Tea Planting Research Articles

Impacts of land use structures on ecosystem services relationships within specialized tea planting regions: a case study of Anxi County

The increasing demand for tea has resulted in the swift expansion of tea plantations, leading to significant alterations in the local ecosystem. This has garnered considerable attention. However, research on rationally modifying land use structures (LUSs) in specialized tea regions to achieve a balance with ecosystem services (ESs) and enhance their synergistic effects remains limited. In this study, we quantified the values of water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ) by the InVEST model, utilized K-means clustering to categorize the LUSs of the village areas in Anxi County from 2010 to 2020, and then investigated the influences of the LUSs on the ESs by the improvement of the constraint line tool, according to which we utilized the ecosystem services trade-off degree (ESTD) and the Pearson correlation coefficient to explore the trade-offs and synergies among ecosystem services. The findings indicated that: (1) LUSs in Anxi County are tea garden structure (TS), forest land-tea garden structure (FTS), and construction land-cropland-tea garden structure (CCTS); (2) In LUSs, to achieve a balance among WY, SC, CS, and HQ, the dominant land use proportions were as follows: 0.5 for tea plantations in TS; a range of 0.55–0.6 for forest land and 0.05–0.1 for tea plantations in FTS; and CCTS, 0.25–0.3 for built-up land, 0–0.1 for cropland, and 0.2 for tea plantations; (3) The trade-offs and synergies of ESs vary across different LUSs. The synergy is particularly evident in FTS. Increasing the quantity of forest area is helpful in enhancing the synergy of ESs. This study offers an analysis of the effect of LUSs on ESs and their interconnections in specialized tea planting regions. It serves as a valuable insight into informing urban planning for future land usage and ecological conservation efforts.

Changes in soil organic carbon stocks and mineralization following the replacement of secondary evergreen broadleaf forests with tea (Camellia sinensis L.) plantations

AbstractTea plantation ecosystems have a strong potential to sequester carbon (C) and reduce CO2 emissions. However, the effects of different tea planting periods on soil organic carbon (SOC) stocks and mineralization and related mechanisms are unclear. To address this knowledge gap, we investigated the effects of replacing evergreen broadleaf forests with tea plantations on SOC stocks and mineralization rates by examining alterations in SOC pools and composition, microbial community composition, functional genes related to C‐cycling and enzyme activities. The SOC content in forest, 30‐, 50‐ and 100‐year‐old tea plantations were 1.91%, 2.37%, 2.87% and 3.69%, respectively, in the 0–20 cm soil depth (100‐year‐old > 50‐year‐old > 30‐year‐old > forest). Cumulative CO2–C emissions increased by 38.1% (114 mg C kg−1 soil), 49.9% (157 mg C kg−1 soil), and 100.2% (171 mg C kg−1 soil) compared to forest soil (228 mg C kg−1 soil) after tea had been grown for 30, 50 and 100 years, respectively; however, cumulative CO2 emissions did not differ significantly between the 30‐ and 50‐year‐old plantations. The rate of SOC mineralization was positively related to particulate organic carbon (POC), water‐soluble organic carbon (WSOC), microbial biomass C (MBC), and O‐alkyl C contents, as well as β‐glucosidase/cellobiohydrolase activities and GH48/cbhI abundance; by contrast, the SOC mineralization rate was negatively correlated with the aromatic C content. More importantly, bacteria and fungi related to SOC mineralization, such as WPS‐2 and Acidobacteria, and Sordariomycetes, Tremellomycetes, Mortierellomycetes and Agaricomycetes, respectively, had high relative abundances. Our results indicate that replacing forests with tea plantations enhanced both SOC stocks and mineralization rates and that this effect was positively correlated with tea cultivation time. We reveal that an increased length of the tea planting period was conducive to increasing SOC stocks, and mitigating C losses in tea plantation soils is crucial for establishing an ecologically low‐C tea plantation system.

Discosia brasiliensis causing Discosia leaf blight on tea plant (Camellia sinensis) in China

Tea (Camellia sinensis), a perennial evergreen shrub, is one of the most important cash crops in China. Tea leaves with symptoms of wilt disease was observed in Fengqing County, Lincang City, Yunnan Province, China. Large irregular jujube-red necrotic spots appeared on the leaves of tea plants, and the lesions with grayish white edge were accompanied by a certain degree of shrinkage. In the tea garden planting base, the natural disease incidence reached 40%–50 %, which significantly affects the yield of tea. One putative pathogen was isolated from three symptomatic tea plant leaves and was identified as Discosia brasiliensis using morphology and molecular phylogeny of multi-loci (ITS, LSU, tub, rpb2) sequence data. Using D. brasiliensis strains for artificial inoculation assay on the tea plant leaves, leaf atrophy symptom in leaves which is similar to those observed in the tea planting base, and the putative pathogen was re-isolated to fulfill Koch's postulates. This is the first report of wilt disease caused by Discosia brasiliensis in China.

Assessing the Impacts of Climate Change on Geographical Distribution of Tea (Camellia sinensis L.) in Kenya with Maximum Entropy Model

Climate change has been disturbing the present species distribution ranges, resulting in the shifting of cultivation areas and decreases in production and quality. Tea (Camellia sinensis L.), which seeks optimum climatic resources, is a key cash crop economically in Kenya. In this study, the shifting of tea suitability was projected with the MaxEnt model under the SSP (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) climate scenarios for the 2050s and 2090s relative to the 1970–2000 distribution. Analysis under the current climatic condition showed that the proportions of optimal and medium- and marginal-suitable areas were 2%, 3%, and 24% of the total area, respectively, and located in south-western (SW), central, and north-eastern (NE) Kenya and, to some extent, in the Rift Valley. It was projected that the potential suitable tea-growing areas would migrate from the western areas to the central, eastern, and north-eastern highlands in Kenya. It was detected that the precipitation of the driest period (July), precipitation of the wettest quarter (April, May, and June), and annual temperature range could be the main climatic factors determining the shift in tea distribution. Compared to the current distribution (29%), the climatically suitable areas for tea production could reach 32.58% of Kenya’s land area under the SSP1-2.6 scenarios in the 2050s and 35.08% in the 2090s under the SSP5-8.5 scenario. On the contrary, it was found that the optimal climate-suitable habitats were projected to shrink by 2% and 1% in the 2050s and 2090s under all scenarios on the west side of the Great Rift Valley compared to the current distribution. In comparison, the sizes of medium- and marginal-suitable habitats would increase by 1% and 3%, respectively. The findings indicated that unless adaptive climate actions are taken, climate change could reduce the tea planting areas in western Kenya. Meanwhile, climate suitability was projected to expand upward on the east side of the Rift Valley, enhancing the potential distribution of tea. The developed climate information could be used to design and implement adaptation interventions in the lower elevation areas. Finally, we highlight that the available scientific literature on the climate suitability of tea in Kenya should be broadened by adding non-climatic factors.

Deep migration learning-based recognition of diseases and insect pests in Yunnan tea under complex environments

BackgroundThe occurrence, development, and outbreak of tea diseases and pests pose a significant challenge to the quality and yield of tea, necessitating prompt identification and control measures. Given the vast array of tea diseases and pests, coupled with the intricacies of the tea planting environment, accurate and rapid diagnosis remains elusive. In addressing this issue, the present study investigates the utilization of transfer learning convolution neural networks for the identification of tea diseases and pests. Our objective is to facilitate the accurate and expeditious detection of diseases and pests affecting the Yunnan Big leaf kind of tea within its complex ecological niche.ResultsInitially, we gathered 1878 image data encompassing 10 prevalent types of tea diseases and pests from complex environments within tea plantations, compiling a comprehensive dataset. Additionally, we employed data augmentation techniques to enrich the sample diversity. Leveraging the ImageNet pre-trained model, we conducted a comprehensive evaluation and identified the Xception architecture as the most effective model. Notably, the integration of an attention mechanism within the Xeption model did not yield improvements in recognition performance. Subsequently, through transfer learning and the freezing core strategy, we achieved a test accuracy rate of 98.58% and a verification accuracy rate of 98.2310%.ConclusionsThese outcomes signify a significant stride towards accurate and timely detection, holding promise for enhancing the sustainability and productivity of Yunnan tea. Our findings provide a theoretical foundation and technical guidance for the development of online detection technologies for tea diseases and pests in Yunnan.

Distribution characteristics of potentially toxic metal(loid)s in the soil and in tea plant (Camellia sinensis)

Potentially toxic metal(loid) assessment of tea and tea garden soil is a vital guarantee of tea safety and is very necessary. This study analyzed the distribution of seven potentially toxic metal(loid)s in different organs of the tea plants and soil at various depths in the Yangai tea farm of Guiyang City, Guizhou Province, China. Although soil potentially toxic metal(loid) in the study area is safe, there should be attention to the health risks of Cu, Ni, As, and Pb in the later stages of tea garden management. Soil As and Pb are primarily from anthropogenic sources, soil Zn is mainly affected by natural sources and human activities, and soil with other potentially toxic metal(loid) is predominantly from natural sources. Tea plants might be the enrichment of Zn and the exclusion or tolerance of As, Cu, Ni, and Pb. The tea plant has a strong ability for absorbing Cd and preferentially storing it in its roots, stems, and mature leaves. Although the Cd and other potentially toxic metal(loid)s content of tea in Guizhou Province is generally within the range of edible safety, with the increase of tea planting years, it is essential to take corresponding measures to prevent the potential health risks of Cd and other potentially toxic metal(loid)s in tea.

Critical Threshold-Based Heat Damage Evolution Monitoring to Tea Plants with Remotely Sensed LST over Mainland China

Tea plants (Camellia sinensis (L.) Kuntze) are a cash crop that thrive under warm and moist conditions. However, tea plants are becoming increasingly vulnerable to heat damage (HD) during summer growing seasons due to global climate warming. Because China ranks first in the world in both harvested tea area and total tea production, monitoring and tracking HD to tea plants in a timely manner has become a significant and urgent task for scientists and tea producers in China. In this study, the spatiotemporal characteristics of HD evolution were analyzed, and a tracking method using HD LST-weighted geographical centroids was constructed based on HD pixels identified by the critical LST threshold and daytime MYD11A1 products over the major tea planting regions of mainland China from two typical HD years (2013 and 2022). Results showed that the average number of HD days in 2022 was five more than in 2013. Daily HD extent increased at a rate of 0.66% per day in 2022, which was faster than that in 2013 with a rate of 0.21% per day. In two typical HD years, the tea regions with the greatest HD extent were concentrated south of the Yangtze River (SYR), with average HD pixel ratios of greater than 50%, then north of the Yangtze River (NYR) and southwest China (SWC), with average HD pixel ratios of around 40%. The regions with the least HD extent were in South China (SC), where the HD ratios were less than 40%. The HD LST-weighted geographical centroid trajectories showed that HD to tea plants in 2013 initially moved from southwest to northeast, and then moved west. In 2022, HD moved from northeast to west and south. Daily HD centroids were mainly concentrated at the conjunction of SYR, SWC, and SC in 2013, and in northern SWC in 2022, where they were near to the centroid of the tea planting gardens. The findings in this study confirmed that monitoring HD evolution of tea plants over a large spatial extent based on reconstructed remotely sensed LST values and critical threshold was an effective method benefiting from available MODIS LST products. Moreover, this method can identify and track the spatial distribution characteristics of HD to tea plants in a timely manner, and it will therefore be helpful for taking effective preventative measures to mitigate economic losses resulting from HD.

Different “nongrain” activities affect the accumulation of heavy metals and their source-oriented health risks on cultivated lands

“Nongrain” production on cultivated land is one of the primary environmental issues in China. Different “nongrain” activities may introduce different pollution sources to the local environment, leading to variations in heavy metal contents in soil, which can profoundly impact national food security. In this study, three typical “nongrain” regions (Nanxun (NX), Xiaoshan (XS) and Lin'an (LA)) with intensive aquaculture, tea planting and flower (seedling) growth on cultivated land around the Hangzhou metropolitan area were selected to address the spatial heterogeneity of accumulation levels, sources and source-oriented health risks of heavy metals in soil. The results showed that Hg was the main pollutant in NX and XS, while Cd and As were the major contaminants in LA. Aquiculture and sericultural industries (37.43%), natural sources (23.59%) and industrial activities (38.99%) were the major sources in NX; atmospheric deposition (37.73%), flower and seedling planting (23.49%) and metal-related industries (35.16%) were the major sources in XS; and atmospheric deposition (28.06%), excessive application of fertilizers and pesticides during tea planting (43.47%) and natural sources (28.47%) were the major sources in LA. The major risk population, area, exposure route and hazardous elements were children, LA, ingestion and As and Cr, respectively. From the perspective of source-based health risk assessment, in addition to natural sources that are difficult to intervene in, industrial activities, especially leather and wood process industries, metal-related industries and excessive fertilizer and pesticide application during tea planting contributed the most to the total health risk, which explained 67%, 41% and 42%, respectively, of the total risk in NX, XS and LA. High health risks are present in sources with heavy loadings of hazardous heavy metals (As and Cr); thus, to protect human health, the corresponding high-risk anthropogenic pollution sources in different “nongrain” areas need to be controlled.

Ampelopsis grossedentata Represents a New Host of the 16SrI Group of Phytoplasma Associated with Yellow Leaf Symptoms in China.

Ampelopsis grossedentata, commonly known as "Vine Tea" and well-recognized for its rich flavonoid content, is mainly distributed in the southern regions of the Yangtze River basin in China. These regions include Hunan, Hubei, Jiangxi, and Guizhou provinces. Vine Tea is mainly consumed as an herbal tea and has garnered attention for its reported health benefits, including antioxidant, anti-inflammatory, anti-tumor, anti-diabetic, and neuroprotective properties. It has been used to alleviate coughs and sore throats (Zhang et al., 2021; Wang et al., 2017; Gao et al., 2009). In the Zhangjiajie region of Hunan province alone, the Vine Tea planting area reached 7,670.5 hectares and produced commercial goods worth 1.417 billion RMB in 2022. In May 2021, leaf margins and veins fading to yellowing mottling, and crumpling of leaf blades in the shape of a boat symptoms were found in ~16% of Vine Tea plants in the Sanjiakuan Township, Yongding District, Zhangjiajie region (29°15'E, 110°30' N) (Figure 1a, b, c). (Figure 1a, b, c). Phytoplasma-like microbial cells (small oval shaped bacterial cells, around 1000 nm in size) were observed in sieve tube cells in the phloem of diseased leaves using transmission electron microscopy. No such cell was observed in the phloem of healthy leaves (Figure 2a, b). To investigate the potential association between phytoplasma and the observed symptoms of the diseased plants, total DNA was isolated from ten diseasedeaves and compared with ten healthy leaves from the same field using SteadyPure Plant Genomic DNA Extraction Kit. The isolated DNAs were analyzed first in a direct PCR using universal phytoplasma primer pair R16mF2/R16mR1 targeting the 16S rRNA gene (Gundersen and Lee 1996) and specific pair rpF1/rpR1 (Lee et al. 1998) targeting the DNA fragment encoding partial ribosomal proteins (rp) L22 (complete) and S3 and S19 (partial). The initial amplified products were used as templates and further amplified by nested PCR respectively with primer pair R16F2n/R16R2 for the 16S rRNA gene (Lee et al. 1998) and the rpF2/rpR2 primer pair for the rp gene (Martini et al. 2007). No amplification was obtained with DNA from healthy leaf samples using any of the four primer pairs. The amplified fragments from diseased leaves by nested PCR were cloned and sequenced (Qingke Biotech, China). The obtained sequences have been deposited in GenBank with accession numbers OR282806 for the 16S rRNA gene and GenBank OR353012 for the rp gene. BLASTn analysis revealed that the partial 16S rRNA gene sequence in our sample shared 99.4% nucleotide sequence identity with 'Candidatus Phytoplasma sp.' (MW364378) and 'Peony yellows phytoplasma' (KY814723) of the 16SrI group. Similarly, our rp gene sequence shared 99.6% nucleotide identity with the rpI group of phytoplasma such as the 'Balsamine virescence phytoplasma' (JN572890) and 'Paulownia witches'-broom phytoplasma' (HM146079). Phylogenetic analysis of the 16S rRNA and rp sequences using MEGA version 7.0 revealed that the phytoplasma strain associated with A. grossedentata yellow leaf syndrome in our study site belonged to the 16SrI (Candidatus Phytoplasma asteris) group of phytoplasma (Figure 3a, b). Using the interactive online phytoplasma classification tool iPhyClassifier (Zhao et al., 2009), virtual restriction fragment length polymorphism (RFLP) analysis of the 16S rRNA gene sequences showed our strain having a distinct RFLP map but was closest to that of the onion yellow phytoplasma 16SrI-B subgroup (GenBank accession number: AP006628), with a similarity coefficient of 0.94 (Figure 4a, b). To confirm phytoplasma transmission, healthy plants were inoculated with three scions of infected plants of A. grossedentata. After 16 days, the new leaves of the inoculated A. grossedentata showed yellow leaf symptoms (Figure 5a, b, c), akin to the symptoms originally observed in the field, and the outer contour of the leaf margin appeared chlorotic. After 26 days, primer pairs R16mF2/R16R1 and R16F2n/R16R2 were used for nested PCR detection of phytoplasma in symptomatic A. grossedentata leaves. Phytoplasma was detected in the first and second leaves of symptomatic branches and leaves while negative control showed no amplification. Sequencing of the amplified fragments showed 100% nucleotide identity to the strain from the grafting source. Our results indicated that the pathogen and the disease can be transmitted by tissue grafting, consistent with the biological characteristics of phytoplasma, and further confirmed that the phytoplasma was the pathogen of yellow leaf syndrome of A. grossedentata. Toour knowledge, this is the first report of phytoplasma of group 16SrI affecting A. grossedentata.

Patterns of Nitrogen and Phosphorus along a Chronosequence of Tea Plantations in Subtropical China

Nitrogen (N) and phosphorus (P) play crucial roles in tea planting, but information on how the long-term excessive application of chemical N fertilizer affected N and P in subtropical tea plantations remains limited. In this study, soil and leaf samples were collected along a chronosequence of tea plantations (0-, 5-, 10-, 18- and 23-year-old plantations) with excessive N input but no P application to investigate the effects of planting age on N and P availability. Diverse soil N forms and P fractions, and the concentrations of leaf N and P were measured. The results showed that (1) NO3−-N and dissolved organic nitrogen (DON) concentrations in both topsoil and subsoil, and the N concentration of mature leaf showed significant upward trends with tea plantation age; (2) the concentrations of available phosphorus (AP), NaHCO3-Pi in labile P pool, NaOH-Pi and D.HCl-Pi in moderately labile P pool in both layers of soil and that the P concentration of mature leaf also increased with age; (3) the N concentration of mature leaves had closely significant logarithmic relations with NO3−-N concentration, while the TP (total P) concentration of mature leaves had significant positive correlations with AP; and (4) the ratio of N/P in tea leaves indicated a slightly P limitation in tea plantations. We concluded that the NO3−-N concentration, instead of TN (total N) of NH4+-N, would be a good indicator to reflect N availability for tea trees, and the increasing of NO3−-N concentration in soil has a diminishing promoting effect on the TN concentration of mature leaves. The long-term application of chemical N fertilizer had not lead to serious P limitation in subtropical tea plantations. Generally, our study could contribute to improving our understanding of N and P availability and optimizing fertilization management in subtropical tea plantations.

Carbon footprints of tea production in smallholder plantations: A case study of Fenghuang Dancong tea in China

The high fertilizer application in tea planting and the large energy consumption in tea processing have raised concerns about greenhouse gas (GHG) emissions of tea production. China is the world's largest tea production country, but its tea production is dominated by smallholder farmers. Therefore, when it comes to GHG emission reduction in tea production, specific measures need to be developed for the smallholder mode. The purpose of this study is to reveal the characteristics and influencing factors of GHG emissions of smallholder tea plantations, as well as to develop GHG emission reduction measures suitable for the smallholder mode. Here, we focus on Fenghuang Dancong tea and two types of smallholder tea plantations, the high-altitude tea plantation (HTP11HTP: the high-altitude tea plantation; MLP: the mid-low-altitude tea plantation; CF: carbon footprint; GHG: greenhouse gas; CO2-eq: CO2 emission equivalent; LCA: life cycle assessment.) and the mid-low-altitude tea plantation (MLP), in Fenghuang Town, Chaozhou City, China. The carbon footprint (CF) method is employed, which is a widely used method for estimating GHG emissions and expressed in CO2 emission equivalent (CO2-eq). The assessment on the CF of the Fenghuang Dancong tea production and a comparative analysis between the HTP and the MLP have been made. Results show that (1) at the tea planting stage, fertilizer input is the main contributor to the CFplanting; electricity input is the primary component of the CFprocessing at the tea processing stage; (2) considering the two stages of tea planting and processing, the CFtea of the MLP is more than twice that of the HTP; (3) the production and management measures adopted by tea farmers have a significant impact on the CFtea, which are mainly driven by economic interests. In view of these findings, we emphasize the importance of balancing GHG emission reduction with economic benefits and propose GHG emission reduction measures such as formulating subsidy policies for organic fertilizers, promoting green and organic product certification, improving the energy input structure and strengthening scientific guidance. We submit that this study will not only help local managers formulate efficient GHG emission reduction measures, but also provide references for other studies on GHG emissions of tea production in the smallholder mode.

The Analysis of Sustainable Business Model in Traditional Chinese Tea Industry

Since ancient times, China has been a great tea country, the worlds largest tea planting area, and the worlds top tea production. Over the entire Chinese tea industry, there are countless large and small tea factories but few famous tea brands, seriously affecting the industrys sustainable development. Thus, creating a famous tea brand is a huge challenge for Chinese tea. In addition, the world currently cultivates tea in many countries, such as Sri Lanka, India, Turkey, Kenya, etc. China is a large tea producer and is always an important economic crop. With the modern, fast-paced urban life, the new tea consumption style is more suitable for the domestic and international consumer market and meets the needs of the public. This paper explores to convert and upgrade the traditional Chinese tea industrys business model by recognizing and analyzing the globally well-known brand Lipton Tea. Firstly, it is no longer limited to the traditional tea culture, and combining the tea culture with commercial activities to create a fashionable tea culture; secondly, to apply the tea to a wider range of consumer markets rather than limiting it to the tea-drinking market only; and then through the assistance of new media such as e-commerce and We media to promote the product, this series of upgrading from the internal to the external business model can improve the popularity of Chinese tea brands, the rapid development of the tea industry will also give Chinas economic market to bring sustainable development of the new power.

Corrigendum: Water Supply 1 May 2023; 23 (5): 2197–2209. Evaluation on real-time self-organization algorithm of forest cultivation, tea planting, and tea processing for sustainable ecosystem management of agricultural water resources. Zhenhong Wang, Liyong Zhang, Minfeng Song, Sangjie Luobu, Jiumei, Danzhen, Hong Peng

Corrigendum: <i>Water Supply</i> 1 May 2023; 23 (5): 2197–2209. Evaluation on real-time self-organization algorithm of forest cultivation, tea planting, and tea processing for sustainable ecosystem management of agricultural water resources. Zhenhong Wang, Liyong Zhang, Minfeng Song, Sangjie Luobu, Jiumei, Danzhen, Hong Peng

Oolong tea cultivars categorization and germination period classification based on multispectral information.

Recognizing and identifying tea plant (Camellia sinensis) cultivar plays a significant role in tea planting and germplasm resource management, particularly for oolong tea. There is a wide range of high-quality oolong tea with diverse varieties of tea plants that are suitable for oolong tea production. The conventional method for identifying and confirming tea cultivars involves visual assessment. Machine learning and computer vision-based automatic classification methods offer efficient and non-invasive alternatives for rapid categorization. Despite advancements in technology, the identification and classification of tea cultivars still pose a complex challenge. This paper utilized machine learning approaches for classifying 18 oolong tea cultivars based on 27 multispectral characteristics. Then the SVM classification model was executed using three optimization algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), and grey wolf optimizer (GWO). The results revealed that the SVM model optimized by GWO achieved the best performance, with an average discrimination rate of 99.91%, 93.30% and 92.63% for the training set, test set and validation set, respectively. In addition, based on the multispectral information (h, s, r, b, L, Asm, Var, Hom, Dis, σ, S, G, RVI, DVI, VOG), the germination period of oolong tea cultivars can be completely evaluated by Fisher discriminant analysis. The study indicated that the practical protection of tea plants through automated and precise classification of oolong tea cultivars and germination periods is feasible by utilizing multispectral imaging system.

The Impact of the Establishment of the Mount Wuyi National Park on the Livelihood of Farmers

The construction of national parks has a profound impact on the production and life of surrounding farmers. Based on the survey data of 354 farmers around the Mount Wuyi National Park, this paper uses the method of constructing a difference-in-difference model to analyze the impact of the Mount Wuyi National Park construction on the livelihood choices of surrounding farmers and the main income of families. In addition, this article analyzes the heterogeneity of surrounding farmers based on differences in tea planting area and farmers’ income levels. The results show the following: First, compared with pre-establishment, farmers around the Mount Wuyi National Park still prefer tea-based agricultural employment or part-time employment. Second, after the establishment of the Mount Wuyi National Park, the main income of surrounding farmers’ families is still agricultural income. Therefore, the authors of this article believe that it is necessary to further strengthen the protection of the livelihoods of surrounding farmers and moderately create more livelihood choices for surrounding farmers in order to achieve both ecological and economic benefits.

Current Status and Health Risk Assessment of Heavy Metals Contamination in Tea across China.

Tea is a non-alcoholic beverage popular among Chinese people. However, due to the application of chemical and organic fertilizers in the tea planting process, the environment pollutionaround the tea plantation, and the instruments used in the processing, heavy metal elements will accumulate in the tea, which brings health risks for tea consumers. This study summarized heavy metal concentrations from 227 published papers and investigated the current contamination status of tea and tea plantation soils, and, finally, the risk of heavy metal exposure to tea consumers in China is assessed, in terms of both non-carcinogenic and carcinogenic risk. The average contamination of six heavy metals in tea-arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), and lead (Pb)-were 0.21, 0.14, 1.17, 14.6, 0.04, and 1.09 mg/kg, respectively. The areas with high concentrations of heavy metals in tea were concentrated primarily in southwest China, some areas in eastern China, and Shaanxi Province in northwest China. The non-carcinogenic risks of heavy metals in tea are all within safe limits. The national average HI value was 0.04, with the highest HI value of 0.18 in Tibet, which has the largest tea consumption in China. However, the carcinogenic risks of Cd in Shaanxi Province, Anhui Province, and southwest China exceed the acceptable range, and due attention should be given to these areas.

Factors influencing the spatiotemporal variation in the value of ecosystem services in Anxi county

Understanding the value of ecosystem services is imperative for the welfare of current and future generations. Anxi town is situated within the mountainous terrain of Fujian province, China and characterized by a diverse range of ecosystems encompassing forests, rivers, and mountains. These ecosystems offer a wide range of ecosystem services. The value of ecosystem services has been declining in the county for the past twenty-years. However, limited is known on the spatial changes and factors affecting the value of these Therefore, current study assessed the spatial changes in the value of ecosystem services (provisioning, regulating, supporting, and cultural) in 24 townships situated in the county for three time periods, i.e., 1999, 2009, and 2019 and factors affecting these services. The results revealed that annual decline in the value of ecosystem services was higher in 1999–2009 than 2009–2019. Longjuan, Xianghua, Gande, Futian, Changkeng, Xiping, Taozhou and Huqiu townships observed the highest annual decline in the value of ecosystem services ranging from 20.1 to 68.1 million yuan. The GWR model indicated that vegetation index had the highest impact on the value of ecosystem services in the county. Overall, the value of ecosystem services was negatively correlated with the urbanization rate and distance from the road with some exceptions, whereas altitude had a positive impact. All townships (except Xianghua, Futian, and Taozhou) had negative values for water supply services. Hence, water supply is a significant ecological issue in the county. It is concluded that tea farmers in the county should be educated about water and soil conservation, investment should be done in conservation measures, regional ecological environments should be protected, and ecological tea planting techniques should be developed in the county to halt further decrease in the value of ecosystem services.

Determining the critical threshold of meteorological heat damage to tea plants based on MODIS LST products for tea planting areas in China

Tea (Camellia sinensis (L.) Kuntze) is a daily drink in modern life throughout the world. Global warming increases the exposure of tea plants to elevated heat conditions during the summer picking period. Therefore, it is a fundamental function of the meteorological service to determine the critical temperature threshold that triggers heat damage (HD) to tea plants. In this study, MODIS daytime land surface temperature (LST) products obtained from the Aqua satellite (MYD11A1), annual land cover type products (MCD12Q1), and actual HD records were jointly used to determine the critical LST threshold resulting in HD to tea planting areas in China. An LST dataset of HD and HD-free samples was constructed based on actual HD records. The box-plot method was then used to delineate the range of LST outliers in HD to tea plants. The cumulative frequency distribution (CFD) method was adopted to determine the critical LST threshold by searching for the maximum slope of CFD within the range of LST outliers based on 2901 actual HD samples from 42 agrometeorological stations in 11 provinces in China. Results showed that the critical LST threshold triggering HD to tea plants was 30.1 °C. Two different HD data sources (i.e., 68 counties in eight provinces from the Meteorological Disaster Management System (MDMS) and 37 counties in six cities from a published book) were used as HD validation samples. Validation accuracy analysis revealed that a critical LST threshold of 30.1 °C was reasonable, with an average accuracy of between 60% and 90% for the published-book dataset, and 75.7% in the northern Yangtze River area and 86.3% in the southern Yangtze River area for the MDMS dataset. This study confirmed that using remotely sensed LST products is an effective method for identifying temperature-related agrometeorological disasters owing to the method's ability to intuitively capture the surface temperature distribution of the disaster-affected object. The findings will be helpful for identifying the timing and location of HD to tea plants, and thereby potentially preventing HD to tea plants.

Response of Soil Microbial Communities and Functions to Long-Term Tea (Camellia sinensis L.) Planting in a Subtropical Region

Soil microbes are the key to revealing the mechanisms driving variation in soil biogeochemical processes. In recent decades, forests in Southeast China have been widely transformed into tea plantations due to the drivers of economic benefits. However, the changes in the soil microbial community and their potential function during the transition from a typical forest ecosystem to tea plantations remain poorly understood. This study investigated the soil microbial community in tea plantation soils with different planting ages, i.e., 6, 12, 23 and 35 years, and in an adjacent woodland control. We discovered that tea planting significantly increased soil bacterial richness (ACE and Chao1) and decreased fungal richness, the diversity of bacteria (Simpson and Shannon) show a trend of initially decreasing and then increasing while there was no significant effect on fungal diversity. After tea planting, the relative abundances of Actinobacteria and Proteobacteria increased by 180.9%–386.6% and 62.3%–97.5%, respectively; the relative abundances of Acidobacteria decreased by 11.4%–66.8%. However, the fungal phyla were not significantly different among different aged tea plantations and woodlands. FAPROTAX and FUNGuild revealed that the transition of natural woodland to tea plantations significantly increased the relative abundances of aerobic_chemoheterotrophy (14.66%–22.69%), chemoheterotrophy (34.36%–37.04%), ureolysis (0.68%–1.35%) and pathogenic fungi (26.17%–37.02%). db-RDA proved that the bacterial community structure was more strongly related to soil pH and available nitrogen (AN), while the main determinants of the fungal community composition were soil pH and soil organic matter (SOM). These findings indicate that tea planting has a strong effect on the soil microbial community and potential function. The change in soil pH during tea planting was the most important factor affecting the soil microbial community, while soil bacteria were more sensitive to tea planting than fungi.

Light Intensity Regulates Low-Temperature Adaptability of Tea Plant through ROS Stress and Developmental Programs.

Low-temperature stress limits global tea planting areas and production efficiency. Light is another essential ecological factor that acts in conjunction with temperature in the plant life cycle. However, it is unclear whether the differential light environment affects the low temperature adaptability of tea plant (Camellia sect. Thea). In this study, tea plant materials in three groups of light intensity treatments showed differentiated characteristics for low-temperature adaptability. Strong light (ST, 240 μmol·m-2·s-1) caused the degradation of chlorophyll and a decrease in peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), and polyphenol oxidase (PPO) activities, as well as an increase in soluble sugar, soluble protein, malondialdehyde (MDA), and relative conductivity in tea leaves. In contrast, antioxidant enzyme activities, chlorophyll content, and relative conductivity were highest in weak light (WT, 15 μmol·m-2·s-1). Damage was observed in both ST and WT materials relative to moderate light intensity (MT, 160 μmol·m-2·s-1) in a frost resistance test. Chlorophyll degradation in strong light was a behavior that prevented photodamage, and the maximum photosynthetic quantum yield of PS II (Fv/Fm) decreased with increasing light intensity. This suggests that the browning that occurs on the leaf surface of ST materials through frost may have been stressed by the previous increase in reactive oxygen species (ROS). Frost intolerance of WT materials is mainly related to delayed tissue development and tenderness holding. Interestingly, transcriptome sequencing revealed that stronger light favors starch biosynthesis, while cellulose biosynthesis is enhanced in weaker light. It showed that light intensity mediated the form of carbon fixation in tea plant, and this was associated with low-temperature adaptability.