weak cold resistance tea were the most, followed by medium cold resistance and the least strong cold resistance. Compared with the traditional method, the prediction result of the random forest model has a deviation of only 1.57%. Using the random forest model to replace the artificial setting of the weight factor in the traditional method has the advantages of simple operation, high time efficiency, and high result accuracy. The prediction results have been verified by the existing hazard data. The model conforms to the actual situation and has certain guiding for local agricultural production and early warning of hazards.

Hydrophobic-action-driven removal of six organophosphorus pesticides from tea infusion by modified carbonized bacterial cellulose

The abuse of organophosphorus pesticides (OPPs) in tea planting makes it easy to transfer from tea into its infusion, bringing potential health risks to consumers. Thus, it is essential to adopt reliable techniques to remove OPPs from tea infusion. In this study, three treatment methods were used to modify carbonized bacterial cellulose (CBC) to improve its adsorption performance. Among them, CBC treated by hydrazine hydrate (N-CBC) had the best adsorption effect, whose removal rate for dicrotophos is 13 times that of CBC. The in-depth study of adsorption mechanism proved that hydrophobic interaction dominated the adsorption of OPPs onto N-CBC. The pseudo-second-order kinetic model and Langmuir isotherm model were more suitable to describe the process. Additionally, there were no significant changes in tea infusion quality after N-CBC treatment. This work clarifies that N-CBC benefitted from simple preparation method, excellent adsorption performance and unique adsorption mechanism has potential applications in tea infusion.

Response of the Soil Fungal Community and Its Function during the Conversion of Forestland to Tea Plantations: A Case Study in Southeast China

Land-use change is one of the most important driving factors of change in soil microbial diversity. Deforestation for tea plantations has transformed large areas of forestland in hilly areas of Southeast China. However, its impact on the soil fungal community structures and functions is still understudied. We compared the soil fungal communities and their functions in forestland (FD), a 3-year-old tea plantation (ZC3) and a 30-year-old tea plantation (ZC30) at 0–20 cm and 20–40 cm soil depths. The soil fungal community compositions and potential functions were analyzed using high-throughput sequencing techniques coupled with FUNGuild analysis. The results showed that the initial conversion from forestland to tea plantations significantly decreased soil fungal diversity. With an increase in the tea plantation age, the soil fungal diversity rebounded. The dominant phyla included Ascomycota, Basidiomycota, unclassified_k_fungi and Mortierellomycota, which were identified in all soil samples and accounted for 90% of all fungal communities. Non-metric multidimensional scaling analysis (NMDS) indicated that the soil fungal community was more responsive to the duration of tea planting than to the soil depth. FUNGuild analysis showed that the relative abundance of pathogenic and pathotrophic-saprotrophic fungi was higher while saprotrophs were lower in ZC30 compared with FD. Among the analyzed soil properties, soil available nitrogen, available phosphorus, available potassium and bulk density were the prime factors affecting the abundance and diversity of soil fungal community compositions. Network analysis showed that fungal microbial taxa increased positive interactions to enhance the adaptability of fungal microorganisms to long-term tea planting. Collectively, our results provide a clear view on the dynamic yet differential responses of fungal communities to land-use changes, and further emphasizes the need for long-term conventional tea plantations to adopt sustainable agricultural practices to reduce soil pathogenic fungi.

The effect of tea plantation age on soil water-stable aggregates and aggregate-associated carbohydrate in southwestern China

Soil carbohydrates constitute an important component of soil organic matter (SOM), and substantially contribute to the stabilization of soil aggregates. Here, we aimed to investigate the distribution of water-stable aggregates and carbohydrates within water-stable aggregates of soil in tea plantations located in Zhongfeng Township of Mingshan County, Sichuan, which is in southwest China. Samples were collected from tea plantations of different ages (18, 25, 33, and 55 years old) and an area of abandoned land was used as a control(CK). We also examined correlations between soil carbohydrates fractions and aggregate stability. The results showed that the mean weight diameter (MWD) of soil aggregates in the tea plantations was significantly higher than that the control. Furthermore, the soil aggregate stability was significantly enhanced in tea plantations, with the 25-year-old plantation showing the most pronounced effect. Soils in the plantations were also characterized by higher concentrated acid-extracted carbohydrate content, and carbohydrate content in both surface and sub-surface layers were higher in the 25-year-old plantation. We also detected a significant positive correlation between the carbohydrate content of soil and MWD after tea plantation (P < 0.01). Notably, the association between dilute-acid extracted carbohydrate and the aggregate stability showed the highest correlation, indicating this carbohydrate fraction could be used as an index to reflect changes in soil quality during tea plantation development. We should develop a potential fertilisation programme to maintain SOM- Carbohydrates within aggregates and the appropriate pH for preventing soil structure degradation after 25 years of tea planting.

Assessment of gamma radiation through agro-morphological characters in camellia sinensis L. (O.) kuntze

Purpose To study the effects of gamma radiation on tea seed germination, morphological changes, and genetic variation by using gamma radiation. Material and Method Fresh Tea seed material were irradiated with twenty different doses of gamma radiation such as 0, 2, 4, 6, 8, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80 90, 100, 200, 500 and 1000 Gy from Cobalt 60Co source from Regional Nuclear Agriculture Research Center, Bidhan Chandra Krishi Viswavidyalaya (BCKV), West Bengal, in between 2019 and 2020. Result and Conclusion The growth behavior of tea seedling was recorded under varying levels of gamma radiation and its performance at nursery stages. It was observed seed irradiated with doses from 35 Gy to 100 Gy could germinate but could not survive beyond five (05) months. When treated with higher doses as 200 Gy, 500 Gy and 1000 Gy, no seed germination takes places due to possible damages occur in the DNA structure. Screening of growth characteristics of tea plant generally monitored by the characteristics like plant height, number of leaves, number of primary branches, base diameter, and total leaf area of plants and we found that these characteristics significantly increased with the progress of time and increasing levels of gamma radiation; however, the plant height showed decreasing trend with the increasing levels of gamma radiation, which could be due to the change in chromosomal structure and genetic alteration. After 90 weeks of planting, the plant height, no. of primary branches, the number of leaves, plant base diameter, and total leaf area per plant recorded were 36.42 cm, 1/plant, 7.11/plant, 0.62 c.m, 22.92 cm2/plant respectively under the radiation level 30 Gy, whereas the corresponding figures of the above parameters at the control treatment were 85.32 cm, 1/plant, 18.84/plant, 1.18 c.m and 26.68 cm2/plant, respectively. The total plant height, no. of primary branches, the number of leaves, plant base diameter, and total leaf area per plant were significantly influenced by the rising levels of gamma radiation (up to 100 Gy), finally, after 90 weeks of planting, the maximum no. of branching was observed in the treatment of 8 Gy, 10 Gy and 15 Gy respectively. The study reveals a hitherto open the possibility of using gamma radiation on tea plant for creation of variation in the tea seed planting materials. Further studies on mutation using tea planting materials would give an insight into its mutable gene behavior.

The dynamics of tea plantation encroachment into forests and effect on forest landscape pattern during 1991–2021 through time series Landsat images

Tea plantations encroachment into forests has occurred in the major tea planting area of Yunnan province, China in the past decades. However, the dynamics of tea plantation encroachment into forests and the effect on forest landscape pattern is not clear. In this study, we proposed a method to evaluate the dynamic effects of tea plantation encroachment on forest landscape pattern change by using time series Landsat 5/7/8 data from 1991 to 2021 on the Google Earth Engine (GEE) platform. First, a pixel- and phenology-based algorithm was applied to generate tea plantations encroachment into forests maps for seven historical periods. Second, three indices including the tea plantations encroachment index (TPEI), the growth area of tea plantations encroachment into forests (GATEF), and the growth index of tea plantations encroachment into forests (GITEF) were used to quantify the tea plantations encroachment into forests of seven historical periods. Third, the effects of forests landscape pattern resulting from tea plantations encroachment were evaluated in class metrics and landscape metrics respectively. Our results show a total of 13,721 ha of GATEF from the early 1990s to the early 2020s. The GITEF increased from the early 1990s to the early 2010s and decreased from the early 2010s to the early 2020s in our study area. And the TPEI indicates that the edge encroachment mode dominated in our study period. Correlation analysis indicates that tea plantations encroachment level had significant correlation coefficients with landscape pattern indices (such as CONTAG (r = −0.91), ED (r = 0.95), DIVISION (r = 0.85), and SHEI (r = 0.86)), which indicates that the level of tea plantations encroachment affects significantly the forest landscape pattern. This study provides a promising approach to quantifying the effect of forest landscape pattern results from tea plantations encroachment.

Responses of soil nematode community within soil aggregates to tea plantation age.

It is increasingly believed that soil nematodes play an important role in the soil community and have a pronounced influence on the evaluation of soil health and the monitoring of soil food web changes. Soil aggregates provide habitable pore space and resource availability for soil organisms. The distribution of soil nematodes, which are relatively small soil fauna, may be related to the degree of soil aggregates. Soil nematode communities were studied with different soil components: large macro-aggregates (> 2mm), medium macro-aggregates (2-1mm), small macro-aggregates (1-0.25mm), and micro-aggregates (< 0.25mm) extracted from the same crop variety plantings (Sichuan tea) of different ages (19years, 26years, 34years, and 56years) in Sichuan province, southwestern China, in 2018. The results showed that the tea plantation with 26years of cultivation was more suitable for the propagation of nematode communities, and the numbers of total nematodes were highest in the > 2mm fractions. Compared with other tea plantations, the Margalef index (SR) of 26-year-old tea plantation was significantly higher than that within the large and medium macro-aggregates, and the maturity index (MI) was higher in the large and small macro-aggregates in the 26-year-old tea plantation. In the large macro-aggregates, the value of functional metabolic footprints decreased with the tea plantation age. In addition, the functional metabolic footprints increased with the increase in soil aggregate size. Our finding suggests that nematode communities are limited by resource availability and resource quality played an important role in determining nematode communities. Moreover, the soil food web was degenerated with the age of tea cultivation. Therefore, in the study area, it is necessary to pay attention to the rational allocation and application of organic fertilizer in the late stage of tea planting, so as to maintain the soil fertility and soil food web structure of the tea garden.

Metabarcoding of organic tea (Camellia sinensis L.) chronosequence plots elucidates soil acidification-induced shifts in microbial community structure and putative function

Tea (Camellia sinensis L.) agroecosystem soil acidification (TASA) is occurring at epidemic rates relative to other crops, however TASA remains poorly defined in its pathogenesis and effects on soil microbiota. The present study examined bulk soil physicochemical and bacterial 16S rDNA sequence data to elucidate TASA-associated changes through 10 tea agroecosystem sites, including an organic-certified tea field chronosequence of 3-year- (Young), 8-year- (Middle), and 13-year-old (Old) plots. Soil pH declined linearly with age through chronosequence plots. Hierarchical clustering based on community β-diversity revealed a tipping point in community composition as soil acidified below pH 4.5, which had occurred between Middle and Old plots. Tipping point-associated changes in predicted community functionality included a precipitous decline in nitrogenase-encoding communities and concurrent proliferations of Al-detoxifiers, anti-oxidative specialists, and pathogen virulence factor-encoding communities. PERMANOVA modeling revealed that Streptomyces was the genus with population abundance corresponding most significantly with whole microbiome composition at both OTU- (r2 = 0.460, p < 0.001) and genus-levels (r2 = 0.512, p < 0.001), despite ranking 74th in total abundance among 186 core genera, providing computationally-modeled evidence of a keystone role of Streptomyces under tea agroecosystem conditions. Correlations of soil pH with Rhizobiales (r = 0.713, p < 0.001), Acidibacter (r = −0.717, p < 0.001), and predicted β-glucosidase-encoding communities (r = −0.622, p < 0.001) across all samples indicated potential utility as community-level TASA biomarkers. Moreover, two phylogenetically diverse OTU co-abundance modules also corresponded (p < 0.01) with soil pH across all samples, suggesting that TASA-induced shifts were interfaced by networks of diverse and interactive taxa, or keystone guilds. Presently, organic management per se was unable to retain soil pH within the optimal range for tea plant cultivation (pH 4.5–5.5), therefore additional considerations not currently encompassed by organic management guidelines, such as lower tea planting density, may be necessary to avoid the detrimental effects of soil acidification described above. Moreover, future studies may seek to further elucidate the keystone functions of Streptomyces spp. under tea agroecosystem conditions.

Tea Cultivation Suitability Evaluation and Driving Force Analysis Based on AHP and Geodetector Results: A Case Study of Yingde in Guangdong, China

Tea is an economically important crop. Evaluating the suitability of tea can better optimize the regional layout of the tea industry and provide a scientific basis for tea planting plans, which is also conducive to the sustainable development of the tea industry in the long run. Driving force analysis can be carried out to better understand the main influencing factors of tea growth. The main purpose of this study was to evaluate the suitability of tea planting in the study area, determine the prioritization of tea industry development in this area, and provide support for the government’s planning and decision making. This study used Sentinel image data to obtain the current land use data of the study area. The results show that the accuracy of tea plantation classification based on Sentinel images reached 86%, and the total accuracy reached 92%. Then, we selected 14 factors, including climate, soil, terrain, and human-related factors, using the analytic hierarchy process and spatial analysis technology to evaluate the suitability of tea cultivation in the study area and obtain a comprehensive potential distribution map of tea cultivation. The results show that the moderately suitable area (36.81%) accounted for the largest proportion of the tea plantation suitability evaluation, followed by the generally suitable area (31.40%), the highly suitable area (16.91%), and the unsuitable area (16.23%). Among these areas, the highly suitable area is in line with the distribution of tea cultivation at the Yingde municipal level. Finally, to better analyze the contribution of each factor to the suitability of tea, the factors were quantitatively evaluated by the Geodetector model. The most important factors affecting the tea cultivation suitability evaluation were temperature (0.492), precipitation (0.367), slope (0.302), and elevation (0.255). Natural factors influence the evaluation of the suitability of tea cultivation, and the influence of human factors is relatively minor. This study provides an important scientific basis for tea yield policy formulation, tea plantation site selection, and adaptation measures.

Tea–vegetable gardens in Longsheng Nationalities Autonomous County: temporal and spatial distribution, agrobiodiversity and social–ecological values

ABSTRACT The tea–vegetable gardens in Longsheng are particular agro-cultural landscapes constructed by the Miao, Yao and Zhuang nationalities, based on the ecological system in which they are located. Herein, we aimed to clarify the traditional agricultural practices of tea planting in Longsheng and explore the value and characteristics of tea agricultural heritage systems. A household survey among the farming communities and a quadrat investigation of different agroecosystems in the study area were conducted. The results revealed that most tea trees in the study area were 50–80 years old, and only a few ancient tea trees – older than 150 years – remained. A total of 35 vegetables belonging to 15 families were intercropped with tea trees. This agroecosystem is an artificial community in which shrubs (tea trees) form the uppermost layer, crops such as Gramineae, Araceae, Paniceae and Cucurbitaceae, make up the intermediate layer, and the bottom layer comprises low-growing crops such as Convolvulaceae and Cruciferae. Indigenous peoples have shown rich experience and high ecological wisdom in the biological combination of a complex ecological agriculture mode, with time and space configuration, and comprehensive management technology. Hence, we suggest that tea–vegetable gardens should be well documented and effectively conserved.

Enhancing Rural Resilience in a Tea Town of China: Exploring Tea Farmers’ Knowledge Production for Tea Planting, Tea Processing and Tea Tasting

Rural areas have undergone visible transformations in recent decades. It leads to some ecological problems. Enhancing rural resilience is necessary in the face of these changes. However, previous literature often ignored the roles of indigenous actors in this process. Consequently, we conduct participant observation and in-depth interviews to explore the process by which local farmer knowledge is produced in Fenghuang, a rural area that concentrates on the tea industry in China, and how this process contributes to the agriculture resilience of individual and rural areas. We find that local knowledge is a dynamic composition of daily practice highlighting the nature of adaptability in farmers’ pursuits. Such knowledge is found to be constructed, exchanged, and then reshaped into a new and heterogeneous form that involves a mix of scientific forces and local practices, building a solid basis for individual and rural resilience. In addition, both sustainable agriculture and successful market promotion can be achieved by knowledge production. In this way, the meaning of “place” is reconstrued, morphing from a barren and backward rural area to a green and unique land with idyllic beauty. This metamorphosis offers belongingness to tea farmers and imposes on them the responsibility to contribute their efforts to the land.

Research on Tea Tree Growth Monitoring Model Using Soil Information.

Crop growth monitoring is an important component of agricultural information, and suitable soil temperature (ST), soil moisture content (SMC) and soil electrical conductivity (SEC) play a key role in crop growth. Real-time monitoring of the three soil parameters to predict the growth of tea plantation helps tea trees grow healthily and to accurately grasp the growth trend of tea trees. In this paper, five different models based on the polynomial model and power model were used to construct the soil temperature, soil water content and soil conductivity and tea plantation growth monitoring models. Experiments proved that tea plantation growth were positively correlated with ST and negatively correlated with SMC and SEC, and among the constructed models, the ternary cubic polynomial model was the best, and R square (R2) of the constructed models were 0.6369, 0.4510 and 0.5784, respectively, indicating that SEC was the most relevant to tea plantation growth maximum. To improve the prediction accuracy, a model based on sum of soil temperature (SST), sum of soil water content (SSMC) and sum of soil conductivity (SSEC) was proposed, and the experiments also showed that the ternary cubic polynomial model was the best, with 0.9638, 0.9733 and 0.9660, respectively. At the same time, a model incorporating three parameters such as soil temperature, soil water content and soil conductivity was also suggested, with 0.6605 and 0.9761, respectively, which effectively improved the prediction accuracy. Validation experiments were conducted. Twelve data sets were utilized to verify the performance of the model. The experiments showed that the regressions in the polynomial models achieved a better prediction effect. Finally, a long short-term memory (LSTM) network prediction model optimized by the bald eagle search algorithm (BES) was also constructed, and R2, root mean square error (RMSE), mean squared error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of prediction were 0.8666, 0.0629, 0.0040, 0.0436 and 10.5257, respectively, which significantly outperformed the LSTM network and achieved better performance. The model proposed in this paper can be used to predict the actual situation during the growing period of tea leaves, which can improve the production management of tea plantations and also provide a scientific basis for accurate tea planting and a decision basis for agricultural policy formulation, as well as provide technical support for the realization of agricultural modernization.